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Zhou M, Huang H, Fan Y, Chen M, Wang Y, Gao F. Golden-angle radial sparse parallel magnetic resonance imaging of rectal perfusion: utility in the diagnosis of poorly differentiated rectal cancer. Quant Imaging Med Surg 2023; 13:4826-4838. [PMID: 37581054 PMCID: PMC10423373 DOI: 10.21037/qims-22-1244] [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: 11/09/2022] [Accepted: 06/09/2023] [Indexed: 08/16/2023]
Abstract
Background The objective of this retrospective investigation is to evaluate the diagnostic efficacy of a dual-parameter strategy that integrates either time-resolved angiography with stochastic trajectories (TWIST) or golden-angle radial sparse parallel (GRASP)-derived dynamic contrast agent-enhanced magnetic resonance imaging (DCE-MRI) with diffusion-weighted imaging (DWI) for the identification of poorly differentiated rectal cancer (RC). The purpose of this investigation is to contrast the aforementioned methodology with conventional single-factor assessments that rely solely on DWI, and ascertain its comparative efficacy. Methods This study was not registered on a clinical trial platform. Consecutive individuals diagnosed with non-mucinous rectal adenocarcinoma through endoscopy-guided biopsy between December 2020 and October 2022 were involved in our study. These patients had also undergone DCE-MRI and DWI. The perfusion metrics of influx forward volume transfer constant (Ktrans) and rate constant (Kep), along with the apparent diffusion coefficient (ADC), were quantified by a pair of investigators. The study compared the area under the curve (AUC) of the receiver operating characteristic (ROC) for both sequences to identify poorly differentiated RC. The investigation incorporated patients who fulfilled the specified criteria. The inclusion criteria for the investigation were as follows: (I) a diagnosis of RC proved through pathological examination, either via endoscopically-guided biopsy or surgical resection; (II) availability of complete MRI images; (III) absence of any prior history of neoadjuvant chemoradiotherapy during the MRI scan. Results Our investigation comprised a total of 179 participants. Compared to diffusion parameter alone, an integrated assessment of diffusion parameter (ADC) and perfusion parameters (Ktrans or Kep) obtained with GRASP leads to a superior diagnostic accuracy (AUC, 0.97±0.02 vs. 0.89±0.03, 0.97±0.02 vs. 0.89±0.03, P=0.005 and 0.003, respectively); however, there was no additional benefit from ADC with perfusion parameters obtained from TWIST (Ktrans or Kep) (AUC, 0.93±0.04 vs. 0.89±0.03, 0.93±0.03 vs. 0.89±0.03; P= 0.955 and 0.981, respectively, for the integration of ADC with Ktrans and Kep). Conclusions By integrating diffusion and perfusion features into a dual-parameter model, the GRASP method enhances the diagnostic efficacy of MRI in discriminating RCs with poor differentiation. Conversely, the TWIST approach did not yield the aforementioned outcome.
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Affiliation(s)
- Mi Zhou
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongyun Huang
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Yingying Fan
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Meining Chen
- Department of MR Scientific Marketing, Siemens Healthineers, Shanghai, China
| | - Yuting Wang
- Department of Radiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Fabao Gao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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Fan Y, Chen M, Huang H, Zhou M. Predicting lymphovascular invasion in rectal cancer: evaluating the performance of golden-angle radial sparse parallel MRI for rectal perfusion assessment. Sci Rep 2023; 13:8453. [PMID: 37231115 DOI: 10.1038/s41598-023-35763-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 05/23/2023] [Indexed: 05/27/2023] Open
Abstract
This study aims to determine whether the dual-parameter approach combined with either time-resolved angiography with stochastic trajectories (TWIST) or golden-angle radial sparse parallel (GRASP) and diffusion-weighted imaging (DWI) has superior diagnostic performance in predicting pathological lymphovascular invasion (pLVI) rectal cancer when compared with traditional single-parameter evaluations using DWI alone. Patients with pathologically confirmed rectal cancer were enrolled. Perfusion (influx forward volume transfer constant [Ktrans] and rate constant [Kep]) and apparent diffusion coefficient (ADC) were measured by two researchers. For both sequences, areas under receiver operating characteristic (ROCs) to predict pLVI-positive rectal cancer were compared. A total of 179 patients were enrolled in our study. A combined analysis of ADC and perfusion parameters (Ktrans) acquired with GRASP yielded a higher diagnostic performance compared with diffusion parameters alone (area under the curve, 0.91 ± 0.03 vs. 0.71 ± 0.06, P < 0.001); However, ADC with GRASP-acquired Kep and ADC with TWIST-acquired perfusion parameters (Ktrans or Kep) did not offer any additional benefit. The Ktrans of the GRASP technique improved the diagnostic performance of multiparametric MRI to predict rectal cancers with pLVI-positive. In contrast, TWIST did not achieve this effect.
