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Song T, Lu S, Qu J, Zhang H, Wang Z, Jia Z, Li H, Zhao Y, Qin J, Feng W, Wang S, Yan X. Intravoxel incoherent motion diffusion-weighted imaging in evaluating preoperative staging of esophageal squamous cell carcinoma : Evaluation of preoperative stage of primary tumour and prediction of lymph node metastases from esophageal cancer using IVIM: a prospective study. Cancer Imaging 2024; 24:116. [PMID: 39210470 PMCID: PMC11363402 DOI: 10.1186/s40644-024-00765-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 08/26/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND The aim of this research is to prospectively investigate the diagnostic performance of intravoxel incoherent motion (IVIM) using the integrated slice-specific dynamic shimming (iShim) technique in staging primary esophageal squamous cell carcinoma (ESCC) and predicting presence of lymph node metastases from ESCC. METHODS Sixty-three patients with ESCC were prospectively enrolled from April 2016 to April 2019. MR and IVIM using iShim technique (b = 0, 25, 50, 75, 100, 200, 400, 600, 800 s/mm2) were performed on 3.0T MRI system before operation. Primary tumour apparent diffusion coefficient (ADC) and IVIM parameters, including true diffusion coefficient (D), pseudodiffusion coefficient (D*), pseudodiffusion fraction (f) were measured by two independent radiologists. The differences in D, D*, f and ADC values of different T and N stages were assessed. Intraclass correlation coefficients (ICCs) were calculated to evaluate the interobserver agreement between two readers. The diagnostic performances of D, D*, f and ADC values in primary tumour staging and prediction of lymph node metastasis of ESCC were determined using receiver operating characteristic (ROC) curve analysis. RESULTS The inter-observer consensus was excellent for IVIM parameters and ADC (D: ICC = 0.922; D*: ICC = 0.892; f: ICC = 0.948; ADC: ICC = 0.958). The ADC, D, D* and f values of group T1 + T2 were significantly higher than those of group T3 + T4a [ADC: (2.55 ± 0.43) ×10- 3 mm2/s vs. (2.27 ± 0.40) ×10- 3 mm2/s, t = 2.670, P = 0.010; D: (1.82 ± 0.39) ×10- 3 mm2/s vs. (1.53 ± 0.33) ×10- 3 mm2/s, t = 3.189, P = 0.002; D*: 46.45 (30.30,55.53) ×10- 3 mm2/s vs. 32.30 (18.60,40.95) ×10- 3 mm2/s, z=-2.408, P = 0.016; f: 0.45 ± 0.12 vs. 0.37 ± 0.12, t = 2.538, P = 0.014]. The ADC, D and f values of the lymph nodes-positive (N+) group were significantly lower than those of lymph nodes-negative (N0) group [ADC: (2.10 ± 0.33) ×10- 3 mm2/s vs. (2.55 ± 0.40) ×10- 3 mm2/s, t=-4.564, P < 0.001; D: (1.44 ± 0.30) ×10- 3 mm2/s vs. (1.78 ± 0.37) ×10- 3 mm2/s, t=-3.726, P < 0.001; f: 0.32 ± 0.10 vs. 0.45 ± 0.11, t=-4.524, P < 0.001]. The combination of D, D* and f yielded the highest area under the curve (AUC) (0.814) in distinguishing group T1 + T2 from group T3 + T4a. D combined with f provided the highest diagnostic performance (AUC = 0.849) in identifying group N + and group N0 of ESCC. CONCLUSIONS IVIM may be used as an effective functional imaging technique to evaluate preoperative stage of primary tumour and predict presence of lymph node metastases from ESCC.
