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Fan L, Ma L, Ling R, Guo X, Li H, Yang D, Lian Z. Clinical value of conventional magnetic resonance imaging combined with diffusion-weighted imaging in predicting pelvic lymph node metastasis of cervical cancer. Front Oncol 2023; 13:1267598. [PMID: 38188298 PMCID: PMC10766846 DOI: 10.3389/fonc.2023.1267598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 12/11/2023] [Indexed: 01/09/2024] Open
Abstract
Background In cervical cancer (CC), the involvement of pelvis lymph nodes is a crucial factor for patients' outcome. We aimed to investigate the value of conventional magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) in predicting CC pelvic lymph node metastasis (PLNM). Methods This retrospective study included CC patients who received surgical treatments. Surgical pathology results served as the gold standard for investigating the diagnostic performance of conventional MRI combined with DWI. We analyzed the association between tumor ADC and PLNM, as well as other pathological factors. The areas under the receiver operating characteristic curves (AUCs) for ADC in assessing PLNM and pathological factors were evaluated, and optimal cut-off points were obtained. Results A total of 261 CC patients were analyzed. PLNM patients had significantly lower tumor ADC (0.829 ± 0.144×10-3mm2/s vs. 1.064 ± 0.345×10-3mm2/s, p<0.0001), than non-PLNM CC. The agreement between conventional MRI combined with DWI and pathological results on PLNM diagnosis was substantial (Kappa=0.7031, p<0.0001), with 76% sensitivity, 94.31% specificity, and 90.8% accuracy. The AUC of tumor ADC was 0.703, and the optimal cut-off was 0.95×10-3 mm2/s. In multivariate analysis model 1, tumor ADC<0.95×10-3mm2/s was significantly associated with PLNM (OR, 2.83; 95%CI, 1.08-7.43; p= 0.0346) after adjusting for age and pathological risk factors. In multivariate analysis model 2, tumor ADC<0.95×10-3mm2/s (OR, 4.00; 95%CI, 1.61-9.89; p=0.0027), age<35 years old (OR, 2.93; 95%CI, 1.04-8.30; p=0.0428), increased tumor diameter on MRI (OR, 2.17; 95%CI, 1.18-3.99; p=0.0128), vaginal vault involvement on MRI (OR, 2; 95%CI, 1.002-3.99; p=0.0494) were independent predictors for PLNM. Tumor ADC<0.95×10-3mm2/s was significantly associated with higher risk of tumor diameter ≥4cm (OR, 2.60; 95%CI, 1.43-4.73; p=0.0017), muscular layer infiltration >1/2 (OR, 5.46; 95%CI, 3.19-9.34; p<0.0001), vaginal vault involvement (OR, 2.25; 95%CI, 1.28-3.96; p=0.0051), and lymphovascular space involvement (OR, 3.81; 95%CI, 2.19-6.63; p<0.0001). Conclusion Conventional MRI combined with DWI had a good diagnostic performance in detecting PLNM. The tumor ADC value in PLNM patients was significantly lower than that in non-PLNM patients. Tumor ADC <0.95×10-3mm2/s, age <35 years old, increased tumor diameter on MRI, vaginal vault involvement on MRI were independent predictors for PLNM.
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Affiliation(s)
- Leilei Fan
- Department of Gynecology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Liguo Ma
- Department of Gynecology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Rennan Ling
- Department of Radiology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Xiaojing Guo
- Department of Pathology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Haili Li
- Department of Gynecology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Degui Yang
- Department of Gynecology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Zhesi Lian
- Department of Public Health, Tufts University School of Medicine, Boston, MA, United States
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Chen J, Ma N, Sun M, Chen L, Yao Q, Chen X, Lin C, Lu Y, Lin Y, Lin L, Fan X, Chen Y, Wu J, He H. Prognostic value of apparent diffusion coefficient in neuroendocrine carcinomas of the uterine cervix. PeerJ 2023; 11:e15084. [PMID: 37020850 PMCID: PMC10069420 DOI: 10.7717/peerj.15084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 02/25/2023] [Indexed: 04/03/2023] Open
Abstract
Objectives
This research was designed to examine the associations between the apparent diffusion coefficient (ADC) values and clinicopathological parameters, and to explore the prognostic value of ADC values in predicting the International Federation of Gynecology and Obstetrics (FIGO) stage and outcome of patients suffering from neuroendocrine carcinomas of the uterine cervix (NECCs).
Methods
This retrospective study included 83 patients with NECCs, who had undergone pre-treatment magnetic resonance imaging (MRI) between November 2002 and June 2019. The median follow-up period was 50.7 months. Regions of interest (ROIs) were drawn manually by two radiologists. ADC values in the lesions were calculated using the Functool software. These values were compared between different clinicopathological parameters groups. The Kaplan–Meier approach was adopted to forecast survival rates. Prognostic factors were decided by the Cox regression method.
Results
In the cohort of 83 patients, nine, 42, 23, and nine patients were in stage I, II, III, and IV, respectively. ADCmean, ADCmax, and ADCmin were greatly lower in stage IIB–IVB than in stage I–IIA tumours, as well as in tumours measuring ≥ 4 cm than in those < 4 cm. ADCmean, FIGO stage, and age at dianosis were independent prognostic variables for the 5-year overall survival (OS). ADCmin, FIGO stage, age at diagnosis and para-aortic lymph node metastasis were independent prognostic variables for the 5-year progression-free survival (PFS) in multivariate analysis. For surgically treated patients (n = 45), ADCmax was an independent prognostic parameter for both 5-year OS and 5-year PFS.
Conclusions
ADCmean, ADCmin, and ADCmax are independent prognostic factors for NECCs. ADC analysis could be useful in predicting the survival outcomes in patients with NECCs.
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Affiliation(s)
- Jian Chen
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Ning Ma
- Department of Radiology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Mingyao Sun
- Department of Clinical Nutrition, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Li Chen
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Qimin Yao
- College of Finance, Fujian Jiangxia University, Fuzhou, Fujian, China
| | - XingFa Chen
- Department of Radiology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Cuibo Lin
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Yongwei Lu
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Yingtao Lin
- Department of Drug Clinical Trial Institution, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Liang Lin
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Xuexiong Fan
- Department of Medical Record, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Yiyu Chen
- Department of Pathology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Jingjing Wu
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Haixin He
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
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Qian W, Chen Q, Hu C. Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis for Assessing Normal-Sized Lymph Node Metastasis in Cervical Cancer: Comparison Between Readout-Segmented and Single-Shot Echo-Planar Diffusion-Weighted Imaging. J Comput Assist Tomogr 2023; Publish Ahead of Print:00004728-990000000-00161. [PMID: 37380155 DOI: 10.1097/rct.0000000000001463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
OBJECTIVE To compare the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis derived from readout-segmented echo-planar imaging (RS-EPI) and single-shot echo-planar imaging (SS-EPI) diffusion-weighted imaging (DWI) in evaluating normal-sized lymph node metastasis (LNM) in cervical cancer. METHODS Seventy-six pathologically confirmed cervical cancer patients (stages IB and IIA) were enrolled, including 61 patients with non-LNM (group A) and 15 patients with normal-sized LNM (group B). The recorded tumor volume on T2-weighted imaging was the reference against which both DWIs were evaluated. Each ADC histogram parameter (including ADCmax, ADC90, ADCmedian, ADCmean, ADC10, ADCmin, ADCskewness, ADCkurtosis, and ADCentropy) was compared between SS-EPI and RS-EPI and between the 2 groups. RESULTS There was no significant difference in tumor volume between the 2 DWIs and T2-weighted imaging (both P > 0.05). Higher ADCmax and ADCentropy but lower ADC10, ADCmin and ADCskewness were found in SS-EPI than those in RS-EPI (all P < 0.05). For SS-EPI, lower ADC90 and higher ADCkurtosis were found in group B than those in group A (both P < 0.05). For RS-EPI, lower ADC90 and higher ADCkurtosis and ADCentropy were found in group B than those in group A (all P < 0.05). Readout-segmented echo-planar imaging ADCkurtosis showed the highest area under the curve of 0.792 in the differentiation of the 2 groups (sensitivity, 80%; specificity, 73.77%). CONCLUSIONS Compared with SS-EPI, the ADC histogram parameters derived from RS-EPI were more accurate, and ADCkurtosis held great potential in differentiating normal-sized LNM in cervical cancer.
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Affiliation(s)
| | - Qian Chen
- Department of Radiology, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou City, Jiangsu Province, China
| | - Chunhong Hu
- From the Department of Radiology, the First Affiliated Hospital of Soochow University; and
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Tang Q, Zhou Q, Chen W, Sang L, Xing Y, Liu C, Wang K, Liu WV, Xu L. A feasibility study of reduced full-of-view synthetic high-b-value diffusion-weighted imaging in uterine tumors. Insights Imaging 2023; 14:12. [PMID: 36645541 PMCID: PMC9842823 DOI: 10.1186/s13244-022-01350-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 12/05/2022] [Indexed: 01/17/2023] Open
Abstract
OBJECTIVES This study aimed to evaluate the feasibility of reduced full-of-view synthetic high-b value diffusion-weighted images (rFOV-syDWIs) in the clinical application of cervical cancer based on image quality and diagnostic efficacy. METHODS We retrospectively evaluated the data of 35 patients with cervical cancer and 35 healthy volunteers from May to November 2021. All patients and volunteers underwent rFOV-DWI scans, including a 13b-protocol: b = 0, 25, 50, 75, 100, 150, 200, 400, 600, 800, 1000, 1200, and 1500 s/mm2 and a 5b-protocol: b = 0, 100, 400, 800,1500 s/mm2. rFOV-syDWIs with b values of 1200 (rFOV-syDWIb=1200) and 1500 (rFOV-syDWIb=1500) were generated from two different multiple-b-value image datasets using a mono-exponential fitting algorithm. According to homoscedasticity and normality assessed by the Levene's test and Shapiro-Wilk test, the inter-modality differences of quantitative measurements were, respectively, examined by Wilcoxon signed-rank test or paired t test and the inter-group differences of ADC values were examined by independent t test or Mann-Whitney U test. RESULTS A higher inter-reader agreement between SNRs and CNRs was found in 13b-protocol and 5b-protocol rFOV-syDWIb=1200/1500 compared to 13b-protocol rFOV-sDWIb=1200/1500 (p < 0.05). AUC of 5b-protocol syADCmean,b=1200/1500 and syADCminimum,b=1200/1500 was equal or higher than that of 13b-protocol sADCmean,b=1200/1500 and sADCminimum,b=1200/1500. CONCLUSIONS rFOV-syDWIs provide better lesion clarity and higher image quality than rFOV-sDWIs. 5b-protocol rFOV-syDWIs shorten scan time, and synthetic ADCs offer reliable diagnosis value as scanned 13b-protocol DWIs.
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Affiliation(s)
- Qian Tang
- grid.443573.20000 0004 1799 2448Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China ,grid.443573.20000 0004 1799 2448Biomedical Engineering College, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China
| | - Qiqi Zhou
- grid.443573.20000 0004 1799 2448Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China
| | - Wen Chen
- grid.443573.20000 0004 1799 2448Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China
| | - Ling Sang
- grid.443573.20000 0004 1799 2448Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China
| | - Yu Xing
- grid.443573.20000 0004 1799 2448Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China
| | - Chao Liu
- grid.443573.20000 0004 1799 2448Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China
| | - Kejun Wang
- grid.443573.20000 0004 1799 2448Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China
| | | | - Lin Xu
- grid.443573.20000 0004 1799 2448Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei China
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Bilgin EY, Ünal Ö, Göç MF, Bahsi T. Differences in apparent diffusion coefficient histogram analysis according to EGFR mutation status in brain metastasis due to lung adenocarcinoma. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2023; 31:1035-1045. [PMID: 37424492 DOI: 10.3233/xst-230084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
BACKGROUND The etiology, clinicopathological features, and prognosis of cancer in cases with EGFR mutations are different from those without mutations.OBJECTİVE:This study aims to evaluate the differences in ADC histogram analysis in brain metastases with EGFR mutation status in lung adenocarcinoma cases and the relationship between ADC histogram analysis differences and overall survival. METHODS In this retrospective case-control study, 30 patients (8 EGFR+/22 EGFR-) and 51 brain metastases (15 EGFR+/36 EGFR-) were included. ROI markings are first performed from each section, including metastasis in ADC mapping using FIREVOXEL software. Next, ADC histogram parameters are calculated. Overall survival analysis after brain metastasis (OSBM) is defined as the time from initial brain metastasis diagnosis to the time of death or last follow-up. Patient-based (by evaluating the largest lesion) and lesion-based (by evaluating all measurable lesions) statistical analyses are then performed. RESULTS In the lesion-based analysis, skewness values are lower in EGFR+ patients, which is statistically significant (p = 0.012). The two groups have no significant difference regarding other ADC histogram analysis parameters, mortality, and overall survival (p > 0.05). In the ROC analysis, the most appropriate skewness cut-off value is determined as 0.321 to distinguish the EGFR mutation difference, and this value is statistically significant (sensitivity: 66.7%, specificity: 80.6%, AUC: 0.730) (p = 0.006).CONCLUSİON:The findings of this study provide valuable insights into the differences in ADC histogram analysis according to EGFR mutation status in brain metastases due to lung adenocarcinoma. The identified parameters, especially skewness, are potentially non-invasive biomarkers for predicting mutation status. Incorporating these biomarkers into routine clinical practice may aid treatment decision-making and prognostic assessment for patients. Further validation studies and prospective investigations are warranted to confirm the clinical utility of these findings and establish their potential for personalized therapeutic strategies and patient outcomes.