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Affiliation(s)
- Yingying Fan
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No.32, West Second Section of First Ring Road, Qingyang District, Chengdu, 610072, People's Republic of China
| | - Meining Chen
- MR Scientific Marketing, Siemens Healthineers, Shanghai, China
| | - Hongyun Huang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No.32, West Second Section of First Ring Road, Qingyang District, Chengdu, 610072, People's Republic of China
| | - Mi Zhou
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No.32, West Second Section of First Ring Road, Qingyang District, Chengdu, 610072, People's Republic of China.
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Liu ZW, Chen G, Dong CF, Qiu WR, Zhang SH. Intelligent assistant diagnosis for pediatric inguinal hernia based on a multilayer and unbalanced classification model. Front Physiol 2023; 14:1105891. [PMID: 36998990 PMCID: PMC10043203 DOI: 10.3389/fphys.2023.1105891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 02/27/2023] [Indexed: 03/17/2023] Open
Abstract
As one of the most common diseases in pediatric surgery, an inguinal hernia is usually diagnosed by medical experts based on clinical data collected from magnetic resonance imaging (MRI), computed tomography (CT), or B-ultrasound. The parameters of blood routine examination, such as white blood cell count and platelet count, are often used as diagnostic indicators of intestinal necrosis. Based on the medical numerical data on blood routine examination parameters and liver and kidney function parameters, this paper used machine learning algorithm to assist the diagnosis of intestinal necrosis in children with inguinal hernia before operation. In the work, we used clinical data consisting of 3,807 children with inguinal hernia symptoms and 170 children with intestinal necrosis and perforation caused by the disease. Three different models were constructed according to the blood routine examination and liver and kidney function. Some missing values were replaced by using the RIN-3M (median, mean, or mode region random interpolation) method according to the actual necessity, and the ensemble learning based on the voting principle was used to deal with the imbalanced datasets. The model trained after feature selection yielded satisfactory results with an accuracy of 86.43%, sensitivity of 84.34%, specificity of 96.89%, and AUC value of 0.91. Therefore, the proposed methods may be a potential idea for auxiliary diagnosis of inguinal hernia in children.
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Affiliation(s)
- Zhi-Wen Liu
- Department of General Surgery, Jiangxi Provincial Children’s Hospital, Nanchang, China
| | - Gang Chen
- Computer Department, Jing-De-Zhen Jingdezhen Ceramic Institute, Jingdezhen, China
| | - Chao-Fan Dong
- Department of General Surgery, Jingdezhen No. 1 People’s Hospital, Jingdezhen, China
| | - Wang-Ren Qiu
- Computer Department, Jing-De-Zhen Jingdezhen Ceramic Institute, Jingdezhen, China
- *Correspondence: Wang-Ren Qiu, , ; Shou-Hua Zhang,
| | - Shou-Hua Zhang
- Department of General Surgery, Jiangxi Provincial Children’s Hospital, Nanchang, China
- *Correspondence: Wang-Ren Qiu, , ; Shou-Hua Zhang,
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Tong P, Sun D, Chen G, Ni J, Li Y. Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer. BMC Cancer 2023; 23:61. [PMID: 36650498 PMCID: PMC9847040 DOI: 10.1186/s12885-023-10534-w] [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: 10/04/2022] [Accepted: 01/09/2023] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Preoperative assessment of lymphovascular invasion(LVI) of rectal cancer has very important clinical significance. However, accurate preoperative imaging evaluation of LVI is highly challenging because the resolution of MRI is still limited. Relatively few studies have focused on prediction of LVI of rectal cancer with the tool of radiomics, especially in patients with negative statue of MRI-based extramural vascular invasion (mrEMVI).The purpose of this study was to explore the preoperative predictive value of biparametric MRI-based radiomics features for LVI of rectal cancer in patients with the negative statue of mrEMVI. METHODS The data of 146 cases of rectal adenocarcinoma confirmed by postoperative pathology were retrospectively collected. In the cases, 38 had positive status of LVI. All patients were examined by MRI before the operation. The biparametric MRI protocols included T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI). We used whole-volume three-dimensional