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Affiliation(s)
- Tao Song
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Shuang Lu
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Jinrong Qu
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
- Henan Province, 127 Dongming road, Jinshui District, Zhengzhou city, 450008, China.
| | - Hongkai Zhang
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Zhaoqi Wang
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Zhengyan Jia
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Hailiang Li
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Yan Zhao
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Jianjun Qin
- Department of Thoracic Surgery, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Wen Feng
- Department of Pathology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, XI'an, 710065, China
| | - Xu Yan
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
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Cheng Q, Ren A, Xu X, Meng Z, Feng X, Pylypenko D, Dou W, Yu D. Application of DKI and IVIM imaging in evaluating histologic grades and clinical stages of clear cell renal cell carcinoma. Front Oncol 2023; 13:1203922. [PMID: 37954085 PMCID: PMC10637387 DOI: 10.3389/fonc.2023.1203922] [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: 04/11/2023] [Accepted: 10/09/2023] [Indexed: 11/14/2023] Open
Abstract
Purpose To evaluate the value of quantitative parameters derived from diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in differentiating histologic grades and clinical stages of clear cell renal cell carcinoma (ccRCC). Materials and methods A total of 65 patients who were surgically and pathologically diagnosed as ccRCC were recruited in this study. In addition to routine renal magnetic resonance imaging examination, all patients underwent preoperative IVIM and DKI. The corresponding diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean diffusivity (MD), kurtosis anisotropy (KA), and mean kurtosis (MK) values were obtained. Independent-samples t-test or Mann-Whitney U test was used for comparing the differences in IVIM and DKI parameters among different histologic grades and clinical stages. The diagnostic efficacy of IVIM and DKI parameters was evaluated using the receiver operating characteristic (ROC) curve. Spearman's correlation analysis was used to separately analyze the correlation of each parameter with histologic grades and stages of ccRCC. Results The D and MD values were significantly higher in low-grade ccRCC than high-grade ccRCC (all p < 0.001) and in low-stage than high-stage ccRCC (all p < 0.05), and the f value of high-stage ccRCC was lower than that of low-stage ccRCC (p = 0.007). The KA and MK values were significantly higher in low-grade than high-grade ccRCC (p = 0.000 and 0.000, respectively) and in low-stage than high-stage ccRCC (p = 0.000 and 0.000, respectively). The area under the curve (AUC) values of D, D*, f, MD, KA, MK, DKI, and IVIM+DKI values were 0.825, 0.598, 0.626, 0.792, 0.750, 0.754, 0.803, and 0.857, respectively, in grading ccRCC and 0.837, 0.719, 0.710, 0.787, 0.796, 0.784, 0.864, 0.823, and 0.916, respectively, in staging ccRCC. The AUC of IVIM was 0.913 in staging ccRCC. The D, D*, and MD values were negatively correlated with the histologic grades and clinical stages (all p < 0.05), and the KA and MK values showed a positive correlation with histologic grades and clinical stages (all p < 0.05). The f value was also negatively correlated with the ccRCC clinical stage (p = 0.008). Conclusion Both the IVIM and DKI values can be used preoperatively to predict the degree of histologic grades and stages in ccRCC, and the D and MD values have better diagnostic performance in the grading and staging. Also, further slightly enhanced diagnostic efficacy was observed in the model with combined IVIM and DKI parameters.