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Affiliation(s)
- Ezel Yaltırık Bilgin
- Department of Radiology, Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital, Ankara, Turkey
| | - Özkan Ünal
- Department of Radiology, Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital, Ankara, Turkey
| | - Muhammed Fatih Göç
- Department of Radiology, Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital, Ankara, Turkey
| | - Taha Bahsi
- Department of Medical Genetics, Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital, Ankara, Turkey
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Fang J, Zhang Y, Li R, Liang L, Yu J, Hu Z, Zhou L, Liu R. The utility of diffusion-weighted imaging for differentiation of phyllodes tumor from fibroadenoma and breast cancer. Front Oncol 2023; 13:938189. [PMID: 36937381 PMCID: PMC10018141 DOI: 10.3389/fonc.2023.938189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Objective To evaluate the utility of apparent diffusion coefficient (ADC) values for differentiating breast tumors. Methods The medical records of 17 patients with phyllodes tumor [PT; circular regions of interest (ROI-cs) n = 171], 74 patients with fibroadenomas (FAs; ROI-cs, n = 94), and 57 patients with breast cancers (BCs; ROI-cs, n = 104) confirmed by surgical pathology were retrospectively reviewed. Results There were significant differences between PTs, FAs, and BCs in ADCmean, ADCmax, and ADCmin values. The cutoff ADCmean for differentiating PTs from FAs was 1.435 × 10-3 mm2/s, PTs from BCs was 1.100 × 10-3 mm2/s, and FAs from BCs was 0.925 × 10-3 mm2/s. There were significant differences between benign PTs, borderline PTs, and malignant PTs in ADCmean, ADCmax, and ADCmin values. The cutoff ADCmean for differentiating benign PTs from borderline PTs was 1.215 × 10-3 mm2/s, and borderline PTs from malignant PTs was 1.665 × 10-3 mm2/s. Conclusion DWI provides quantitative information that can help distinguish breast tumors.
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Affiliation(s)
- Jinzhi Fang
- Department of Radiology, Affiliated Longhua People’s Hospital, Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Yuzhong Zhang
- Department of Radiology, Affiliated Longhua People’s Hospital, Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Ruifeng Li
- Department of Radiology, Affiliated Longhua People’s Hospital, Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Lanlan Liang
- Clinical Medical College of Dali University, Dali, China
- Department of Radiology, Affiliated Hospital of Yunnan University, Kunming, China
| | - Juan Yu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen, China
| | - Ziqi Hu
- Department of Radiology, Affiliated Longhua People’s Hospital, Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Lingling Zhou
- Department of Radiology, Affiliated Longhua People’s Hospital, Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Renwei Liu
- Department of Radiology, Affiliated Longhua People’s Hospital, Southern Medical University (Longhua People’s Hospital), Shenzhen, China
- *Correspondence: Renwei Liu,
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Gonçalves FG, Tierradentro-Garcia LO, Kim JDU, Zandifar A, Ghosh A, Viaene AN, Khrichenko D, Andronikou S, Vossough A. The role of apparent diffusion coefficient histogram metrics for differentiating pediatric medulloblastoma histological variants and molecular groups. Pediatr Radiol 2022; 52:2595-2609. [PMID: 35798974 DOI: 10.1007/s00247-022-05411-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 04/05/2022] [Accepted: 05/31/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Medulloblastoma, a high-grade embryonal tumor, is the most common primary brain malignancy in the pediatric population. Molecular medulloblastoma groups have documented clinically and biologically relevant characteristics. Several authors have attempted to differentiate medulloblastoma molecular groups and histology variants using diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps. However, literature on the use of ADC histogram analysis in medulloblastomas is still scarce. OBJECTIVE This study presents data from a sizable group of pediatric patients with medulloblastoma from a single institution to determine the performance of ADC histogram metrics for differentiating medulloblastoma variants and groups based on both histological and molecular features. MATERIALS AND METHODS In this retrospective study, we evaluated the distribution of absolute and normalized ADC values of medulloblastomas. Tumors were manually segmented and diffusivity metrics calculated on a pixel-by-pixel basis. We calculated a variety of first-order histogram metrics from the ADC maps, including entropy, minimum, 10th percentile, 90th percentile, maximum, mean, median, skewness and kurtosis, to differentiate molecular and histological variants. ADC values of the tumors were also normalized to the bilateral cerebellar cortex and thalami. We used the Kruskal-Wallis and Mann-Whitney U tests to evaluate differences between the groups. We carried out receiver operating characteristic (ROC) curve analysis to evaluate the areas under the curves and to determine the cut-off values for differentiating tumor groups. RESULTS We found 65 children with confirmed histopathological diagnosis of medulloblastoma. Mean age was 8.3 ± 5.8 years, and 60% (n = 39) were male. One child was excluded because histopathological variant could not be determined. In terms of medulloblastoma variants, tumors were classified as classic (n = 47), desmoplastic/nodular (n = 9), large/cell anaplastic (n = 6) or as having extensive nodularity (n = 2). Seven other children were excluded from the study because of incomplete imaging or equivocal molecular diagnosis. Regarding medulloblastoma molecular groups, there were: wingless (WNT) group (n = 7), sonic hedgehog (SHH) group (n = 14) and non-WNT/non-SHH (n = 36). Our results showed significant differences among the molecular groups in terms of the median (P = 0.002), mean (P = 0.003) and 90th percentile (P = 0.002) ADC histogram metrics. No significant differences among the various medulloblastoma histological variants were found. CONCLUSION ADC histogram analysis can be implemented as a complementary tool in the preoperative evaluation of medulloblastoma in children. This technique can provide valuable information for differentiating among medulloblastoma molecular groups. ADC histogram metrics can help predict medulloblastoma molecular classification preoperatively.
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Affiliation(s)
- Fabrício Guimarães Gonçalves
- Department of Radiology, Division of Neuroradiology, The Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA.
| | - Luis Octavio Tierradentro-Garcia
- Department of Radiology, Division of Neuroradiology, The Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | - Jorge Du Ub Kim
- Department of Radiology, Division of Neuroradiology, The Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | - Alireza Zandifar
- Department of Radiology, Division of Neuroradiology, The Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | - Adarsh Ghosh
- Department of Radiology, Division of Neuroradiology, The Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | - Angela N Viaene
- Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Dmitry Khrichenko
- Department of Radiology, Division of Neuroradiology, The Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | - Savvas Andronikou
- Department of Radiology, Division of Neuroradiology, The Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA.,Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Arastoo Vossough
- Department of Radiology, Division of Neuroradiology, The Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA.,Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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Liu R, Li R, Fang J, Deng K, Chen C, Li J, Wu Z, Zeng X. Apparent diffusion coefficient histogram analysis for differentiating solid ovarian tumors. Front Oncol 2022; 12:904323. [PMID: 35978817 PMCID: PMC9376384 DOI: 10.3389/fonc.2022.904323] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 07/06/2022] [Indexed: 12/21/2022] Open
Abstract
Objective To evaluate the utility of apparent diffusion coefficient (ADC) histogram analysis to differentiate between three types of solid ovarian tumors: granulosa cell tumors (GCTs) of the ovary, ovarian fibromas, and high-grade serous ovarian carcinomas (HGSOCs). Methods The medical records of 11 patients with GCTs of the ovary (regions of interest [ROI-cs], 137), 61 patients with ovarian fibromas (ROI-cs, 161), and 14 patients with HGSOCs (ROI-cs, 113) confirmed at surgery and histology who underwent diffusion-weighted imaging were retrospectively reviewed. Histogram parameters of ADC maps (ADCmean, ADCmax, ADCmin) were estimated and compared using the Kruskal-WallisH test and Mann-Whitney U test. The area under the curve of receiver operating characteristic curves was used to assess the diagnostic performance of ADC parameters for solid ovarian tumors. Results There were significant differences in ADCmean, ADCmax and ADCmin values between GCTs of the ovary, ovarian fibromas, and HGSOCs. The cutoff ADCmean value for differentiating a GCT of the ovary from an ovarian fibroma was 0.95×10-3 mm2/s, for differentiating a GCT of the ovary from an HGSOC was 0.69×10-3 mm2/s, and for differentiating an ovarian fibroma from an HGSOC was 1.24×10-3 mm2/s. Conclusion ADCmean derived from ADC histogram analysis provided quantitative information that allowed accurate differentiation of GCTs of the ovary, ovarian fibromas, and HGSOCs before surgery.
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Affiliation(s)
- Renwei Liu
- Department of Radiology, Affiliated Longhua People’s Hospital Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Ruifeng Li
- Department of Radiology, Affiliated Longhua People’s Hospital Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Jinzhi Fang
- Department of Radiology, Affiliated Longhua People’s Hospital Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Kan Deng
- C&TS Clinical Science, Philips Healthcare, Guangzhou, China
| | - Cuimei Chen
- Department of Radiology, Affiliated Longhua People’s Hospital Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Jianhua Li
- Department of Radiology, Affiliated Longhua People’s Hospital Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Zhiqing Wu
- Department of Radiology, Affiliated Longhua People’s Hospital Southern Medical University (Longhua People’s Hospital), Shenzhen, China
| | - Xiaoxu Zeng
- Department of Radiology, Affiliated Longhua People’s Hospital Southern Medical University (Longhua People’s Hospital), Shenzhen, China
- *Correspondence: Xiaoxu Zeng,
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Gihr G, Horvath-Rizea D, Kohlhof-Meinecke P, Ganslandt O, Henkes H, Härtig W, Donitza A, Skalej M, Schob S. Diffusion Weighted Imaging in Gliomas: A Histogram-Based Approach for Tumor Characterization. Cancers (Basel) 2022; 14:cancers14143393. [PMID: 35884457 PMCID: PMC9321540 DOI: 10.3390/cancers14143393] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/07/2022] [Accepted: 07/09/2022] [Indexed: 12/10/2022] Open
Abstract
Simple Summary Glioma represent approximately one-third of all brain tumors. Although they differ clinically, histologically and genetically, they often are not distinguishable by morphological magnetic resonance imaging (MRI) diagnostics. We therefore investigated in this retrospective study whether diffusion weighted imaging (DWI) using a radiomic approach could provide complementary information with respect to tumor differentiation and cell proliferation, as well as the underlying genetic and epigenetic tumor profile. We identified several histogram features that could facilitate presurgical tumor grading and potentially enable one to draw conclusions about tumor characteristics on a cellular and subcellular scale. Abstract (1) Background: Astrocytic gliomas present overlapping appearances in conventional MRI. Supplementary techniques are necessary to improve preoperative diagnostics. Quantitative DWI via the computation of apparent diffusion coefficient (ADC) histograms has proven valuable for tumor characterization and prognosis in this regard. Thus, this study aimed to investigate (I) the potential of ADC histogram analysis (HA) for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and (II) whether those parameters are associated with Ki-67 immunolabelling, the isocitrate-dehydrogenase-1 (IDH1) mutation profile and the methylguanine-DNA-methyl-transferase (MGMT) promoter methylation profile; (2) Methods: The ADC-histograms of 82 gliomas were computed. Statistical analysis was performed to elucidate associations between histogram features and WHO grade, Ki-67 immunolabelling, IDH1 and MGMT profile; (3) Results: Minimum, lower percentiles (10th and 25th), median, modus and entropy of the ADC histogram were significantly lower in HGG. Significant differences between IDH1-mutated and IDH1-wildtype gliomas were revealed for maximum, lower percentiles, modus, standard deviation (SD), entropy and skewness. No differences were found concerning the MGMT status. Significant correlations with Ki-67 immunolabelling were demonstrated for minimum, maximum, lower percentiles, median, modus, SD and skewness; (4) Conclusions: ADC HA facilitates non-invasive prediction of the WHO grade, tumor-proliferation rate and clinically significant mutations in case of astrocytic gliomas.
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Affiliation(s)
- Georg Gihr
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, 70174 Stuttgart, Germany; (D.H.-R.); (H.H.)
- Correspondence: (G.G.); (S.S.); Tel.: +49-711-2785-4454 (G.G.); +49-345-557-2342 (S.S.)
| | - Diana Horvath-Rizea
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, 70174 Stuttgart, Germany; (D.H.-R.); (H.H.)
| | | | - Oliver Ganslandt
- Katharinenhospital Stuttgart, Clinic for Neurosurgery, 70174 Stuttgart, Germany;
| | - Hans Henkes
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, 70174 Stuttgart, Germany; (D.H.-R.); (H.H.)
| | - Wolfgang Härtig
- Paul Flechsig Institute for Brain Research, University of Leipzig, 04103 Leipzig, Germany;
| | - Aneta Donitza
- Department for Neuroradiology, Clinic and Policlinic for Radiology, University Hospital Halle (Saale), 06120 Halle (Saale), Germany; (A.D.); (M.S.)
| | - Martin Skalej
- Department for Neuroradiology, Clinic and Policlinic for Radiology, University Hospital Halle (Saale), 06120 Halle (Saale), Germany; (A.D.); (M.S.)
| | - Stefan Schob
- Department for Neuroradiology, Clinic and Policlinic for Radiology, University Hospital Halle (Saale), 06120 Halle (Saale), Germany; (A.D.); (M.S.)
- Correspondence: (G.G.); (S.S.); Tel.: +49-711-2785-4454 (G.G.); +49-345-557-2342 (S.S.)