method and two feature selection methods, minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO), to extract and select the features. Logistics regression was used to construct models. The area under the receiver operating characteristic curve (AUC) and DeLong's test were used to evaluate the diagnostic performance of the radiomics based on T2WI and DWI and the combined models. RESULTS Radiomics models based on T2WI and DWI had good predictive performance for LVI of rectal cancer in both the training cohort and the validation cohort. The AUCs of the T2WI model were 0.87 and 0.87, and the AUCs of the DWI model were 0.94 and 0.92. The combined model was better than the T2WI model, with AUCs of 0.97 and 0.95. The predictive performance of the DWI model was comparable to that of the combined model. CONCLUSIONS The radiomics model based on biparametric MRI, especially DWI, had good predictive value for LVI of rectal cancer. This model has the potential to facilitate the clinical recognition of LVI in rectal cancer preoperatively.
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Affiliation(s)
- Pengfei Tong
- grid.258151.a0000 0001 0708 1323Department of Radiology, Jiangnan University Medical Center, Wuxi, 214000 Jiangsu China
| | - Danqi Sun
- grid.429222.d0000 0004 1798 0228Department of Radiology, the First Affiliated Hospital of Soochow University, Suzhou, 215006 Jiangsu China
| | - Guangqiang Chen
- grid.452666.50000 0004 1762 8363Department of Radiology, the Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu China
| | - Jianming Ni
- grid.258151.a0000 0001 0708 1323Department of Radiology, Jiangnan University Medical Center, Wuxi, 214000 Jiangsu China
| | - Yonggang Li
- grid.429222.d0000 0004 1798 0228Department of Radiology, the First Affiliated Hospital of Soochow University, Suzhou, 215006 Jiangsu China
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Jin J, Zhou H, Sun S, Tian Z, Ren H, Feng J, Jiang X. Machine learning based gray-level co-occurrence matrix early warning system enables accurate detection of colorectal cancer pelvic bone metastases on MRI. Front Oncol 2023; 13:1121594. [PMID: 37035167 PMCID: PMC10073745 DOI: 10.3389/fonc.2023.1121594] [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: 12/16/2022] [Accepted: 03/02/2023] [Indexed: 04/11/2023] Open
Abstract
Objective The mortality of colorectal cancer patients with pelvic bone metastasis is imminent, and timely diagnosis and intervention to improve the prognosis is particularly important. Therefore, this study aimed to build a bone metastasis prediction model based on Gray level Co-occurrence Matrix (GLCM) - based Score to guide clinical diagnosis and treatment. Methods We retrospectively included 614 patients with colorectal cancer who underwent pelvic multiparameter magnetic resonance image(MRI) from January 2015 to January 2022 in the gastrointestinal surgery department of Gezhouba Central Hospital of Sinopharm. GLCM-based Score and Machine learning algorithm, that is,artificial neural net7work model(ANNM), random forest model(RFM), decision tree model(DTM) and support vector machine model(SVMM) were used to build prediction model of bone metastasis in colorectal cancer patients. The effectiveness evaluation of each model mainly included decision curve analysis(DCA), area under the receiver operating characteristic (AUROC) curve and clinical influence curve(CIC). Results We captured fourteen categories of radiomics data based on GLCM for variable screening of bone metastasis prediction models. Among them, Haralick_90, IV_0, IG_90, Haralick_30, CSV, Entropy and Haralick_45 were significantly related to the risk of bone metastasis, and were listed as candidate variables of machine learning prediction models. Among them, the prediction efficiency of RFM in combination with Haralick_90, Haralick_all, IV_0, IG_90, IG_0, Haralick_30, CSV, Entropy and Haralick_45 in training set and internal verification set was [AUC: 0.926,95% CI: 0.873-0.979] and [AUC: 0.919,95% CI: 0.868-0.970] respectively. The prediction efficiency of the other four types of prediction models was between [AUC: 0.716,95% CI: 0.663-0.769] and [AUC: 0.912,95% CI: 0.859-0.965]. Conclusion The automatic segmentation model based on diffusion-weighted imaging(DWI) using depth learning method can accurately segment the pelvic bone structure, and the subsequently established radiomics model can effectively detect bone metastases within the pelvic scope, especially the RFM algorithm, which can provide a new method for automatically evaluating the pelvic bone turnover of colorectal cancer patients.