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Affiliation(s)
- QiChao Cheng
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - AnLi Ren
- Department of Radiology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - XingHua Xu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Zhao Meng
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Xue Feng
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | | | | | - DeXin Yu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
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Qin Y, Chen C, Chen H, Gao F. The value of intravoxel incoherent motion model-based diffusion-weighted imaging for predicting long-term outcomes in nasopharyngeal carcinoma. Front Oncol 2022; 12:902819. [DOI: 10.3389/fonc.2022.902819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 11/03/2022] [Indexed: 12/04/2022] Open
Abstract
ObjectiveThe aim of this study was to evaluate the prognostic value for survival of parameters derived from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in patients with nasopharyngeal carcinoma (NPC).MaterialsBaseline IVIM-DWI was performed on 97 newly diagnosed NPC patients in this prospective study. The relationships between the pretreatment IVIM-DWI parametric values (apparent diffusion coefficient (ADC), D, D*, and f) of the primary tumors and the patients’ 3-year survival were analyzed in 97 NPC patients who received chemoradiotherapy. The cutoff values of IVIM parameters for local relapse-free survival (LRFS) were identified by a non-parametric log-rank test. The local-regional relapse-free survival (LRRFS), LRFS, regional relapse-free survival (RRFS), distant metastasis-free survival (DMFS), progression-free survival (PFS), and overall survival (OS) rates were calculated by using the Kaplan–Meier method. A Cox proportional hazards model was used to explore the independent predictors for prognosis.ResultsThere were 97 participants (mean age, 48.4 ± 10.5 years; 65 men) analyzed. Non-parametric log-rank test results showed that the optimal cutoff values of ADC, D, D*, and f were 0.897 × 10−3 mm2/s, 0.699 × 10−3 mm2/s, 8.71 × 10−3 mm2/s, and 0.198%, respectively. According to the univariable analysis, the higher ADC group demonstrated significantly higher OS rates than the low ADC group (p = 0.036), the higher D group showed significantly higher LRFS and OS rates than the low D group (p = 0.028 and p = 0.017, respectively), and the higher D* group exhibited significantly higher LRFS and OS rates than the lower D* group (p = 0.001 and p = 0.002, respectively). Multivariable analyses indicated that ADC and D were the independent prognostic factors for LRFS (p = 0.041 and p = 0.037, respectively), D was an independent prognostic factor for LRRFS (p = 0.045), D* and f were the independent prognostic factors for OS (p = 0.019 and 0.029, respectively), and f acted was an independent prognostic factor for DMFS (p = 0.020).ConclusionsBaseline IVIM-DWI perfusion parameters ADC and D, together with diffusion parameter D*, could act as useful factors for predicting long-term outcomes and selecting high-risk patients with NPC.
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Yang H, Ge X, Zheng X, Li X, Li J, Liu M, Zhu J, Qin J. Predicting Grade of Esophageal Squamous Carcinoma: Can Stretched Exponential Model-Based DWI Perform Better Than Bi-Exponential and Mono-Exponential Model? Front Oncol 2022; 12:904625. [PMID: 35912203 PMCID: PMC9329622 DOI: 10.3389/fonc.2022.904625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Background To evaluate and compare the potential performance of various diffusion parameters obtained from mono-exponential model (MEM)-, bi-exponential model (BEM)-, and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in grading of esophageal squamous carcinoma (ESC). Methods Eighty-two patients with pathologically confirmed ESC without treatment underwent multi-b-value DWI scan with 13 b values (0~12,00 s/mm2). The apparent diffusion coefficient (ADC) deriving from the MEM; the pure molecular diffusion (ADCslow), pseudo-diffusion coefficient (ADCfast), perfusion, and fraction (f) deriving from the BEM; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) deriving from the SEM were calculated and compared between poorly differentiated and well/moderately differentiated ESC, respectively. The prediction parameters and diagnostic efficiency were compared by drawing receiver operating characteristic (ROC) curves. Results The ADC, ADCslow, ADCfast, and DDC in poorly ESC were significantly lower than those in well/moderately differentiated ones. By using only one parameter, ADCslow, DDC had the moderate diagnostic efficiency and the areas under the curve (AUC) were 0.758 and 0.813 in differentiating ESC. The DDC had the maximum AUC with sensitivity (88.00%) and specificity (68.42%). Combining ADC with ADCfast, ADCslow, and DDC and combining ADCslow with ADCfast can provide a higher diagnostic accuracy with AUC ranging from 0.756, 0.771, 0.816, and 0.793, respectively. Conclusion Various parameters derived from different DWI models including MEM, BEM, and SEM were potentially helpful in grading ESC. DDC obtained from SEM was the most promising diffusion parameter for predicting the grade of ESC.