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Cai M, Yao F, Ding J, Zheng R, Huang X, Yang Y, Lin F, Hu Z. MRI Radiomic Features: A Potential Biomarker for Progression-Free Survival Prediction of Patients With Locally Advanced Cervical Cancer Undergoing Surgery. Front Oncol 2022; 11:749114. [PMID: 34970482 PMCID: PMC8712932 DOI: 10.3389/fonc.2021.749114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/19/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives To investigate the prognostic role of radiomic features based on pretreatment MRI in predicting progression-free survival (PFS) of locally advanced cervical cancer (LACC). Methods All 181 women with histologically confirmed LACC were randomly divided into the training cohort (n = 126) and the validation cohort (n = 55). For each patient, we extracted radiomic features from whole tumors on sagittal T2WI and axial DWI. The least absolute shrinkage and selection operator (LASSO) algorithm combined with the Cox survival analysis was applied to select features and construct a radiomic score (Rad-score) model. The cutoff value of the Rad-score was used to divide the patients into high- and low-risk groups by the X-tile. Kaplan–Meier analysis and log-rank test were used to assess the prognostic value of the Rad-score. In addition, we totally developed three models, the clinical model, the Rad-score, and the combined nomogram. Results The Rad-score demonstrated good performance in stratifying patients into high- and low-risk groups of progression in the training (HR = 3.279, 95% CI: 2.865–3.693, p < 0.0001) and validation cohorts (HR = 2.247, 95% CI: 1.735–2.759, p < 0.0001). Otherwise, the combined nomogram, integrating the Rad-score and patient’s age, hemoglobin, white blood cell, and lymph vascular space invasion, demonstrated prominent discrimination, yielding an AUC of 0.879 (95% CI, 0.811–0.947) in the training cohort and 0.820 (95% CI, 0.668–0.971) in the validation cohort. The Delong test verified that the combined nomogram showed better performance in estimating PFS than the clinical model and Rad-score in the training cohort (p = 0.038, p = 0.043). Conclusion The radiomics nomogram performed well in individualized PFS estimation for the patients with LACC, which might guide individual treatment decisions.
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Affiliation(s)
- Mengting Cai
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Fei Yao
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jie Ding
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ruru Zheng
- Department of Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaowan Huang
- Department of Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yunjun Yang
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Feng Lin
- Department of Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhangyong Hu
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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11
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Haghighi Borujeini M, Farsizaban M, Yazdi SR, Tolulope Agbele A, Ataei G, Saber K, Hosseini SM, Abedi-Firouzjah R. Grading of meningioma tumors based on analyzing tumor volumetric histograms obtained from conventional MRI and apparent diffusion coefficient images. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [DOI: 10.1186/s43055-021-00545-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Abstract
Background
Our purpose was to evaluate the application of volumetric histogram parameters obtained from conventional MRI and apparent diffusion coefficient (ADC) images for grading the meningioma tumors.
Results
Tumor volumetric histograms of preoperative MRI images from 45 patients with the diagnosis of meningioma at different grades were analyzed to find the histogram parameters. Kruskal-Wallis statistical test was used for comparison between the parameters obtained from different grades. Multi-parametric regression analysis was used to find the model and parameters with high predictive value for the classification of meningioma. Mode; standard deviation on post-contrast T1WI, T2-FLAIR, and ADC images; kurtosis on post-contrast T1WI and T2-FLAIR images; mean and several percentile values on ADC; and post-contrast T1WI images showed significant differences among different tumor grades (P < 0.05). The multi-parametric linear regression showed that the ADC histogram parameters model had a higher predictive value, with cutoff values of 0.212 (sensitivity = 79.6%, specificity = 84.3%) and 0.180 (sensitivity = 70.9%, specificity = 80.8%) for differentiating the grade I from II, and grade II from III, respectively.
Conclusions
The multi-parametric model of volumetric histogram parameters in some of the conventional MRI series (i.e., post-contrast T1WI and T2-FLAIR images) along with the ADC images are appropriate for predicting the meningioma tumors’ grade.
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Kalantar R, Lin G, Winfield JM, Messiou C, Lalondrelle S, Blackledge MD, Koh DM. Automatic Segmentation of Pelvic Cancers Using Deep Learning: State-of-the-Art Approaches and Challenges. Diagnostics (Basel) 2021; 11:1964. [PMID: 34829310 PMCID: PMC8625809 DOI: 10.3390/diagnostics11111964] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 10/14/2021] [Accepted: 10/19/2021] [Indexed: 12/18/2022] Open
Abstract
The recent rise of deep learning (DL) and its promising capabilities in capturing non-explicit detail from large datasets have attracted substantial research attention in the field of medical image processing. DL provides grounds for technological development of computer-aided diagnosis and segmentation in radiology and radiation oncology. Amongst the anatomical locations where recent auto-segmentation algorithms have been employed, the pelvis remains one of the most challenging due to large intra- and inter-patient soft-tissue variabilities. This review provides a comprehensive, non-systematic and clinically-oriented overview of 74 DL-based segmentation studies, published between January 2016 and December 2020, for bladder, prostate, cervical and rectal cancers on computed tomography (CT) and magnetic resonance imaging (MRI), highlighting the key findings, challenges and limitations.
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Affiliation(s)
- Reza Kalantar
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK; (R.K.); (J.M.W.); (C.M.); (S.L.); (D.-M.K.)
| | - Gigin Lin
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou and Chang Gung University, 5 Fuhsing St., Guishan, Taoyuan 333, Taiwan;
| | - Jessica M. Winfield
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK; (R.K.); (J.M.W.); (C.M.); (S.L.); (D.-M.K.)
- Department of Radiology, The Royal Marsden Hospital, London SW3 6JJ, UK
| | - Christina Messiou
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK; (R.K.); (J.M.W.); (C.M.); (S.L.); (D.-M.K.)
- Department of Radiology, The Royal Marsden Hospital, London SW3 6JJ, UK
| | - Susan Lalondrelle
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK; (R.K.); (J.M.W.); (C.M.); (S.L.); (D.-M.K.)
- Department of Radiology, The Royal Marsden Hospital, London SW3 6JJ, UK
| | - Matthew D. Blackledge
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK; (R.K.); (J.M.W.); (C.M.); (S.L.); (D.-M.K.)
| | - Dow-Mu Koh
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK; (R.K.); (J.M.W.); (C.M.); (S.L.); (D.-M.K.)
- Department of Radiology, The Royal Marsden Hospital, London SW3 6JJ, UK
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Yu B, Huang C, Liu S, Li T, Guan Y, Zheng X, Ding J. Application of first-order feature analysis of DWI-ADC in rare malignant mesenchymal tumours of the maxillofacial region. BMC Oral Health 2021; 21:463. [PMID: 34556116 PMCID: PMC8459531 DOI: 10.1186/s12903-021-01835-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 09/16/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To research the first-order features of apparent diffusion coefficient (ADC) values on diffusion-weighted magnetic resonance imaging (DWI) in maxillofacial malignant mesenchymal tumours. METHODS The clinical data of 12 patients with rare malignant mesenchymal tumours of the maxillofacial region (6 cases of sarcoma and 6 cases of lymphoma) treated in the hospital from May 2018 to June 2020 and were confirmed by postoperative pathology were retrospectively analyzed. The patients were all examined by 1.5T magnetic resonance imaging. PyRadiomics were used to extract radiomics imaging first-order features. Group differences in quantitative variables were examined using independent-samples t-tests. RESULTS The voxels number of ADCmean and ADCmedian of sarcoma tissues were 44.9124 and 44.2064, respectively, significantly higher than those in lymphoma tissues (ADCmean (- 68.8379) and ADCmedian (- 74.0045)), the difference considered statistically significant, so do the ADCkurt and ADCskew. CONCLUSIONS The statistical difference of ADCmean and ADCmedian is significant, it is consistent with the outcome of the manual measurement of the ADC mean value of the most significant cross-section of twelve cases of lymphoma. Development of tumour volume based on the ADC parameter map of DWI demonstrates that the first-order ADC radiomics features analysis can provide new imaging markers for the differentiation of maxillofacial sarcoma and lymphoma. Therefore, first-order ADC features of ADCkurt combined ADCskew may improve the diagnosis level.
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Affiliation(s)
- Baoting Yu
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Chencui Huang
- Department of Research Collaboration, R&D Center, Beijing Deepwise and League of PHD Technology Co. Ltd., Beijing, 100080, China
| | - Shuo Liu
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Tong Li
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Yuyao Guan
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Xuewei Zheng
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Jun Ding
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China.
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14
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deSouza NM. Imaging to assist fertility-sparing surgery. Best Pract Res Clin Obstet Gynaecol 2021; 75:23-36. [PMID: 33722497 DOI: 10.1016/j.bpobgyn.2021.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Accepted: 01/31/2021] [Indexed: 11/23/2022]
Abstract
Cytological screening and human papilloma virus testing has led to diagnosis of cervical cancer in young women at an earlier stage. Defining the full extent of the disease within the cervix with imaging aids the decision on feasibility of fertility-sparing surgical options, such as extended cone biopsy or trachelectomy. High spatial resolution images with maximal contrast between tumour and surrounding background are achieved with T2-weighted and diffusion-weighted (DW) magnetic resonance imaging (MRI) obtained using an endovaginal receiver coil. Tumour size and volume demonstrated in this way correlates between observers and with histology and differences between MRI and histology estimates of normal endocervical canal length are not significant. For planning fertility-sparing surgery, this imaging technique facilitates the best oncological outcome while minimising subsequent obstetric risks. Parametrial invasion may be assessed on large field of view T2-weighted MRI. The fat content of the parametrium limits the utility of DW imaging in this context, because fat typically shows diffusion restriction. The use of contrast-enhanced MRI for assessing the parametrium does not provide additional benefits to the T2-weighted images and the need for an extrinsic contrast agent merely adds additional complexity and cost. For nodal assessment, 18fluorodeoxyglucose positron emission tomography-computerised tomography (18FDG PET-CT) remains the gold standard.
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Affiliation(s)
- N M deSouza
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, 15 Cotswold Road, SM2 5NG, UK.
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15
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Gihr G, Horvath-Rizea D, Hekeler E, Ganslandt O, Henkes H, Hoffmann KT, Scherlach C, Schob S. Diffusion weighted imaging in high-grade gliomas: A histogram-based analysis of apparent diffusion coefficient profile. PLoS One 2021; 16:e0249878. [PMID: 33857203 PMCID: PMC8049265 DOI: 10.1371/journal.pone.0249878] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 03/26/2021] [Indexed: 12/15/2022] Open
Abstract
Purpose Glioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status. Methods Pre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics. Results Grade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG. Conclusions ADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis.
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Affiliation(s)
- Georg Gihr
- Clinic for Neuroradiology, Katharinenhospital Stuttgart, Stuttgart, Germany
- * E-mail:
| | | | - Elena Hekeler
- Department for Pathology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Oliver Ganslandt
- Clinic for Neurosurgery, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Hans Henkes
- Clinic for Neuroradiology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Karl-Titus Hoffmann
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Cordula Scherlach
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Stefan Schob
- Department for Radiology, University Hospital Halle (Saale), Halle (Saale), Germany
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Usuda K, Ishikawa M, Iwai S, Iijima Y, Motono N, Matoba M, Doai M, Hirata K, Uramoto H. Combination Assessment of Diffusion-Weighted Imaging and T2-Weighted Imaging Is Acceptable for the Differential Diagnosis of Lung Cancer from Benign Pulmonary Nodules and Masses. Cancers (Basel) 2021; 13:cancers13071551. [PMID: 33800560 PMCID: PMC8037373 DOI: 10.3390/cancers13071551] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/23/2021] [Accepted: 03/25/2021] [Indexed: 12/13/2022] Open
Abstract
Simple Summary The purpose of this study is to determine whether the combination assessment of DWI and T2WI improves the diagnostic ability for differential diagnosis of lung cancer from benign pulmonary nodules and masses (BPNMs). As using the OCV (1.470 × 10−3 mm2/s) for ADC, the sensitivity was 83.9% (220/262), the specificity 63.4% (33/52), and the accuracy 80.6% (253/314). As using the OCV (2.45) for T2 CR, the sensitivity was 89.7% (235/262), the specificity 61.5% (32/52), and the accuracy 85.0% (267/314). In 212 PNMs which were judged to be malignant by both DWI and T2WI, 203 PNMs (95.8%) were lung cancers. In 33 PNMs which were judged to be benign by both DWI and T2WI, 23 PNMs (69.7%) were BPNMs. The combined assessment of DWI and T2WI could judge PNMs more precisely and would be acceptable for differential diagnosis of PNMs. Abstract The purpose of this study is to determine whether the combination assessment of DWI and T2-weighted imaging (T2WI) improves the diagnostic ability for differential diagnosis of lung cancer from benign pulmonary nodules and masses (BPNMs). The optimal cut-off value (OCV) for differential diagnosis was set at 1.470 × 10−3 mm2/s for apparent diffusion coefficient (ADC), and at 2.45 for T2 contrast ratio (T2 CR). The ADC (1.24 ± 0.29 × 10−3 mm2/s) of lung cancer was significantly lower than that (1.69 ± 0.58 × 10−3 mm2/s) of BPNM. The T2 CR (2.01 ± 0.52) of lung cancer was significantly lower than that (2.74 ± 1.02) of BPNM. As using the OCV for ADC, the sensitivity was 83.9% (220/262), the specificity 63.4% (33/52), and the accuracy 80.6% (253/314). As using the OCV for T2 CR, the sensitivity was 89.7% (235/262), the specificity 61.5% (32/52), and the accuracy 85.0% (267/314). In 212 PNMs which were judged to be malignant by both DWI and T2WI, 203 PNMs (95.8%) were lung cancers. In 33 PNMs which were judged to be benign by both DWI and T2WI, 23 PNMs (69.7%) were BPNMs. The combined assessment of DWI and T2WI could judge PNMs more precisely and would be acceptable for differential diagnosis of PNMs.