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EL Sayed FM, Nassef EM, Abdelmageed NA, Abdel Maqsoud RR, Abosaif AI. Diffusion-Weighted MRI as Non-Invasive Diagnostic Tool for Rectal Cancer Aggressiveness and Correlation with KI-67 Expression in Tumor Tissue. Asian Pac J Cancer Prev 2022; 23:3387-3391. [PMID: 36308363 PMCID: PMC9924338 DOI: 10.31557/apjcp.2022.23.10.3387] [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: 05/08/2022] [Indexed: 02/18/2023] Open
Abstract
BACKGROUND AND AIM Apparent diffusion coefficient (ADC) was suggested as a prognostic marker in rectal carcinoma (RC). However, reported data are inconsistent. The present study aimed to assess the relation between ADC value and Ki-67 expression index and other pathological parameters in Egyptian RC patients. MATERIALS AND METHODS The study included 39 patients with newly diagnosed RC (non-mucinous adenocarcinoma). All patients underwent magnetic resonance imaging (MRI) scan by 1.5T magnet. Mean ADC value was calculated. Pathological features were assessed and Ki- 67 immunohistochemical expression was applied as a proliferative index (PI) biomarker. RESULTS It was shown that patients with T4 tumors had significantly lower ADC values when compared with patients with T2 and T3 (0.903 ± 0.24 versus 1.157 ± 0.31 and 0.971 ± 0.26 respectively, p<0.001). Also, patients with circumferential resection margin (CRM) involvement had significantly lower ADC values when compared with patients without (0.905 ± 0.24 versus 1.109 ± 0.30, p=0.036). Patients with T4 tumors expressed significantly higher ki-67 PI when compared with patients with T2 and T3 tumors (75.71 ± 5.14 versus 46.25 ± 5.18 and 75.71 ± 5.14 respectively, p<0.001). Pearson's correlation coefficient identified a significant inverse correlation between ADC values and ki-67 PI (r=-367, p=0.027). CONCLUSION ADC values of RC may reflect tumor staging and Ki-67 is closely related to the ADC value confirm this result.
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Affiliation(s)
- Fadila Mamdouh EL Sayed
- Department of Radiodiagnosis, Faculty of Medicine For Girl, Al-Azhar University, Cairo, Egypt.
| | - Eman Mostafa Nassef
- Department of Internal Medicine, Faculty of Medicine for Girls, Al-Azhar University, Cairo, Egypt. ,For Correspondence:
| | - Neamat Abdelmageed Abdelmageed
- Department of Hepatogastroenterology and Infectious Diseases, Faculty of Medicine for Girls, Al-Azhar University, Cairo, Egypt.
| | | | - Amany Ibrahim Abosaif
- Department of Pathology, Faculty of Medicine for Girls, Al-Azhar University, Cairo, Egypt.