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Affiliation(s)
- Hui Yang
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
| | - Xubo Ge
- Department of Radiology, The Fourth People’s Hospital of Taian, Tai’an, China
| | - Xiuzhu Zheng
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
| | - Xiaoqian Li
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
| | - Jiang Li
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
| | - Min Liu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
| | - Jianzhong Zhu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
| | - Jian Qin
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai’an, China
- *Correspondence: Jian Qin,
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Liu N, Yang X, Lei L, Pan K, Liu Q, Huang X. Intravoxel Incoherent Motion Model in Differentiating the Pathological Grades of Esophageal Carcinoma: Comparison of Mono-Exponential and Bi-Exponential Fit Model. Front Oncol 2021; 11:625891. [PMID: 33912449 PMCID: PMC8071935 DOI: 10.3389/fonc.2021.625891] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 03/15/2021] [Indexed: 02/03/2023] Open
Abstract
PURPOSE To compare the diagnostic efficiency of the mono-exponential model and bi-exponential model deriving from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating the pathological grade of esophageal squamous cell carcinoma (ESCC). METHODS Fifty-four patients with ESCC were divided into three groups of poorly-differentiated (PD), moderately-differentiated (MD), and well-differentiated (WD), and underwent the IVIM-DWI scan. Mono-exponential (Dmono, D*mono, and fmono) and bi-exponential fit parameters (Dbi, D*bi, and fbi) were calculated using the IVIM data for the tumors. Mean parameter values of three groups were compared using a one-way ANOVA followed by post hoc tests. The receiver operating characteristic curve was drawn for differentiating pathological grade of ESCC. Correlations between pathological grades and IVIM parameters were analyzed. RESULTS There were significant differences in fmono and fbi among the PD, MD and WD ESCC groups (all p<0.05). The fmono were 0.32 ± 0.07, 0.23 ± 0.08, and 0.16 ± 0.05, respectively, and the fbi were 0.35 ± 0.08, 0.26 ± 0.10, and 0.18 ± 0.07, respectively. There was a significant difference in the Dmono between the WD and the PD group (1.48 ± 0.51* 10-3 mm2/s versus 1.05 ± 0.44*10-3 mm2/s, p<0.05), but there was no significant difference between the WD and MD groups, MD and PD groups (all p>0.05). The D*mono, Dbi, and D*bi showed no significant difference among the three groups (all p>0.05). The area under the curve (AUC) of Dmono, fmono and fbi in differentiating WD from PD ESCC were 0.764, 0.961 and 0.932, and the sensitivity and specificity were 92.9% and 60%, 92.9% and 90%, 85.7% and 100%, respectively. The AUC of fmono and fbi in differentiating MD from PD ESCC were 0.839 and 0.757, and the sensitivity and specificity were 78.6% and 80%, 85.7% and 70%, respectively. The AUC of fmono and fbi in differentiating MD from WD ESCC were 0.746 and 0.740, and the sensitivity and specificity were 65% and 85%, 80% and 60%, respectively. The pathologically differentiated grade was correlated with all IVIM parameters (all p<0.05). CONCLUSIONS The mono-exponential IVIM model is superior to the bi-exponential IVIM model in differentiating pathological grades of ESCC, which may be a promising imaging method to predict pathological grades of ESCC.
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Affiliation(s)
- Nian Liu
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xiongxiong Yang
- Department of Radiology, Nanchong Hospital of Traditional Chinese Medicine, Nanchong, China
| | - Lixing Lei
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Ke Pan
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Qianqian Liu
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xiaohua Huang
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
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Lee SL, Yadav P, Starekova J, Christensen L, Chandereng T, Chappell R, Reeder SB, Bassetti MF. Diagnostic Performance of MRI for Esophageal Carcinoma: A Systematic Review and Meta-Analysis. Radiology 2021; 299:583-594. [PMID: 33787334 DOI: 10.1148/radiol.2021202857] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Background Although CT, endoscopic US, and PET are critical in determining the appropriate management of esophageal carcinoma (squamous cell carcinoma and adenocarcinoma), previous reports show that staging accuracy remains low, particularly for nodal involvement sensitivity. Purpose To perform a systematic review and meta-analysis to determine the diagnostic performance of MRI for multiple staging thresholds in patients with biopsy-proven esophageal carcinoma (differentiation of stage T0 disease from stage T1 or higher disease, differentiation of stage T2 or lower disease from stage T3 or higher disease, and differentiation of stage N0 disease from