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Affiliation(s)
- Katsuo Usuda
- Department of Thoracic Surgery, Kanazawa Medical University, Ishikawa 920-0293, Japan; (M.I.); (S.I.); (Y.I.); (N.M.); (H.U.)
- Correspondence: ; Tel.: +81-76-286-2211; Fax: +81-76-286-1207
| | - Masahito Ishikawa
- Department of Thoracic Surgery, Kanazawa Medical University, Ishikawa 920-0293, Japan; (M.I.); (S.I.); (Y.I.); (N.M.); (H.U.)
| | - Shun Iwai
- Department of Thoracic Surgery, Kanazawa Medical University, Ishikawa 920-0293, Japan; (M.I.); (S.I.); (Y.I.); (N.M.); (H.U.)
| | - Yoshihito Iijima
- Department of Thoracic Surgery, Kanazawa Medical University, Ishikawa 920-0293, Japan; (M.I.); (S.I.); (Y.I.); (N.M.); (H.U.)
| | - Nozomu Motono
- Department of Thoracic Surgery, Kanazawa Medical University, Ishikawa 920-0293, Japan; (M.I.); (S.I.); (Y.I.); (N.M.); (H.U.)
| | - Munetaka Matoba
- Department of Radiology, Kanazawa Medical University, Ishikawa 920-0293, Japan; (M.M.); (M.D.)
| | - Mariko Doai
- Department of Radiology, Kanazawa Medical University, Ishikawa 920-0293, Japan; (M.M.); (M.D.)
| | - Keiya Hirata
- MRI Center, Kanazawa Medical University Hospital, Ishikawa 920-0293, Japan;
| | - Hidetaka Uramoto
- Department of Thoracic Surgery, Kanazawa Medical University, Ishikawa 920-0293, Japan; (M.I.); (S.I.); (Y.I.); (N.M.); (H.U.)
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Meyer HJ, Höhn AK, Woidacki K, Andric M, Powerski M, Pech M, Surov A. Associations between IVIM histogram parameters and histopathology in rectal cancer. Magn Reson Imaging 2020; 77:21-27. [PMID: 33316358 DOI: 10.1016/j.mri.2020.12.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 11/18/2020] [Accepted: 12/08/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE Histogram analysis can better reflect tumor heterogeneity than conventional imaging analysis. The present study analyzed possible correlations between histogram analysis parameters derived from Intravoxel-incoherent imaging (IVIM) and histopathological features in rectal cancer (RC). METHODS Seventeen patients with histopathologically proven rectal adenocarcinomas were retrospectively acquired. In all cases, pelvic MRI was performed. Diffusion weighted imaging was obtained using a multi-slice single-shot echo-planar imaging sequence with b values of 0, 50, 200, 500 and 1000 s/mm2. Simplified IVIM analysis was performed using the IntelliSpace portal, version 10 and the following images were generated: f (perfusion fraction) map, D (true diffusion coefficient) map, and ADC map utilizing all b-values. Histogram based analysis of signal intensities was performed for every IVIM map using an in-house matlab tool. Histopathology was investigated using Ki 67 specimens with calculation of Ki 67-index and cellularity. CD31 stained specimens were used for calculation of microvessel density (MVD). RESULTS There were statistically significant correlations between Ki 67 index and mode derived from ADC as well as entropy from f, r=-0.50, p=.04 and r=-0.55, p=.02, respectively. MVD correlated well with parameters derived from f. CONCLUSION IVIM histogram analysis parameters can reflect histopathology in RC. ADC and D values are associated with proliferation potential. Perfusion fraction f is associated with MVD.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.
| | | | - Katja Woidacki
- Section Experimental Radiology, Department of Radiology and Nuclear Medicine, Otto-von-Guericke-University of Magdeburg, Magdeburg, Germany
| | - Mihailo Andric
- Department of Surgery, Otto-von-Guericke-University of Magdeburg, Magdeburg, Germany
| | - Maciej Powerski
- Department of Radiology and Nuclear Medicine, Otto-von-Guericke-University of Magdeburg, Magdeburg, Germany
| | - Maciej Pech
- Department of Radiology and Nuclear Medicine, Otto-von-Guericke-University of Magdeburg, Magdeburg, Germany
| | - Alexey Surov
- Department of Radiology and Nuclear Medicine, Otto-von-Guericke-University of Magdeburg, Magdeburg, Germany
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The Role of Multiparametric Magnetic Resonance Imaging in the Study of Primary Tumor and Pelvic Lymph Node Metastasis in Stage IB1-IIA1 Cervical Cancer. J Comput Assist Tomogr 2020; 44:750-758. [PMID: 32842062 DOI: 10.1097/rct.0000000000001084] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of this study was to investigate the value of multiparametric magnetic resonance imaging (MRI) in demonstrating the metastatic potential of primary tumor and differentiating metastatic lymph nodes (MLNs) from nonmetastatic lymph nodes (non-MLNs) in stage IB1-IIA1 cervical cancer. METHODS Fifty-seven stage IB1-IIA1 subjects were included. The apparent diffusion coefficient (ADC) values and dynamic contrast-enhanced MRI (DCE-MRI) parameters of primary tumors and lymph nodes and the conventional imaging features of the lymph nodes were measured and analyzed. Mann-Whitney test and χ test were used to analyze statistically significant parameters, logistic regression was used for multivariate analysis, and receiver operating characteristic analysis was used to compare the diagnostic performance of the MLNs. RESULTS Nineteen subjects had lymph node metastasis. A total of 94 lymph nodes were evaluated, including 30 MLNs and 64 non-MLNs. There were no significant difference in ADC and DCE-MRI parameters between metastatic and nonmetastatic primary tumors. The heterogeneous signal was more commonly seen in MLNs than in non-MLNs (P = 0.001). The values of ADCmean, ADCmin, and ADCmax of MLNs were lower than those of non-MLNs (P < 0.001). The values of short-axis diameter, K, Kep, and Ve of MLNs were higher than those of non-MLNs (P < 0.05). Compared with individual MRI parameters, the combined evaluation of short-axis diameter, ADCmean, and K showed the highest area under the curve of 0.930. CONCLUSIONS Diffusion-weighted imaging and DCE-MRI could not demonstrate the metastatic potential of primary tumor in stage IB1-IIA1 cervical cancer. Compared with individual MRI parameters, the combination of multiparametric MRI could improve the diagnostic performance of lymph node metastasis.
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Bozdağ M, Er A, Çinkooğlu A. Histogram Analysis of ADC Maps for Differentiating Brain Metastases From Different Histological Types of Lung Cancers. Can Assoc Radiol J 2020; 72:271-278. [PMID: 32602365 DOI: 10.1177/0846537120933837] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
PURPOSE Our study aimed to investigate the role of histogram analysis derived from apparent diffusion coefficient (ADC) maps in brain metastases (BMs) from lung cancer for differentiating histological subtype. METHODS A total of 61 BMs (45 non-small cell lung cancer [NSCLC] comprising 32 adenocarcinoma [AC], 13 squamous cell carcinoma [SCC], and 16 small-cell lung cancer [SCLC]) in 50 patients with histopathologically confirmed lung cancer were retrospectively included in this study. Pretreatment cranial diffusion-weighted imaging was performed, and the corresponding ADC maps were generated. Regions of interest were drawn on solid components of the BM on all slices of the ADC maps to obtain parameters, including ADCmax, ADCmean, ADCmin, ADCmedian, ADCrange, skewness, kurtosis, entropy, ADC10, ADC25, ADC75, and ADC90. Apparent diffusion coefficient histogram parameters were compared among histological type groups. Kruskal-Wallis, Mann-Whitney U, chi-square tests, and receiver-operating characteristic (ROC) curve were used for statistical assessment. RESULTS ADCmin, ADC10, and ADC25 were found to be significantly different among AC, SCC, and SCLC groups; these parameters were higher for AC group, moderate for SCC group, and significantly lower for SCLC group. Skewness and kurtosis were not significantly different among all groups. The ROC analysis for differentiating BMs of NSCLC from SCLC showed that ADC25 achieved the highest area under the curve at 0.922 with 93.02% sensitivity and 81.25% specificity. CONCLUSION Apparent diffusion coefficient histogram analysis of BMs from lung cancer has significant prognostic value in differentiating histological subtypes of lung cancer.
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Affiliation(s)
- Mustafa Bozdağ
- Department of Radiology, 64205Tepecik Training and Research Hospital, Konak, Izmir, Turkey
| | - Ali Er
- Department of Radiology, 64205Tepecik Training and Research Hospital, Konak, Izmir, Turkey
| | - Akın Çinkooğlu
- Department of Radiology, 60521Ege University Faculty of Medicine, Bornova, Izmir, Turkey
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Li L, Chen W, Yan Z, Feng J, Hu S, Liu B, Liu X. Comparative Analysis of Amide Proton Transfer MRI and Diffusion-Weighted Imaging in Assessing p53 and Ki-67 Expression of Rectal Adenocarcinoma. J Magn Reson Imaging 2020; 52:1487-1496. [PMID: 32524685 DOI: 10.1002/jmri.27212] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 05/12/2020] [Accepted: 05/14/2020] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The evaluation of prognostic factors in rectal carcinoma patients has important clinical significance. P53 status and the Ki-67 index have served as prognostic factors in rectal carcinoma. Amide proton transfer (APT) imaging has shown great potential in tumor diagnosis. However, few studies reported the value of APT imaging in evaluating p53 and Ki-67 status of rectal carcinoma. PURPOSE To investigate the feasibility of amide proton transfer MRI in assessing p53 and Ki-67 expression of rectal adenocarcinoma, and compare it with conventional diffusion-weighted imaging (DWI). STUDY TYPE Retrospective. POPULATION Forty-three patients with rectal adenocarcinoma (age: 34-85 years). FIELD STRENGTH/SEQUENCE 3T/APT imaging using a 3D turbo spin echo (TSE)-Dixon pulse sequence with chemical shift-selective fat suppression, 2D DWI, and 2D T2 -weighted TSE. ASSESSMENT Mean tumor APT signal intensity (SImean ) and apparent diffusion coefficient (ADCmean ) were measured. Traditional tumor pathological analysis included WHO grades, pT (pathologic tumor) stages, and pN (pathologic node) stages. Expression levels of p53 and Ki-67 were determined by immunohistochemical assay. STATISTICAL TESTS One-way analysis of variance (ANOVA); Student's t-test; Spearman's correlation coefficient; receiver operating characteristic (ROC) curve analysis. RESULTS High-grade tumors, more advanced stage tumors, and tumors with lymph node involvement had higher APT SImean values: high grade (n = 15) vs. low-grade (n = 28), P < 0.001; pT2 (n = 10) vs. pT3 (n = 20) vs. pT4 (N = 13), P = 0.021; pN0 (n = 24) vs. pN1-2 (n = 19), P = 0.019. ADCmean differences were found in tumors with different pT stage: pT2 (n = 10) vs. pT3 (n = 20) vs. pT4 (N = 13), P = 0.013, but not in tumors with different histologic grade: high grade (n = 15) vs. low-grade (n = 28), P = 0.3536; or pN stage: pN0 (n = 24) vs. pN1-2 (n = 19), P = 0.624. Tumor with p53 positive status had higher APT SImean than tumor with negative p53 status (2.363 ± 0.457 vs. 2.0150 ± 0.3552, P = 0.014). There was no difference in ADCmean with p53 status (1.058 ± 0.1163 10-3 mm2 /s vs. 1.055 ± 0.128 10-3 mm2 /s, P = 0.935). APT SImean and ADCmean were significantly different in tumors with low and high Ki-67 status (1.7882 ± 0.11386 vs. 2.3975 ± 0.41586, P < 0.001; 1.1741 ± 0.093 10-3 mm2 /s vs. 1.0157 ± 0.10459 10-3 mm2 /s, P < 0.001, respectively). APT SImean exhibited a positive correlation with p53 labeling index and Ki-67 labeling index (r = 0.3741, P = 0.0135; r = 0.7048; P < 0.001, respectively). ADCmean showed no correlation with p53 labeling index, but a negative correlation with Ki-67 labeling index (r = -0.5543, P < 0.0001). ROC curves demonstrated that APT SImean had significantly higher diagnostic ability for differentiation of high Ki-67 expression of rectal adenocarcinoma than ADCmean (81.2% vs. 78.12%, 90.91% vs. 63.64; P < 0.001 vs. P = 0.017), while no difference was found in predicting p53 status (92.86% vs. 71.4%, 53.33% vs. 66.7%; P < 0.001 vs. P = 0.0471). DATA CONCLUSION APT SImean was related to p53 and Ki-67 expression levels in rectal adenocarcinoma. APT imaging may serve as a noninvasive biomarker for assessing genetic prognostic factors of rectal adenocarcinoma. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Ling Li
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Weicui Chen
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Zhaoxian Yan
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Jieping Feng
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Shaowei Hu
- Department of Pathology, The Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Bo Liu
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Xian Liu
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
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Wang F, Wang Y, Zhou Y, Liu C, Liang D, Xie L, Yao Z, Liu J. Apparent Diffusion Coefficient Histogram Analysis for Assessing Tumor Staging and Detection of Lymph Node Metastasis in Epithelial Ovarian Cancer: Correlation with p53 and Ki-67 Expression. Mol Imaging Biol 2020; 21:731-739. [PMID: 30456593 DOI: 10.1007/s11307-018-1295-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
PURPOSE To investigate the potential of apparent diffusion coefficient (ADC) histogram parameters in epithelial ovarian cancer (EOC) for distinguishing different tumor stages and determining lymph node status and correlations between ADC values and p53 and Ki-67 expression. PROCEDURES Forty-nine EOC patients underwent preoperative magnetic resonance imaging. Staging and lymph node status were determined postoperatively. ADC values were measured using histogram analysis and compared between groups. Relationships between ADCs and Ki-67 and p53 expression were explored. RESULTS DC parameters differed significantly between stage I vs II, I vs III, and I vs IV. The parameters were significantly lower in the lymph node-positive group than in the lymph node-negative group, were significantly negatively correlated with Ki-67 labeling index, and were all significantly lower in the mutation-type p53 group than in the wild-type p53 group. CONCLUSIONS ADC histogram analysis can help discriminate stage I from advanced-stage EOC and predict lymph node metastasis. ADC parameters were correlated with Ki-67 labeling index; the parameters may help indicate p53 expression.