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Zhu K, Chen Z, Cui L, Zhao J, Liu Y, Cao J. The Preoperative Diagnostic Performance of Multi-Parametric Quantitative Assessment in Rectal Carcinoma: A Preliminary Study Using Synthetic Magnetic Resonance Imaging. Front Oncol 2022; 12:682003. [PMID: 35707367 PMCID: PMC9190242 DOI: 10.3389/fonc.2022.682003] [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: 03/17/2021] [Accepted: 04/19/2022] [Indexed: 12/24/2022] Open
Abstract
Objective Synthetic MRI (SyMRI) can reconstruct different contrast-weighted images(T1, T2, PD) and has shorter scan time, easier post-processing and better reproducibility. Some studies have shown splendid correlation with conventional mapping techniques and no degradation in the quality of syMRI images compared with conventional MRI. It is crucial to select an individualized treatment plan based on the preoperative images of rectal carcinoma (RC). We tried to explore the feasibility of syMRI on T, N stage and extramural vascular invasion (EMVI) of rectal cancer. Materials and Methods A total of 100 patients (37 females and 63 males) diagnosed with rectal carcinoma were enrolled. All the patients underwent preoperative pelvic MR examinations including conventional MR sequence and synthetic MRI. Two radiologists evaluated the MRI findings of each rectal carcinoma and EMVI score in consensus. The values for T1, T2 relaxation times and PD value were measured in tumor(ROI-1) and pararectal fat space(ROI-2) and analyzed independently. A receiver operating characteristic (ROC) analysis was performed. Correlations between the T1, T2 and PD values and EMVI score were also evaluated. Results Compared with the normal rectal wall, the values of T1 and T2 relaxation times of the tumor were significantly higher (P <0.001). There was no statistically significant difference in the PD value (P >0.05). As for ROI, the ROI of pararectal fat space(ROI-2) had better significance than rectal cancer lesion (ROI-1). T2 value of ROI-1 and T1 value of ROI-2 were higher in the pEMVI positive group than in the negative group (P=0.002 and 0.001) and T1 value of ROI-2 had better performance with an AUC of 0.787, (95% CI:0.693- 0.882). T1 value, T2 value and PD value from ROI-2 were effective for both T and N stage of rectal cancer. High-grade pathological stage had showed higher T1 value (PT stage=0.013,PN stage=0.035), lower T2 value (PT stage=0.025,PN stage=0.034) and lower PD value (PT stage=0.017). We also enrolled the characteristics with P < 0.05 in the combined model which had better diagnostic efficacy. A significant positive correlation was found between the T1 value of pararectal fat space(ROI-2) and EMVI score (r value = 0.519, P<0.001). The T2 value(r=0.213,P=0.049) and PD value(r=0.354,P=0.001) from ROI-1 was correlated with EMVI score. Correlation analysis did not show any significant associations between T2 value of tumor, T2, PD values of pararectal fat space and EMVI scores. Conclusion Synthetic MRI can provide multi-parameter quantitative image maps with a easier measurement and slightly shorter acquisition time compared with conventional MRI. The measurement of multi-parametric quantitative values contributes to diagnosing the tumor and evaluating T stage, N stage and EMVI. It has the potential to be used as a preoperative diagnostic and grading technique in rectal carcinoma.
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Affiliation(s)
- Kexin Zhu
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Zhicheng Chen
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lingling Cui
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jinli Zhao
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yi Liu
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jibin Cao
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
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Zhao Z, Zhou Y, Jiang M, Dang L. Application Value of MRI Combined with MSCT in Diagnosis and Staging of Colon Carcinoma. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:2593844. [PMID: 35651927 PMCID: PMC9150994 DOI: 10.1155/2022/2593844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/12/2022] [Accepted: 04/20/2022] [Indexed: 12/04/2022]
Abstract
Objective To clarify the application value of magnetic resonance imaging (MRI) combined with multislice spiral computed tomography (MSCT) in the diagnosis and staging of colon carcinoma (CC). Methods A total of 103 patients with histopathologically diagnosed CC were enrolled. Patient clinical and imaging data were collected, and MRI and MSCT images were analyzed to assess the accuracy of MRI, MSCT, and their combination in diagnosing tumor (T) staging of CC. Results Among the 103 cases of histopathologically diagnosed CC, 26 cases (25.24) were in stage T1-2, 72 cases (69.90) were in stage T3, and 5 cases (4.85) were in stage T4. The accuracy of MRI in diagnosing stage T1-2, T3, and T4 was 80.77%, 88.89%, and 60.00%, respectively, with an average of 76.55%. The accuracy rates of MSCT in diagnosing T1-2, T3, and T4 stages were 73.08%, 90.27%, and 60.00%, respectively, with an average of 74.45%. The accuracy rates of MRI+MSCT in diagnosing T1-2, T3, and T4 were 88.46%, 95.83%, and 80.00%, respectively, with an average of 88.10%. Conclusions Compared with single use of MRI or MSCT, MRI+MSCT provides accurate imaging data with higher accuracy, which is more helpful for the T-staging evaluation of CC.