stage N1 or higher disease [where T refers to tumor stage and N refers to nodal stage]). Materials and Methods Studies of the diagnostic performance of MRI in determining the stage of esophageal carcinoma in patients before esophagectomy and pathologic staging between 2000 and 2019 were searched in PubMed, Scopus, Web of Science, and Cochrane Library by a librarian and radiation oncologist. Pooled diagnostic performance of MRI was calculated with a bivariate random effects model. Bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (version 2) tool. Results Twenty studies with a total of 984 patients were included in the analysis. Pooled accuracy for stage T0 versus stage T1 or higher had a sensitivity of 92% (95% CI: 82, 96) and a specificity of 67% (95% CI: 51, 81). Pooled accuracy for stage T2 or lower versus stage T3 or higher had a sensitivity of 86% (95% CI: 76, 92) and a specificity of 86% (95% CI: 75, 93). Pooled accuracy for stage N0 versus stage N1 or higher had a sensitivity of 71% (95% CI: 60, 80) and a specificity of 72% (95% CI: 64, 79). The concern for applicability was low for the patient selection, index test, and reference test domains, except for 10% of studies (two of 20) that had unclear concern for patient selection applicability. Conclusion MRI has high sensitivity but low specificity for the detection of esophageal carcinoma, which shows promise for determining neoadjuvant therapy response and for detecting locally advanced disease for potential trimodality therapy. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Leeflang in this issue.
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Affiliation(s)
- Sangjune Laurence Lee
- From the Department of Oncology, Division of Radiation Oncology, University of Calgary, 1331 29 St NW, Calgary, AB, Canada T2N 4N2 (S.L.L.); Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.L.L., P.Y., M.F.B.); Department of Radiology, University of Wisconsin-Madison, Madison, Wis (J.S., S.B.R.); Departments of Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wis (S.B.R); University of Wisconsin School of Medicine and Public Health, Madison, Wis (L.C.); Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wis (T.C., R.C.)
| | - Poonam Yadav
- From the Department of Oncology, Division of Radiation Oncology, University of Calgary, 1331 29 St NW, Calgary, AB, Canada T2N 4N2 (S.L.L.); Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.L.L., P.Y., M.F.B.); Department of Radiology, University of Wisconsin-Madison, Madison, Wis (J.S., S.B.R.); Departments of Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wis (S.B.R); University of Wisconsin School of Medicine and Public Health, Madison, Wis (L.C.); Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wis (T.C., R.C.)
| | - Jitka Starekova
- From the Department of Oncology, Division of Radiation Oncology, University of Calgary, 1331 29 St NW, Calgary, AB, Canada T2N 4N2 (S.L.L.); Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.L.L., P.Y., M.F.B.); Department of Radiology, University of Wisconsin-Madison, Madison, Wis (J.S., S.B.R.); Departments of Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wis (S.B.R); University of Wisconsin School of Medicine and Public Health, Madison, Wis (L.C.); Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wis (T.C., R.C.)
| | - Leslie Christensen
- From the Department of Oncology, Division of Radiation Oncology, University of Calgary, 1331 29 St NW, Calgary, AB, Canada T2N 4N2 (S.L.L.); Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.L.L., P.Y., M.F.B.); Department of Radiology, University of Wisconsin-Madison, Madison, Wis (J.S., S.B.R.); Departments of Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wis (S.B.R); University of Wisconsin School of Medicine and Public Health, Madison, Wis (L.C.); Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wis (T.C., R.C.)
| | - Thevaa Chandereng
- From the Department of Oncology, Division of Radiation Oncology, University of Calgary, 1331 29 St NW, Calgary, AB, Canada T2N 4N2 (S.L.L.); Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.L.L., P.Y., M.F.B.); Department of Radiology, University of Wisconsin-Madison, Madison, Wis (J.S., S.B.R.); Departments of Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wis (S.B.R); University of Wisconsin School of Medicine and Public Health, Madison, Wis (L.C.); Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wis (T.C., R.C.)
| | - Richard Chappell
- From the Department of Oncology, Division of Radiation Oncology, University of Calgary, 1331 29 St NW, Calgary, AB, Canada T2N 4N2 (S.L.L.); Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.L.L., P.Y., M.F.B.); Department of Radiology, University of Wisconsin-Madison, Madison, Wis (J.S., S.B.R.); Departments of Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wis (S.B.R); University of Wisconsin School of Medicine and Public Health, Madison, Wis (L.C.); Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wis (T.C., R.C.)