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Affiliation(s)
- Feng Wang
- Department of Radiology, Peking University Third Hospital, 49 North Garden Street, Haidian District, Beijing, 100191, China
| | - Yuxiang Wang
- Department of Pathology, School of Basic Medical Science, Peking University Third Hospital, Peking University Health Science Center, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Yan Zhou
- Department of Radiology, Peking University Third Hospital, 49 North Garden Street, Haidian District, Beijing, 100191, China
| | - Congrong Liu
- Department of Pathology, School of Basic Medical Science, Peking University Third Hospital, Peking University Health Science Center, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Dong Liang
- Siemens Ltd., China, 7 Wangjing Zhonghuan Nanlu, Chaoyang District, Beijing, 100102, China
| | - Lizhi Xie
- GE Healthcare China, 1 Yongchang North Road, Beijing, 100176, China
| | - Zhihang Yao
- Department of Radiology, Peking University Third Hospital, 49 North Garden Street, Haidian District, Beijing, 100191, China
| | - Jianyu Liu
- Department of Radiology, Peking University Third Hospital, 49 North Garden Street, Haidian District, Beijing, 100191, China.
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Correlation analysis of apparent diffusion coefficient value and P53 and Ki-67 expression in esophageal squamous cell carcinoma. Magn Reson Imaging 2020; 68:183-189. [DOI: 10.1016/j.mri.2020.01.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 01/21/2020] [Accepted: 01/22/2020] [Indexed: 12/20/2022]
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Perucho JAU, Chiu KWH, Wong EMF, Tse KY, Chu MMY, Chan LWC, Pang H, Khong PL, Lee EYP. Diffusion-weighted magnetic resonance imaging of primary cervical cancer in the detection of sub-centimetre metastatic lymph nodes. Cancer Imaging 2020; 20:27. [PMID: 32252829 PMCID: PMC7137185 DOI: 10.1186/s40644-020-00303-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 03/20/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Magnetic resonance imaging (MRI) has limited accuracy in detecting pelvic lymph node (PLN) metastasis. This study aimed to examine the use of intravoxel incoherent motion (IVIM) in classifying pelvic lymph node (PLN) involvement in cervical cancer patients. METHODS Fifty cervical cancer patients with pre-treatment magnetic resonance imaging (MRI) were examined for PLN involvement by one subspecialist and one non-subspecialist radiologist. PLN status was confirmed by positron emission tomography or histology. The tumours were then segmented by both radiologists. Kruskal-Wallis tests were used to test for differences between diffusion tumour volume (DTV), apparent diffusion coefficient (ADC), pure diffusion coefficient (D), and perfusion fraction (f) in patients with no malignant PLN involvement, those with sub-centimetre and size-significant PLN metastases. These parameters were then considered as classifiers for PLN involvement, and were compared with the accuracies of radiologists. RESULTS Twenty-one patients had PLN involvement of which 10 had sub-centimetre metastatic PLNs. DTV increased (p = 0.013) while ADC (p = 0.015), and f (p = 0.006) decreased as the nodal status progressed from no malignant involvement to sub-centimetre and then size-significant PLN metastases. In determining PLN involvement, a classification model (DTV + f) had similar accuracies (80%) as the non-subspecialist (76%; p = 0.73) and subspecialist (90%; p = 0.31). However, in identifying patients with sub-centimetre PLN metastasis, the model had higher accuracy (90%) than the non-subspecialist (30%; p = 0.01) but had similar accuracy with the subspecialist (90%, p = 1.00). Interobserver variability in tumour delineation did not significantly affect the performance of the classification model. CONCLUSION IVIM is useful in determining PLN involvement but the added value decreases with reader experience.
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Affiliation(s)
- Jose Angelo Udal Perucho
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong
| | - Keith Wan Hang Chiu
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong
| | - Esther Man Fung Wong
- Department of Radiology, Pamela Youde Nethersole Eastern Hospital, 3 Lok Man Road, Chai Wan, Hong Kong
| | - Ka Yu Tse
- Department of Obstetrics and Gynaecology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 6/F, Professorial Block, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong
| | - Mandy Man Yee Chu
- Department of Obstetrics and Gynaecology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 6/F, Professorial Block, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong
| | - Lawrence Wing Chi Chan
- Department of Health Technology and Informatics, Hong Kong Polytechnic University, Room Y934, 9/F, Lee Shau Kee Building, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Herbert Pang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, G/F, Patrick Manson Building (North Wing), 7 Sassoon Road, Pok Fu Lam, Hong Kong
| | - Pek-Lan Khong
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong
| | - Elaine Yuen Phin Lee
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Room 406, Block K, Queen Mary Hospital, Pok Fu Lam Road, Pok Fu Lam, Hong Kong
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He Y, Rong Y, Chen H, Zhang Z, Qiu J, Zheng L, Benedict S, Niu X, Pan N, Liu Y, Yuan Z. Impact of different b-value combinations on radiomics features of apparent diffusion coefficient in cervical cancer. Acta Radiol 2020; 61:568-576. [PMID: 31466457 DOI: 10.1177/0284185119870157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background The impact of variable b-value combinations on apparent diffusion coefficient (ADC)-based radiomics features has not been fully addressed in literature. Purpose To investigate the correlation between radiomics features extracted from ADC maps and various b-value combinations in cervical cancer. Material and Methods Diffusion-weighted images (b-values: 0, 600, 800, and 1000 s/mm2) of 20 patients with cervical cancer were included. Tumors were identified with the largest transversal cross-section and manually segmented by radiologist. For each b-value combination, 92 radiomics features were extracted and coefficient of variance (CV) was used to evaluate the robustness of radiomics features with different b-value combinations. Features with CV > 5% were normalized by the mean feature variation across the group. Results Out of a total of 92 radiomics features, 18 were classified as robust features with CV ≤5%. Among the rest (CV > 5%), 11, 23, and 40 features demonstrated 5%< CV ≤10%, 10%< CV ≤20%, and CV > 20%, respectively. A subset of features in each category (CV > 5%) showed strong correlation with the b-value combination variation, including 44% (7/16) features in gray level co-occurrence matrix, 62% (8/13) features in gray level dependence matrix, 64% (9/14) features in first order, 50% (8/16) features in gray level run length matrix, 57% (8/14) features in gray level size matrix, and 20% (1/5) features in neighborhood gray-tone difference matrix. Conclusions Variations in b-value combinations demonstrated impact on radiomics features extracted from ADC maps for cervical cancer. The radiomics features with CV <5% can be considered as robust features and are recommended to be used in multicenter radiomics studies.
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Affiliation(s)
- Yaoyao He
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
- Medical Engineering and Technology Center, Taishan Medical University, Taian, PR China
| | - Yi Rong
- Department of Radiation Oncology, University of California Davis Medical Center, Sacramento, CA, USA
| | - Hao Chen
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Zhaoxi Zhang
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Jianfeng Qiu
- Medical Engineering and Technology Center, Taishan Medical University, Taian, PR China
| | - Lili Zheng
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Stanley Benedict
- Department of Radiation Oncology, University of California Davis Medical Center, Sacramento, CA, USA
| | - Xiaohui Niu
- College of Informatics, Huazhong Agricultural University, Wuhan, PR China
| | - Ning Pan
- College of Biomedical Engineering, South Central University for Nationalities, Wuhan, PR China
- Hubei Key Laboratory of Medical Information Analysis and Tumor Diagnosis & Treatment, Wuhan, PR China
| | - Yulin Liu
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Zilong Yuan
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
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Gihr GA, Horvath-Rizea D, Hekeler E, Ganslandt O, Henkes H, Hoffmann KT, Scherlach C, Schob S. Histogram Analysis of Diffusion Weighted Imaging in Low-Grade Gliomas: in vivo Characterization of Tumor Architecture and Corresponding Neuropathology. Front Oncol 2020; 10:206. [PMID: 32158691 PMCID: PMC7051987 DOI: 10.3389/fonc.2020.00206] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 02/06/2020] [Indexed: 02/01/2023] Open
Abstract
Background: Low-grade gliomas (LGG) in adults are usually slow growing and frequently asymptomatic brain tumors, originating from glial cells of the central nervous system (CNS). Although regarded formally as “benign” neoplasms, they harbor the potential of malignant transformation associated with high morbidity and mortality. Their complex and unpredictable tumor biology requires a reliable and conclusive presurgical magnetic resonance imaging (MRI). A promising and emerging MRI approach in this context is histogram based apparent diffusion coefficient (ADC) profiling, which recently proofed to be capable of providing prognostic relevant information in different tumor entities. Therefore, our study investigated whether histogram profiling of ADC distinguishes grade I from grade II glioma, reflects the proliferation index Ki-67, as well as the IDH (isocitrate dehydrogenase) mutation and MGMT (methylguanine-DNA methyl-transferase) promotor methylation status. Material and Methods: Pre-treatment ADC volumes of 26 LGG patients were used for histogram-profiling. WHO-grade, Ki-67 expression, IDH mutation, and MGMT promotor methylation status were evaluated. Comparative and correlative statistics investigating the association between histogram-profiling and neuropathology were performed. Results: Almost the entire ADC profile (p25, p75, p90, mean, median) was significantly lower in grade II vs. grade I gliomas. Entropy, as second order histogram parameter of ADC volumes, was significantly higher in grade II gliomas compared with grade I gliomas. Mean, maximum value (ADCmax) and the percentiles p10, p75, and p90 of ADC histogram were significantly correlated with Ki-67 expression. Furthermore, minimum ADC value (ADCmin) was significantly associated with MGMT promotor methylation status as well as ADC entropy with IDH-1 mutation status. Conclusions: ADC histogram-profiling is a valuable radiomic approach, which helps differentiating tumor grade, estimating growth kinetics and probably prognostic relevant genetic as well as epigenetic alterations in LGG.
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Affiliation(s)
| | | | - Elena Hekeler
- Department for Pathology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Oliver Ganslandt
- Katharinenhospital Stuttgart, Clinic for Neurosurgery, Stuttgart, Germany
| | - Hans Henkes
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, Stuttgart, Germany
| | - Karl-Titus Hoffmann
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Cordula Scherlach
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Stefan Schob
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
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Peng Y, Tang H, Meng X, Shen Y, Hu D, Kamel I, Li Z. Histological grades of rectal cancer: whole-volume histogram analysis of apparent diffusion coefficient based on reduced field-of-view diffusion-weighted imaging. Quant Imaging Med Surg 2020; 10:243-256. [PMID: 31956546 DOI: 10.21037/qims.2019.11.17] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background To explore the role of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) technique in discriminating histological grades of rectal carcinoma. Methods Altogether, 49 patients with rectal cancer were enrolled in this retrospective study. All patients received preoperative 3.0 T MR scan. Histogram parameters from rFOV DWI were calculated and correlated with histological differentiation of rectal cancer. The parameters were compared between different histological grades of rectal cancer by independent Student's t-test or Man-Whitney U-test. The Spearman correlation test analyzed correlations between histological grade and histogram parameters. The diagnostic performance of individual parameters for distinguishing poorly from well-/moderately differentiated tumors was assessed by receiver operating characteristic curve (ROC) analysis. Results There were significant differences for ADCmean, 25th, 50th, 75th, 90th, 95th percentiles, skewness, and kurtosis of rFOV DWI sequence between well-, moderately, and poorly differentiated rectal cancers (P<0.05). Significant correlations were noted between histological grades and the above histogram parameters (r=0.679, 0.540, 0.701, 0.730, 0.669, 0.574, -0.730, and -0.760 respectively, P<0.001). Among the individual histogram parameter, kurtosis achieved the highest AUC of 0.882 with an optimal cutoff value of 1.934 in distinguishing poorly from well-/moderately differentiated rectal cancers. The combination of ADCmean, 75th percentile, and kurtosis yielded the highest AUC of 0.927 with a sensitivity of 88.00% and a sensitivity of 91.7% using logistic regression. Conclusions Quantitative whole-lesion ADC histogram analysis based on the rFOV DWI technique could help differentiate histological grades of rectal cancer. The combination of ADCmean, 75th percentile, and kurtosis may be the best choice.
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Affiliation(s)
- Yang Peng
- Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China
| | - Hao Tang
- Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiaoyan Meng
- Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yaqi Shen
- Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China
| | - Daoyu Hu
- Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ihab Kamel
- Russell H. Morgan Department of Radiology and Radiological Science, the Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
| | - Zhen Li
- Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China
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Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer. Eur Radiol 2019; 30:1297-1305. [DOI: 10.1007/s00330-019-06467-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 08/20/2019] [Accepted: 09/19/2019] [Indexed: 12/13/2022]
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Lee J, Kim CK, Park SY. Histogram analysis of apparent diffusion coefficients for predicting pelvic lymph node metastasis in patients with uterine cervical cancer. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2019; 33:283-292. [DOI: 10.1007/s10334-019-00777-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 07/29/2019] [Accepted: 09/16/2019] [Indexed: 10/25/2022]
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Mongula J, Bakers F, Slangen B, van Kuijk S, Kruitwagen R, Mihl C. Evaluation of various apparent diffusion coefficient measurement techniques in pre-operative staging of early cervical carcinoma. Eur J Radiol 2019; 118:101-106. [DOI: 10.1016/j.ejrad.2019.06.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 06/21/2019] [Accepted: 06/25/2019] [Indexed: 02/08/2023]
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Predictive Factors of Recurrence in Patients with Differentiated Thyroid Carcinoma: A Retrospective Analysis on 579 Patients. Cancers (Basel) 2019; 11:cancers11091230. [PMID: 31443531 PMCID: PMC6770388 DOI: 10.3390/cancers11091230] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Revised: 07/28/2019] [Accepted: 08/20/2019] [Indexed: 01/29/2023] Open
Abstract
Differentiated thyroid carcinoma (DTC) is usually associated with a favorable prognosis. Nevertheless, up to 30% of patients present a local or distant recurrence. The aim of this study was to assess the incidence of recurrence after surgery for DTC and to identify predictive factors of recurrence. We included in this retrospective study 579 consecutive patients who underwent thyroidectomy for DTC from 2011 to 2016 at our institution. We observed biochemical or structural recurrent disease in 36 (6.2%) patients; five-year disease-free survival was 94.1%. On univariate analysis, male sex, histotype, lymph node yield, lymph node metastasis, extrathyroidal invasion and multicentricity were associated with significantly higher risk of recurrence, while microcarcinoma was correlated with significantly lower risk of recurrence. On multivariate analysis, only lymph node metastases (OR 4.724, p = 0.012) and microcarcinoma (OR 0.328, p = 0.034) were detected as independent predictive factors of recurrence. Postoperative management should be individualized and commensurate with the risk of recurrence: Patients with high-risk carcinoma should undergo strict follow-up and aggressive treatment. Furthermore, assessment of the risk should be repeated over time, considering individual response to therapy.
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Meyer HJ, Hamerla G, Höhn AK, Surov A. Whole Lesion Histogram Analysis Derived From Morphological MRI Sequences Might be Able to Predict EGFR- and Her2-Expression in Cervical Cancer. Acad Radiol 2019; 26:e208-e215. [PMID: 30318289 DOI: 10.1016/j.acra.2018.09.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 08/31/2018] [Accepted: 09/09/2018] [Indexed: 01/10/2023]
Abstract
RATIONALE AND OBJECTIVES Histogram analysis is an imaging analysis in which a whole tumor can be assessed, and every voxel of a radiological image is issued into a histogram. Thereby, statistically information about tumor can be obtained. The purpose of the study was to analyze possible relationships between histogram parameters derived from conventional MRI sequences and several histopathological features in cervical squamous cell carcinomas. METHODS A total of 18 female patients (age range 32-79 years) with squamous cell cervical carcinoma were retrospectively enrolled into the study. In all cases, pelvic MRI with a clinically protocol was performed. Histogram analysis was performed as a whole lesion measurement, calculating several percentils, minimum, mean, median, mode, maximum, kurtosis, skewness, and entropy. Histopathological parameters included expression of epidermal-growth factor (EGFR), vascular endothelial growth factor, hypoxia-inducible factor 1-alpha, Her2, and Histone 3. Spearman's correlation coefficient was used to analyze associations between investigated parameters. RESULTS Several pre- and postcontrast derived T1-weighted parameters correlated inversely with EGFR expression. For precontrast T1-weighted images, the strongest correlation was found for p90 (ρ = -0.77, p = 0.004). For postcontrast T1-weighted images, the strongest correlation was observed for minimum (ρ = -0.64, p = 0.021). Several parameters derived from T2-weighted images were statistically significant different between Her2-positive and Her2 negative tumors. Skewness had the best p-value ( p = 0.004). CONCLUSIONS Histogram analysis parameters of T1-weighted and T2-weighted images reflect HER2 status and EGFR expression in cervical cancer. Histogram parameters cannot predict cell count, proliferation index, or angiogenesis related histopathological features.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.
| | - Gordian Hamerla
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | | | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
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Meyer HJ, Renatus K, Höhn AK, Hamerla G, Schopow N, Fakler J, Josten C, Surov A. Texture analysis parameters derived from T1-and T2-weighted magnetic resonance images can reflect Ki67 index in soft tissue sarcoma. Surg Oncol 2019; 30:92-97. [PMID: 31500794 DOI: 10.1016/j.suronc.2019.06.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 04/23/2019] [Accepted: 06/21/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND AND OBJECTIVES Texture analysis derived from morphological magnetic resonance (MR) images might be associated with histopathology in tumors. The present study sought to elucidate possible associations between texture features derived from T1-and T2-weighted images with proliferation index Ki67 in soft tissue sarcomas. METHODS Overall, 29 patients (n = 13, 44.8% female) with a median age of 52 years were included into this retrospective study. Several soft tissue sarcomas were investigated. Texture analysis was performed on pre-contrast T1-weighted and T2-weighted images using the free available Mazda software. RESULTS The best correlation coefficients with Ki67 index were identified for the following parameters: T1-weighted images "45dgr_RLNonUni (p = 0.50, P = 0.006), T2-weighted images "S (4,0)SumAverg" (p = -0.45, P = 0.02). A ROC analysis was performed for Ki67-index with a threshold of 10%. The highest area under the curve (AUC) was found for the parameter "T1_WavEnHL_s-7" with an AUC of 0.90. For the threshold of Ki67 = 20% the highest AUC was identified for the parameter "T2_S (1,1)Entropy" with an AUC of 0.77. CONCLUSION Several texture features derived from T1-and T2-weighted images correlated with proliferation index Ki67 and might be used as valuable novel biomarkers in soft tissue sarcomas.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.
| | - Katharina Renatus
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | | | - Gordian Hamerla
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | - Nikolas Schopow
- Department of Orthopaedics, Trauma Surgery and Plastic Surgery, University of Leipzig, Leipzig, Germany
| | - Johannes Fakler
- Department of Orthopaedics, Trauma Surgery and Plastic Surgery, University of Leipzig, Leipzig, Germany
| | - Christoph Josten
- Department of Orthopaedics, Trauma Surgery and Plastic Surgery, University of Leipzig, Leipzig, Germany
| | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
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Magnetic resonance imaging radiomics in categorizing ovarian masses and predicting clinical outcome: a preliminary study. Eur Radiol 2019; 29:3358-3371. [DOI: 10.1007/s00330-019-06124-9] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Revised: 02/09/2019] [Accepted: 02/22/2019] [Indexed: 12/13/2022]
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Wang T, Gao T, Yang J, Yan X, Wang Y, Zhou X, Tian J, Huang L, Zhang M. Preoperative prediction of pelvic lymph nodes metastasis in early-stage cervical cancer using radiomics nomogram developed based on T2-weighted MRI and diffusion-weighted imaging. Eur J Radiol 2019; 114:128-135. [PMID: 31005162 DOI: 10.1016/j.ejrad.2019.01.003] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 12/29/2018] [Accepted: 01/04/2019] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To explore an MRI-based radiomics nomogram for preoperatively predicting of pelvic lymph node (PLN) metastasis in patients with early-stage cervical cancer (ECC). METHODS Ninety-six patients with ECC were enrolled in this study. All patients underwent T2WI and DWI scans before radical hysterectomy with PLN dissection surgery. Radiomics features extracted from T2WI and DWI were selected by least absolute shrinkage and selection operation regression for further radimoics signature calculation. The discrimination of this radiomics signature for PLN metastasis was then assessed using a support vector machine (SVM) model. Subsequently, a radiomics nomogram was constructed based on the radiomics signature and clinicopathologic risk factors using a multivariable logistic regression method. The performance of the radiomics nomogram for the preoperative prediction of PLN metastasis was evaluated for discrimination and calibration. RESULTS The radiomics signatures demonstrated a good discrimination for PLN metastasis. A radiomics signature derived from joint T2WI and DWI yielded higher AUC than the signatures derived from T2WI or DWI alone. The radiomics nomogram integrating the radiomics signature with clinicopathologic risk factors showed a significant improvement over the nomogram based only on clinicopathologic risk factors in the primary cohort(C-index, 0.893 vs. 0.616; P = 4.311×10-5) and validation cohort(C-index, 0.922 vs. 0.799; P = 3.412 ×10-2).The calibration curves also showed good agreement. CONCLUSIONS The radiomics nomogram based on joint T2WI and DWI demonstrated an improved prediction ability for PLN metastasis in ECC. This noninvasive and convenient tool may be used to facilitate preoperative identification of PLN metastasis in patients with ECC.
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Affiliation(s)
- Tao Wang
- Department of Medical Imaging, First Affiliated Hospital of Xi'an Jiaotong University, No.277, West Yanta Road, Xi'an, 710061, Shaanxi, People's Republic of China; Department of Radiology, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, 710068, People's Republic of China
| | - Tingting Gao
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China
| | - Jingbo Yang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China
| | - Xuejiao Yan
- Room of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, 710068, People's Republic of China
| | - Yubo Wang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China
| | - Xiaobo Zhou
- Department of Radiology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
| | - Jie Tian
- Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, 100080, People's Republic of China
| | - Liyu Huang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China.
| | - Ming Zhang
- Department of Medical Imaging, First Affiliated Hospital of Xi'an Jiaotong University, No.277, West Yanta Road, Xi'an, 710061, Shaanxi, People's Republic of China.
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Meyer HJ, Schob S, Münch B, Frydrychowicz C, Garnov N, Quäschling U, Hoffmann KT, Surov A. Histogram Analysis of T1-Weighted, T2-Weighted, and Postcontrast T1-Weighted Images in Primary CNS Lymphoma: Correlations with Histopathological Findings-a Preliminary Study. Mol Imaging Biol 2019; 20:318-323. [PMID: 28865050 DOI: 10.1007/s11307-017-1115-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE Previously, some reports mentioned that magnetic resonance imaging (MRI) can predict histopathological features in primary CNS lymphoma (PCNSL). The reported data analyzed diffusion-weighted imaging findings. The aim of this study was to investigate possible associations between histopathological findings, such as tumor cellularity, nucleic areas and proliferation index Ki-67, and signal intensity on T1-weighted and T2-weighted images in PCNSL. PROCEDURES For this study, 18 patients with PCNSL were retrospectively investigated by histogram analysis on precontrast and postcontrast T1-weighted and fluid-attenuated inversion recovery (FLAIR) images. For every patient, histopathology parameters, nucleic count, total nucleic area, and average nucleic area, as well as Ki-67 index, were estimated. RESULTS Correlation analysis identified several statistically significant associations. Skewness derived from precontrast T1-weighted images correlated with Ki-67 index (p = - 0.55, P = 0.028). Furthermore, entropy derived from precontrast T1-weighted images correlated with average nucleic area (p = 0.53, P = 0.04). Several parameters from postcontrast T1-weighted images correlated with nucleic count: maximum signal intensity (p = 0.59, P = 0.017), P75 (p = 0.56, P = 0.02), and P90 (p = 0.52, P = 0.04) as well as SD (p = 0.58, P = 0.02). Maximum signal intensity derived from FLAIR sequence correlated with nucleic count (p = 0.50, P = 0.03). CONCLUSION Histogram-derived parameters of conventional MRI sequences can reflect different histopathological features in PSNCL.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, University Leipzig, Liebigstraße 20, 04103, Leipzig, Germany.