| | - Scott B Reeder
- From the Department of Oncology, Division of Radiation Oncology, University of Calgary, 1331 29 St NW, Calgary, AB, Canada T2N 4N2 (S.L.L.); Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.L.L., P.Y., M.F.B.); Department of Radiology, University of Wisconsin-Madison, Madison, Wis (J.S., S.B.R.); Departments of Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wis (S.B.R); University of Wisconsin School of Medicine and Public Health, Madison, Wis (L.C.); Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wis (T.C., R.C.)
| | - Michael F Bassetti
- From the Department of Oncology, Division of Radiation Oncology, University of Calgary, 1331 29 St NW, Calgary, AB, Canada T2N 4N2 (S.L.L.); Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.L.L., P.Y., M.F.B.); Department of Radiology, University of Wisconsin-Madison, Madison, Wis (J.S., S.B.R.); Departments of Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin-Madison, Madison, Wis (S.B.R); University of Wisconsin School of Medicine and Public Health, Madison, Wis (L.C.); Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wis (T.C., R.C.)
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Chikui T, Tokumori K, Panyarak W, Togao O, Yamashita Y, Kawano S, Kamitani T, Yoshiura K. The application of a gamma distribution model to diffusion-weighted images of the orofacial region. Dentomaxillofac Radiol 2020; 50:20200252. [PMID: 32706975 DOI: 10.1259/dmfr.20200252] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVES This study evaluated the correlation among the diffusion-derived parameters obtained by monoexponential (ME), intravoxel incoherent motion (IVIM) and γ distribution (GD) models and compared these parameters among representative orofacial tumours. METHODS Ninety-two patients who underwent 1.5 T MRI including diffusion-weighted imaging were included. The shape parameter (κ), scale parameter (θ), ratio of the intracellular diffusion (ƒ1), extracellular diffusion (ƒ2) and perfusion (ƒ3) were obtained by the GD model; the true diffusion coefficient (D) and perfusion fraction (f) were obtained by the IVIM model; and the apparent diffusion coefficient (ADC) was obtained by the ME model. RESULTS ƒ1 had a strongly negative correlation with the ADC (ρ = -0.993) and D (ρ = -0.926). A strong positive correlation between f and ƒ3 (ρ = 0.709) was found. Malignant lymphoma (ML) had the highest ƒ1, followed by squamous cell carcinoma (SCC), malignant salivary gland tumours, pleomorphic adenoma (Pleo) and angioma. Both the IVIM and GD models suggested the highest perfusion in angioma and the lowest perfusion in ML. The GD model demonstrated a high extracellular component in Pleo and revealed that the T4a+T4b SCC group had a lower ƒ2 than the T2+T3 SCC group, and poor to moderately differentiated SCC had a higher ƒ1 than highly differentiated SCC. CONCLUSIONS Given the correlation among the diffusion-derived parameters, the GD model might be a good alternative to the IVIM model. Furthermore, the GD model's parameters were useful for characterizing the pathological structure.