| | - Stefan Schob
- Department of Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Benno Münch
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, University Leipzig, Liebigstraße 20, 04103, Leipzig, Germany
| | | | - Nikita Garnov
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, University Leipzig, Liebigstraße 20, 04103, Leipzig, Germany
| | - Ulf Quäschling
- Department of Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | | | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, University Leipzig, Liebigstraße 20, 04103, Leipzig, Germany
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Meyer HJ, Gundermann P, Höhn AK, Hamerla G, Surov A. Associations between whole tumor histogram analysis parameters derived from ADC maps and expression of EGFR, VEGF, Hif 1-alpha, Her-2 and Histone 3 in uterine cervical cancer. Magn Reson Imaging 2018; 57:68-74. [PMID: 30367998 DOI: 10.1016/j.mri.2018.10.016] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 09/23/2018] [Accepted: 10/22/2018] [Indexed: 12/09/2022]
Abstract
OBJECTIVE Diffusion weighted imaging (DWI) can be quantified by apparent diffusion coefficient (ADC) and can predict tissue microstructure. The aim of the present study was to analyze possible associations between ADC histogram based parameters with different histopathological parameters in cervical squamous cell carcinoma. MATERIALS AND METHODS 18 female patients (age range 32-79 years) with squamous cell cervical carcinoma were retrospectively enrolled. In all cases, pelvic MRI was performed with a DWI (b-values 0 and 1000 s/mm2). Histogram analysis was performed as a whole lesion measurement. Histopathological parameters included expression of EGFR, VEGF, Hif1-alpha, Her2 and Histone 3. Spearman's correlation coefficient was used to analyze associations between investigated parameters. RESULTS Analyze of the investigated ADC histogram parameters showed a good interreader variability, ranging from 0.705 for entropy to 0.959 for ADCmedian. EGFR expression correlated statistically significant with several histogram parameters. The highest correlation was observed for p75 (p = -0.562, P = 0.015). There were several correlations with histone 3, the highest with p25 (p = -0.610, P = 0.007). None of the ADC related parameters correlated statistically significant with expression of VEGF, Hif1-alpha and Her2. CONCLUSION Histogram analysis showed a good interreader agreement. ADC histogram parameters might be able to reflect expression of EGFR and histone 3 in cervical squamous cell carcinomas, but not expression of VEGF, Hif1-alpha and Her2.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
| | - Peter Gundermann
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
| | - Anne Kathrin Höhn
- Department of Pathology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
| | - Gordian Hamerla
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
| | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
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Meyer HJ, Leifels L, Hamerla G, Höhn AK, Surov A. Histogram Analysis Parameters Derived from Conventional T1- and T2-Weighted Images Can Predict Different Histopathological Features Including Expression of Ki67, EGFR, VEGF, HIF-1α, and p53 and Cell Count in Head and Neck Squamous Cell Carcinoma. Mol Imaging Biol 2018; 21:740-746. [DOI: 10.1007/s11307-018-1283-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Meyer HJ, Purz S, Sabri O, Surov A. Relationships between histogram analysis of ADC values and complex 18F-FDG-PET parameters in head and neck squamous cell carcinoma. PLoS One 2018; 13:e0202897. [PMID: 30188926 PMCID: PMC6126801 DOI: 10.1371/journal.pone.0202897] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2017] [Accepted: 08/10/2018] [Indexed: 11/26/2022] Open
Abstract
Purpose Histogram analysis is an emergent imaging technique to further analyze radiological images and to obtain imaging biomarker. In head and neck cancer, MRI and PET are routinely used in clinical practice. The aim of this study was to analyze associations between histogram based ADC parameters and complex FDG-PET derived parameters in head and neck squamous cell carcinoma (HNSCC). Methods 34 patients (26% female, mean age, 56.7 ± 10.2 years) with primary HNSCC were prospectively included into the study. ADC histogram parameters were calculated by inhouse made matlab software using a whole lesion measurement. For each tumor, maximum and mean standardized uptake values (SUVmax, SUVmean), Total Lesion Glycolysis (TLG) and Metabolic Tumor Volume (MTV) were determined on PET-images. Spearman's correlation coefficient (ρ) was used to analyze associations between investigated parameters. Benjamini-Hochberg correction was used to adjust for multiple testing. Mann-Whitney test was used for group discrimination. P-values < 0.05 were taken to indicate statistical significance. Results The correlation analysis in the whole tumor group revealed a statistically significant correlation between entropy and MTV as well as TLG (ρ = 0.67, P<0.0001 and ρ = 0.61, P = 0.0002 respectively). There were statistically significant differences between T1/2 and T3/4 tumors in the following parameters: entropy (2.07 ± 0.36 vs 2.61 ± 0.43, P = 0.007), SUVmax (10.79 ± 4.13 vs 17.93 ± 5.89, P = 0.007), SUVmean (6.39 ± 2.48 vs 9.81 ± 4.49, P = 0.01), SUVmin (4.09 ± 1.57 vs 6.34 ± 2.59, P = 0.03), MTV (9.50 ± 7.92 vs 20.36 ± 13.30, P = 0.02), TGU (55.97 ± 39.09 vs 212.3 ± 186.3, P = 0.002). Conclusion This study showed that entropy derived from ADC maps is strongly associated with MTV and TLG in HNSCC. Entropy, SUVmax, SUVmean, TLG and MTV were statistically significant higher in T3/4 tumors in comparison to T1/2 carcinomas.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
- * E-mail:
| | - Sandra Purz
- Department of Nuclear Medicine, University of Leizig, Leipzig, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University of Leizig, Leipzig, Germany
| | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
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Meyer HJ, Leifels L, Hamerla G, Höhn AK, Surov A. ADC-histogram analysis in head and neck squamous cell carcinoma. Associations with different histopathological features including expression of EGFR, VEGF, HIF-1α, Her 2 and p53. A preliminary study. Magn Reson Imaging 2018; 54:214-217. [PMID: 30189236 DOI: 10.1016/j.mri.2018.07.013] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 07/23/2018] [Accepted: 07/23/2018] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Apparent diffusion coefficient (ADC) values derived from Diffusion-weighted images are able to reflect tumor microstructure, such as cellularity, extracellular matrix or proliferation potential. This present study sought to correlate prognostic relevant histopathologic parameters with ADC values derived from a whole lesion measurement in head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS Thirty-four patients with histological proven primary HNSCC were prospectively acquired. Histogram analysis was derived from ADC maps. In all cases, expression of Hif1-alpha, VEGF, EGFR, p53, p16, Her 2 were analyzed. RESULTS In the overall patient sample, ADCmax correlated with p53 expression (p = -0.446, p = 0.009) and ADCmode correlated with Her2-expression (p = -0.354, p = 0.047). In the p16 positive group there were several correlations. P25, P90 and entropy correlated with Hif1-alpha (p = -0.423, p = 0.05, p = -0.494, p = 0.019, p = 0.479, p = 0.024, respectively). Kurtosis correlated with P53 expression (p = -0.466, p = 0.029). For p16 negative carcinomas the following associations could be identified. Mode correlated with VEGF-expression (p = -0.657, p = 0.039). ADCmax, P75, P90, and Std correlated with p53-expression (p = -0.827, p = 0.002, p = -0.736, p = 0.01, p = -0.836, p = 0.001 and p = -0.70, p = 0.016, respectively). There were no statistically significant differences of ADC histogram parameters between p16 positive and p16 negative carcinomas. CONCLUSION ADC histogram values can reflect different histopathological features in HNSCC. Associations between ADC histogram analysis parameters and histopathology depend on p16 status.
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Affiliation(s)
- Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
| | - Leonard Leifels
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
| | - Gordian Hamerla
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
| | | | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
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Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma. Childs Nerv Syst 2018; 34:1651-1656. [PMID: 29855678 DOI: 10.1007/s00381-018-3846-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 05/17/2018] [Indexed: 12/16/2022]
Abstract
BACKGROUND Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. MATERIAL AND METHODS Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. RESULTS ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). DISCUSSION AND CONCLUSION Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.
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Cervical Cancer: Associations between Metabolic Parameters and Whole Lesion Histogram Analysis Derived from Simultaneous 18F-FDG-PET/MRI. CONTRAST MEDIA & MOLECULAR IMAGING 2018; 2018:5063285. [PMID: 30154687 PMCID: PMC6098855 DOI: 10.1155/2018/5063285] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 06/12/2018] [Accepted: 06/25/2018] [Indexed: 01/16/2023]
Abstract
Multimodal imaging has been increasingly used in oncology, especially in cervical cancer. By using a simultaneous positron emission (PET) and magnetic resonance imaging (MRI, PET/MRI) approach, PET and MRI can be obtained at the same time which minimizes motion artefacts and allows an exact imaging fusion, which is especially important in anatomically complex regions like the pelvis. The associations between functional parameters from MRI and 18F-FDG-PET reflecting different tumor aspects are complex with inconclusive results in cervical cancer. The present study correlates histogram analysis and 18F-FDG-PET parameters derived from simultaneous FDG-PET/MRI in cervical cancer. Overall, 18 female patients (age range: 32–79 years) with histopathologically confirmed squamous cell cervical carcinoma were retrospectively enrolled. All 18 patients underwent a whole-body simultaneous 18F-FDG-PET/MRI, including diffusion-weighted imaging (DWI) using b-values 0 and 1000 s/mm2. Apparent diffusion coefficient (ADC) histogram parameters included several percentiles, mean, min, max, mode, median, skewness, kurtosis, and entropy. Furthermore, mean and maximum standardized uptake values (SUVmean and SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were estimated. No statistically significant correlations were observed between SUVmax or SUVmean and ADC histogram parameters. TLG correlated inversely with p25 (r=−0.486, P=0.041), p75 (r=−0.490, P=0.039), p90 (r=−0.513, P=0.029), ADC median (r=−0.497, P=0.036), and ADC mode (r=−0.546, P=0.019). MTV also showed significant correlations with several ADC parameters: mean (r=−0.546, P=0.019), p10 (r=−0.473, P=0.047), p25 (r=−0.569, P=0.014), p75 (r=−0.576, P=0.012), p90 (r=−0.585, P=0.011), ADC median (r=−0.577, P=0.012), and ADC mode (r=−0.597, P=0.009). ADC histogram analysis and volume-based metabolic 18F-FDG-PET parameters are related to each other in cervical cancer.
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Meyer HJ, Pazaitis N, Surov A. ADC histogram analysis of muscle lymphoma-correlation with histopathology in a rare entity. Br J Radiol 2018; 91:20180291. [PMID: 29927638 DOI: 10.1259/bjr.20180291] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE: Diffusion-weighted imaging is able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize lesion on MRI. To correlate histogram parameters derived from apparent diffusion coefficient (ADC) maps with histopathology parameters in muscle lymphoma. METHODS: Eight patients (mean age 64.8 years, range 45-72 years) with histopathologically confirmed muscle lymphoma were retrospectively identified. Cell count, total nucleic and average nucleic areas were estimated using ImageJ. Additionally, Ki67-index was calculated. Diffusion-weightedimaging was obtained on a 1.5 T scanner by using the b-values of 0 and 1000 s mm-2. Histogram analysis was performed as a whole lesion measurement by using a custom-made Matlab-based application. RESULTS: All ADC parameters showed a good to excellent interreader variability. Cell count correlated well with ADCmean (ρ = -0.76, p = 0.03) and ADCp75 (ρ =-0.79, p = 0.02). Kurtosis and entropy correlated with average nucleic area (ρ = -0.81, p = 0.02, ρ =0.88, p = 0.007, respectively). None of the analyzed ADC parameters correlated with total nucleic area and with Ki67-index. CONCLUSION: ADC histogram analysis parameters can reflect cellularity in muscle lymphoma. ADVANCES IN KNOWLEDGE: Histogram parameters derived from ADC maps can reflect several different cellularity parameters in muscle lymphoma.
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Affiliation(s)
- Hans-Jonas Meyer
- 1 Department of Diagnostic and Interventional Radiology, University of Leipzig , Leipzig , Germany
| | - Nikolaos Pazaitis
- 2 Department of Pathology, Martin-Luther-University Halle-Wittenberg , Halle , Germany
| | - Alexey Surov
- 1 Department of Diagnostic and Interventional Radiology, University of Leipzig , Leipzig , Germany
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Surov A, Ginat DT, Lim T, Cabada T, Baskan O, Schob S, Meyer HJ, Gihr GA, Horvath-Rizea D, Hamerla G, Hoffmann KT, Wienke A. Histogram Analysis Parameters Apparent Diffusion Coefficient for Distinguishing High and Low-Grade Meningiomas: A Multicenter Study. Transl Oncol 2018; 11:1074-1079. [PMID: 30005209 PMCID: PMC6067084 DOI: 10.1016/j.tranon.2018.06.010] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2018] [Revised: 06/23/2018] [Accepted: 06/25/2018] [Indexed: 01/11/2023] Open
Abstract
Low grade meningiomas have better prognosis than high grade meningiomas. The aim of this study was to measure apparent diffusion coefficient (ADC) histogram analysis parameters in different meningiomas in a large multicenter sample and to analyze the possibility of several parameters for predicting tumor grade and proliferation potential. Overall, 148 meningiomas from 7 institutions were evaluated in this retrospective study. Grade 1 lesions were diagnosed in 101 (68.2%) cases, grade 2 in 41 (27.7%) patients, and grade 3 in 6 (4.1%) patients. All tumors were investigated by MRI (1.5 T scanner) by using diffusion weighted imaging (b values of 0 and 1000 s/mm2). For every lesion, the following parameters were calculated: mean ADC, maximum ADC, minimum ADC, median ADC, mode ADC, ADC percentiles P10, P25, P75, P90, kurtosis, skewness, and entropy. The comparison of ADC values was performed by Mann–Whitney-U test. Correlation between different ADC parameters and KI 67 was calculated by Spearman's rank correlation coefficient. Grade 2/3 meningiomas showed statistically significant lower ADC histogram analysis parameters in comparison to grade 1 tumors, especially ADC median. A threshold value of 0.82 for ADC median to predict tumor grade was estimated (sensitivity = 82.2%, specificity = 63.8%, accuracy = 76.4%, positive and negative predictive values were 83% and 62.5%, respectively). All ADC parameters except maximum ADC showed weak significant correlations with KI 67, especially ADC P25 (P = −.340, P = .0001).