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Affiliation(s)
- Toru Chikui
- Department of Oral and Maxillofacial Radiology, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
| | - Kenji Tokumori
- Department of Clinical Radiology, Faculty of Medical Technology, Teikyo University, Tokyo, Japan
| | | | - Osamu Togao
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yasuo Yamashita
- Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan
| | - Shintaro Kawano
- Section of Oral and Maxillofacial Oncology, Division of Maxillofacial Diagnostic and Surgical Sciences, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
| | - Takeshi Kamitani
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kazunori Yoshiura
- Department of Oral and Maxillofacial Radiology, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
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8
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Well L, Salamon J, Kaul MG, Farschtschi S, Herrmann J, Geier KI, Hagel C, Bockhorn M, Bannas P, Adam G, Mautner VF, Derlin T. Differentiation of peripheral nerve sheath tumors in patients with neurofibromatosis type 1 using diffusion-weighted magnetic resonance imaging. Neuro Oncol 2020; 21:508-516. [PMID: 30496452 DOI: 10.1093/neuonc/noy199] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND We sought to determine the value of diffusion-weighted (DW) magnetic resonance imaging (MRI) for characterization of benign and malignant peripheral nerve sheath tumors (PNSTs) in patients with neurofibromatosis type 1 (NF1). METHODS Twenty-six patients with NF1 and suspicion of malignant transformation of PNSTs were prospectively enrolled and underwent DW MRI at 3T. For a set of benign (n = 55) and malignant (n = 12) PNSTs, functional MRI parameters were derived from both biexponential intravoxel incoherent motion (diffusion coefficient D and perfusion fraction f) and monoexponential data analysis (apparent diffusion coefficients [ADCs]). A panel of morphological MRI features was evaluated using T1- and T2-weighted imaging. Mann-Whitney U-test, Fisher's exact test, and receiver operating characteristic (ROC) analyses were applied to assess the diagnostic accuracy of quantitative and qualitative MRI. Cohen's kappa was used to determine interrater reliability. RESULTS Malignant PNSTs demonstrated significantly lower diffusivity (P < 0.0001) compared with benign PNSTs. The perfusion fraction f was significantly higher in malignant PNSTs (P < 0.001). In ROC analysis, functional MRI parameters showed high diagnostic accuracy for differentiation of PNSTs (eg, ADCmean, 92% sensitivity with 98% specificity, AUC 0.98; Dmean, 92% sensitivity with 98% specificity, AUC 0.98). By contrast, morphological imaging features had only limited sensitivity (18-94%) and specificity (18-82%) for identification of malignancy. Interrater reliability was higher for monoexponential data analysis. CONCLUSION DW imaging shows better diagnostic performance than morphological features and allows accurate differentiation of benign and malignant peripheral nerve sheath tumors in NF1.
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Affiliation(s)
- Lennart Well
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Johannes Salamon
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Michael G Kaul
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Said Farschtschi
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jochen Herrmann
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Karin I Geier
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Hagel
- Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maximilian Bockhorn
- Department of General, Visceral, and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Peter Bannas
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gerhard Adam
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Victor F Mautner
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thorsten Derlin
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany
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9
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Basirjafari S, Poureisa M, Shahhoseini B, Zarei M, Aghayari Sheikh Neshin S, Anvari Aria S, Nouri-Vaskeh M. Apparent diffusion coefficient values and non-homogeneity of diffusion in brain tumors in diffusion-weighted MRI. Acta Radiol 2020; 61:244-252. [PMID: 31264441 DOI: 10.1177/0284185119856887] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Background The values that have been received from apparent diffusion coefficient (ADC) maps of diffusion-weighted magnetic resonance imaging (DW-MRI) might play a vital role in evaluating tumors and their grading scale. Purpose To investigate the predictive role of this heterogeneity in brain tumor pathologies and its correlation with Ki-67. Material and Methods A total of 124 patients with brain tumors underwent brain MRI with gadolinium injection. ADC and standard deviation of each lesion have been obtained from manual localization of the region of interest on the ADC map. A receiver operating characteristic analysis was conducted to determine the minimum cut-off values of the mean ADC and mean standard deviation of ADC maps having the highest sensitivity and specificity to differentiate high-grade and low-grade tumors. Results Mean ADC values in the region of interest were significantly lower for malignant tumors (grade IV and metastasis) than grade I brain tumors, while a higher mean standard deviation was observed. In a more detailed comparison of tumor groups, the mean standard deviation of the ADC for glioblastoma multiform was significantly higher than meningioma grade I ( P < 0.001) and metastasis was significantly higher than grade III and IV astrocytic tumors ( P = 0.004). The analysis of Ki-67 proliferation index and mean ADC values in gliomas showed a significant inverse correlation between the parameters (r = –0.0429, P < 0.001) and direct correlation between Ki-67 and mean standard deviation of the ADC (r = 0.551, P < 0.001). As an index for the ADC to differentiate high-grade and low-grade tumors, the cut-off values of 1.40*10−3 mm2/s for mean ADC and 45*10−3 mm2/s for mean standard deviation have the highest combination of sensitivity, specificity, and area under the curve. Conclusion The mean value and standard deviation of the ADC could be considered for differentiating between low-grade and high-grade brain tumors, as two available non-invasive methods.
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Affiliation(s)
| | - Masoud Poureisa
- Department of Radiology, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Babak Shahhoseini
- Imam Khomeini Hospital, North Khorasan University of Medical Sciences, Shirvan, Iran
| | - Mohammad Zarei
- Department of Pharmacology, Toxicology and Therapeutic Chemistry, Faculty of Pharmacy, University of Barcelona, Barcelona, Spain
- Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Spain
| | | | - Sheida Anvari Aria
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Masoud Nouri-Vaskeh
- Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran
- Connective Tissue Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
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10
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Zhang YH, Fischer MA, Lehmann H, Johnsson Å, Rouvelas I, Herlin G, Lundell L, Brismar TB. Computed tomography volumetry of esophageal cancer - the role of semiautomatic assessment. BMC Med Imaging 2019; 19:17. [PMID: 30767773 PMCID: PMC6377716 DOI: 10.1186/s12880-019-0317-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Accepted: 01/28/2019] [Indexed: 01/16/2023] Open
Abstract
Background The clinical and research value of Computed Tomography (CT) volumetry of esophageal cancer tumor size remains controversial. Development in CT technique and image analysis has made CT volumetry less cumbersome and it has gained renewed attention. The aim of this study was to assess esophageal tumor volume by semi-automatic measurements as compared to manual. Methods A total of 23 esophageal cancer patients (median age 65, range 51–71), undergoing CT in the portal-venous phase for tumor staging, were retrospectively included between 2007 and 2012. One radiology resident and one consultant radiologist measured the tumor volume by semiautomatic segmentation and manual segmentation. Reproducibility of the respective measurements was assessed by intraclass correlation coefficients (ICC) and by average deviation from mean. Results Mean tumor volume was 46 ml (range 5-137 ml) using manual segmentation and 42 ml (range 3-111 ml) using semiautomatic segmentation. Semiautomatic measurement provided better inter-observer agreement than traditional manual segmentation. The ICC was significantly higher for semiautomatic segmentation in comparison to manual segmentation (0.86, 0.56, p < 0.01). The average absolute percentage difference from mean was reduced from 24 to 14% (p < 0.001) when using semiautomatic segmentation. Conclusions Semiautomatic analysis outperforms manual analysis for assessment of esophageal tumor volume, improving reproducibility.
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Affiliation(s)
- Yi-Hua Zhang
- Department of Diagnostic Radiology and Karolinska Institutet, Karolinska University Hospital, CLINTEC, Stockholm, Sweden. .,Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology, Karolinska University Hospital, Huddinge, 141 86, Stockholm, Sweden.
| | - Michael A Fischer
- Department of Diagnostic Radiology and Karolinska Institutet, Karolinska University Hospital, CLINTEC, Stockholm, Sweden
| | - Henrik Lehmann
- Department of Diagnostic Radiology and Karolinska Institutet, Karolinska University Hospital, CLINTEC, Stockholm, Sweden
| | - Åse Johnsson
- Department of Radiology, Institute of Clinical Sciences, The Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.,Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Ioannis Rouvelas
- Department of Surgery, Centre for Digestive Diseases and Karolinska Institutet, Karolinska University Hospital, CLINTEC, Stockholm, Sweden
| | - Gunnar Herlin
- Department of Diagnostic Radiology and Karolinska Institutet, Karolinska University Hospital, CLINTEC, Stockholm, Sweden
| | - Lars Lundell
- Department of Surgery, Centre for Digestive Diseases and Karolinska Institutet, Karolinska University Hospital, CLINTEC, Stockholm, Sweden
| | - Torkel B Brismar
- Department of Diagnostic Radiology and Karolinska Institutet, Karolinska University Hospital, CLINTEC, Stockholm, Sweden
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