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Affiliation(s)
- Alexey Surov
- Department of Radiology, Martin-Luther-University Halle-Wittenberg, Germany; Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
| | - Daniel T Ginat
- University of Chicago, Pritzker School of Medicine, Chicago, IL, USA
| | - Tchoyoson Lim
- Department of Neuroradiology, National Neuroscience Institute, Singapore
| | - Teresa Cabada
- Servicio de Radiologia, Hospital de Navarra, Pamplona, Spain
| | - Ozdil Baskan
- Department of Radiology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Stefan Schob
- Department of Neuroradiology, University of Leipzig
| | - Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany
| | | | | | | | | | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther University Halle-Wittenberg, Halle, Germany
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Gihr GA, Horvath-Rizea D, Kohlhof-Meinecke P, Ganslandt O, Henkes H, Richter C, Hoffmann KT, Surov A, Schob S. Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas. Transl Oncol 2018; 11:957-961. [PMID: 29909365 PMCID: PMC6008484 DOI: 10.1016/j.tranon.2018.05.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2018] [Revised: 05/24/2018] [Accepted: 05/24/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND: Meningiomas are the most frequently diagnosed intracranial masses, oftentimes requiring surgery. Especially procedure-related morbidity can be substantial, particularly in elderly patients. Hence, reliable imaging modalities enabling pretherapeutic prediction of tumor grade, growth kinetic, realistic prognosis, and—as a consequence—necessity of surgery are of great value. In this context, a promising diagnostic approach is advanced analysis of magnetic resonance imaging data. Therefore, our study investigated whether histogram profiling of routinely acquired postcontrast T1-weighted images is capable of separating low-grade from high-grade lesions and whether histogram parameters reflect Ki-67 expression in meningiomas. MATERIAL AND METHODS: Pretreatment T1-weighted postcontrast volumes of 44 meningioma patients were used for signal intensity histogram profiling. WHO grade, tumor volume, and Ki-67 expression were evaluated. Comparative and correlative statistics investigating the association between histogram profile parameters and neuropathology were performed. RESULTS: None of the investigated histogram parameters revealed significant differences between low-grade and high-grade meningiomas. However, significant correlations were identified between Ki-67 and the histogram parameters skewness and entropy as well as between entropy and tumor volume. CONCLUSIONS: Contrary to previously reported findings, pretherapeutic postcontrast T1-weighted images can be used to predict growth kinetics in meningiomas if whole tumor histogram analysis is employed. However, no differences between distinct WHO grades were identifiable in out cohort. As a consequence, histogram analysis of postcontrast T1-weighted images is a promising approach to obtain quantitative in vivo biomarkers reflecting the proliferative potential in meningiomas.
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Affiliation(s)
| | | | | | - Oliver Ganslandt
- Katharinenhospital Stuttgart, Neurosurgical Clinic, Stuttgart, Germany
| | - Hans Henkes
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, Stuttgart, Germany
| | - Cindy Richter
- University Hospital Leipzig, Department for Neuroradiology, Leipzig, Germany
| | - Karl-Titus Hoffmann
- University Hospital Leipzig, Department for Neuroradiology, Leipzig, Germany
| | - Alexey Surov
- University Hospital Leipzig, Clinic for Diagnostic and Interventional Radiology, Leipzig, Germany
| | - Stefan Schob
- University Hospital Leipzig, Department for Neuroradiology, Leipzig, Germany
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Surov A, Hamerla G, Meyer HJ, Winter K, Schob S, Fiedler E. Whole lesion histogram analysis of meningiomas derived from ADC values. Correlation with several cellularity parameters, proliferation index KI 67, nucleic content, and membrane permeability. Magn Reson Imaging 2018; 51:158-162. [PMID: 29782920 DOI: 10.1016/j.mri.2018.05.009] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Revised: 05/17/2018] [Accepted: 05/17/2018] [Indexed: 11/19/2022]
Abstract
PURPOSE To analyze several histopathological features and their possible correlations with whole lesion histogram analysis derived from ADC maps in meningioma. MATERIALS AND METHODS The retrospective study involved 36 patients with primary meningiomas. For every tumor, the following histogram analysis parameters of apparent diffusion coefficient (ADC) were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, ADC percentiles: P10, P25, P75, P90, as well kurtosis, skewness, and entropy. All measures were performed by two radiologists. Proliferation index KI 67, minimal, maximal and mean cell count, total nucleic area, and expression of water channel aquaporin 4 (AQP4) were estimated. Spearman's correlation coefficient was used to analyze associations between investigated parameters. RESULTS A perfect interobserver agreement for all ADC values (0.84-0.97) was identified. All ADC values correlated inversely with tumor cellularity with the strongest correlation between P10, P25 and mean cell count (-0.558). KI 67 correlated inversely with all ADC values except ADCmin. ADC parameters did not correlate with total nucleic area. All ADC values correlated statistically significant with expression of AQP4. CONCLUSIONS ADC histogram analysis is a valid method with an excellent interobserver agreement. Cellularity parameters and proliferation potential are associated with different ADC values. Membrane permeability may play a greater role for water diffusion than cell count and proliferation activity.
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Affiliation(s)
- Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany; Department of Radiology, Martin-Luther-university Halle-Wittenberg, Germany.
| | - Gordian Hamerla
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany
| | - Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany
| | - Karsten Winter
- Institute of Neuroanatomy, University of Leipzig, Germany; Institute of Biometry, University of Leipzig, Germany
| | - Stefan Schob
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany
| | - Eckhard Fiedler
- Department of Dermatology, Martin-Luther-university Halle-Wittenberg, Germany
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Liu Y, Zhang Y, Cheng R, Liu S, Qu F, Yin X, Wang Q, Xiao B, Ye Z. Radiomics analysis of apparent diffusion coefficient in cervical cancer: A preliminary study on histological grade evaluation. J Magn Reson Imaging 2018; 49:280-290. [PMID: 29761595 DOI: 10.1002/jmri.26192] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 04/26/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND The role of apparent diffusion coefficient (ADC)-based radiomics features in evaluating histopathological grade of cervical cancer is unresolved. PURPOSE To determine if there is a difference between radiomics features derived from center-slice 2D versus whole-tumor volumetric 3D for ADC measurements in patients with cervical cancer regarding tumor histopathological grade, and systematically assess the impact of the b value on radiomics analysis in ADC quantifications. STUDY TYPE Prospective. SUBJECTS In all, 160 patients with histopathologically confirmed squamous cell carcinoma of uterine cervix. FIELD STRENGTH/SEQUENCE Conventional and diffusion-weighted MR images (b values = 0, 800, 1000 s/mm2 ) were acquired on a 3.0T MR scanner. ASSESSMENT Regions of interest (ROIs) were drawn manually along the margin of tumor on each slice, and then the center slice of the tumor was selected with naked eyes in the course of whole-tumor segmentation. A total of 624 radiomics features were derived from T2 -weighted images and ADC maps. We randomly selected 50 cases and did the reproducibility analysis. STATISTICAL TESTS Parameters were compared using Wilcoxon signed rank test, Bland-Altman analysis, t-test, and least absolute shrinkage and selection operator (LASSO) regression with crossvalidation. RESULTS In all, 95 radiomics features were insensitive to ROI variation among T2 images, ADC map of b800, and ADC map of b1000 (P > 0.0002). There was a significant statistical difference between the performances of 2D center-slice and 3D whole-tumor radiomics models in both ADC feature sets of b800 and b1000 (P < 0.0001, P < 0.0001). Compared with ADC features of b800 (0.3758 ± 0.0118), the model of b1000 ADC features appeared to be slightly lower in overall misclassification error (0.3642 ± 0.0162) (P = 0.0076). DATA CONCLUSION Several radiomics features extracted from T2 images and ADC maps were highly reproducible. Whole-tumor volumetric 3D radiomics analysis had a better performance than using the 2D center-slice of tumor in stratifying the histological grade of cervical cancer. A b value of 1000 s/mm2 is suggested as the optimal parameter in pelvic DWI scans. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:280-290.
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Affiliation(s)
- Ying Liu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Yuwei Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China.,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Runfen Cheng
- Department of Pathology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Shichang Liu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Fangyuan Qu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Xiaoyu Yin
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Qin Wang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Bohan Xiao
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
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Surov A, Meyer HJ, Winter K, Richter C, Hoehn AK. Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma. Oncotarget 2018; 9:23599-23607. [PMID: 29805759 PMCID: PMC5955087 DOI: 10.18632/oncotarget.25284] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 04/06/2018] [Indexed: 11/26/2022] Open
Abstract
Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADCmean, ADCmin, ADCmedian, and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADCmean, ADCmin, ADCmedian, P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading.
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Affiliation(s)
- Alexey Surov
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, Leipzig 04103, Germany
| | - Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, Leipzig 04103, Germany
| | - Karsten Winter
- Institute of Anatomy, University Hospital of Leipzig, Leipzig 04103, Germany
| | - Cindy Richter
- Institute of Anatomy, University Hospital of Leipzig, Leipzig 04103, Germany
| | - Anna-Kathrin Hoehn
- Department of Pathology, University Hospital of Leipzig, Leipzig 04103, Germany
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Surov A, Meyer HJ, Leifels L, Höhn AK, Richter C, Winter K. Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma. Oncotarget 2018; 9:21070-21077. [PMID: 29765520 PMCID: PMC5940412 DOI: 10.18632/oncotarget.24920] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Accepted: 03/06/2018] [Indexed: 02/07/2023] Open
Abstract
Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC). 30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of Ktrans, Ve, and Kep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. KI 67 correlated with Ktrans min (p = −0.386, P = 0.043) and s Ktrans skewness (p = 0.382, P = 0.045), Ve min (p = −0.473, P = 0.011), Ve entropy (p = 0.424, P = 0.025), and Kep entropy (p = 0.464, P = 0.013). Cell count correlated with Ktrans kurtosis (p = 0.40, P = 0.034), Ve entropy (p = 0.475, P = 0.011). Total nucleic area correlated with Ve max (p = 0.386, P = 0.042) and Ve entropy (p = 0.411, P = 0.030). In G1/2 tumors, only Ktrans entropy correlated well with total (P =0.78, P =0.013) and average nucleic areas (p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min (p = −0.552, P = 0.022) and Ve entropy (p = 0.524, P = 0.031). Ve max correlated with total nucleic area (p = 0.483, P = 0.049). Kep max correlated with total area (p = −0.51, P = 0.037), and Kep entropy with KI 67 (p = 0.567, P = 0.018). We concluded that histogram-based parameters skewness, kurtosis and entropy of Ktrans, Ve, and Kep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.
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Affiliation(s)
- Alexey Surov
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Leonard Leifels
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Anne-Kathrin Höhn
- Department of Pathology University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Cindy Richter
- Institute of Anatomy, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Karsten Winter
- Institute of Anatomy, University Hospital of Leipzig, 04103 Leipzig, Germany
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49
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Horvath-Rizea D, Surov A, Hoffmann KT, Garnov N, Vörkel C, Kohlhof-Meinecke P, Ganslandt O, Bäzner H, Gihr GA, Kalman M, Henkes E, Henkes H, Schob S. The value of whole lesion ADC histogram profiling to differentiate between morphologically indistinguishable ring enhancing lesions-comparison of glioblastomas and brain abscesses. Oncotarget 2018; 9:18148-18159. [PMID: 29719596 PMCID: PMC5915063 DOI: 10.18632/oncotarget.24454] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2017] [Accepted: 01/30/2018] [Indexed: 12/17/2022] Open
Abstract
Background Morphologically similar appearing ring enhancing lesions in the brain parenchyma can be caused by a number of distinct pathologies, however, they consistently represent life-threatening conditions. The two most frequently encountered diseases manifesting as such are glioblastoma multiforme (GBM) and brain abscess (BA), each requiring disparate therapeutical approaches. As a result of their morphological resemblance, essential treatment might be significantly delayed or even ommited, in case results of conventional imaging remain inconclusive. Therefore, our study aimed to investigate, whether ADC histogram profiling reliably can distinguish between both entities, thus enhancing the differential diagnostic process and preventing treatment failure in this highly critical context. Methods 103 patients (51 BA, 52 GBM) with histopathologically confirmed diagnosis were enrolled. Pretreatment diffusion weighted imaging (DWI) was obtained in a 1.5T system using b values of 0, 500, and 1000 s/mm2. Whole lesion ADC volumes were analyzed using a histogram-based approach. Statistical analysis was performed using SPSS version 23. Results All investigated parameters were statistically different in comparison of both groups. Most importantly, ADCp10 was able to differentiate reliably between BA and GBM with excellent accuracy (0.948) using a cutpoint value of 70 × 10−5 mm2 × s−1. Conclusions ADC whole lesion histogram profiling provides a valuable tool to differentiate between morphologically indistinguishable mass lesions. Among the investigated parameters, the 10th percentile of the ADC volume distinguished best between GBM and BA.
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Affiliation(s)
| | - Alexey Surov
- Clinic for Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany
| | - Karl-Titus Hoffmann
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | | | - Cathrin Vörkel
- Clinic for Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany
| | | | - Oliver Ganslandt
- Clinic for Neurosurgery, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Hansjörg Bäzner
- Clinic for Neurology, Katherinenhospital Stuttgart, Stuttgart, Germany
| | | | - Marcell Kalman
- Clinic for Neuroradiology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Elina Henkes
- Clinic for Neuroradiology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Hans Henkes
- Clinic for Neuroradiology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Stefan Schob
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
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Meyer HJ, Höhn A, Surov A. Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study. Oncotarget 2018; 9:18510-18517. [PMID: 29719621 PMCID: PMC5915088 DOI: 10.18632/oncotarget.24905] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 03/11/2018] [Indexed: 12/19/2022] Open
Abstract
Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10-3mm2/s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction.
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Affiliation(s)
- Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Annekathrin Höhn
- Department of Pathology University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, 04103 Leipzig, Germany
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