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Affiliation(s)
- Zhiwei Zhao
- Medical Imaging Center, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital), Urumqi, 830011 Xinjiang, China
| | - Yong Zhou
- Medical Imaging Center, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital), Urumqi, 830011 Xinjiang, China
| | - Meng Jiang
- Department of Gastroenterology, People's Hospital of Tongchuan, Tongchuan, 727000 Shaanxi, China
| | - Ling Dang
- Department of Gastroenterology, People's Hospital of Tongchuan, Tongchuan, 727000 Shaanxi, China
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Ao W, Zhang X, Yao X, Zhu X, Deng S, Feng J. Preoperative prediction of extramural venous invasion in rectal cancer by dynamic contrast-enhanced and diffusion weighted MRI: a preliminary study. BMC Med Imaging 2022; 22:78. [PMID: 35484509 PMCID: PMC9052632 DOI: 10.1186/s12880-022-00810-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 04/22/2022] [Indexed: 12/29/2022] Open
Abstract
Background To explore the value of the quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in assessing preoperative extramural venous invasion (EMVI) in rectal cancer. Methods Eighty-two rectal adenocarcinoma patients who had underwent MRI preoperatively were enrolled in this study. The differences in quantitative DCE-MRI and DWI parameters including Krans, Kep and ADC values were analyzed between MR-detected EMVI (mrEMVI)-positive and -negative groups. Multivariate logistic regression analysis was performed to build the combined prediction model for pathologic EMVI (pEMVI) with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) curve. Results Of the 82 patients, 24 were mrEMVI-positive and 58 were -negative. In the mrEMVI positive group, the Ktrans and Kep values were significantly higher than those in the mrEMVI negative group (P < 0.01), but the ADC values were significantly lower (P < 0.01). A negative correlation was observed between the Ktrans vs ADC values and Kep vs ADC values in patients with rectal cancer. Among the four quantitative parameters, Ktrans and ADC value were independently associated with mrEMVI by multivariate logistic regression analysis. ROC analysis showed that combined prediction model based on quantitative DCE parameters and ADC values had a good prediction efficiency for pEMVI in rectal cancer. Conclusion The quantitative DCE-MRI parameters, Krans, Kep and ADC values play important role in predicting EMVI of rectal cancer, with Ktrans and ADC value being independent predictors of EMVI in rectal cancer.
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Affiliation(s)
- Weiqun Ao
- Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Xian Zhang
- Departments of Radiology, Zhuji Affiliated Hospital of Shaoxing University, Zhuji People's Hospital, No. 9 Jianmin Road, Zhuji, 311800, Zhejiang Province, China
| | - Xiuzhen Yao
- Department of Ultrasound, Shanghai Putuo District People's Hospital, Shanghai, China
| | - Xiandi Zhu
- Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Shuitang Deng
- Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang Province, China
| | - Jianju Feng
- Departments of Radiology, Zhuji Affiliated Hospital of Shaoxing University, Zhuji People's Hospital, No. 9 Jianmin Road, Zhuji, 311800, Zhejiang Province, China.
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Zhang Y, Peng J, Liu J, Ma Y, Shu Z. Preoperative Prediction of Perineural Invasion Status of Rectal Cancer Based on Radiomics Nomogram of Multiparametric Magnetic Resonance Imaging. Front Oncol 2022; 12:828904. [PMID: 35480114 PMCID: PMC9036372 DOI: 10.3389/fonc.2022.828904] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives To compare the predictive performance of different radiomics signatures from multiparametric magnetic resonance imaging (mpMRI), including four sequences when used individually or combined, and to establish and validate an optimal nomogram for predicting perineural invasion (PNI) in rectal cancer (RC) patients. Methods Our retrospective study included 279 RC patients without preoperative antitumor therapy (194 in the training dataset and 85 in the test dataset) who underwent preoperative mpMRI scan between January 2017 and January 2021. Among them, 72 cases were PNI-positive. Then, clinical and radiological variables were collected, including carcinoembryonic antigen (CEA), radiological tumour stage (T1-4), lymph node stage (N0-2) and so on. Quantitative radiomics features were extracted and selected from oblique axial T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), apparent diffusion coefficient (ADC), and enhanced T1WI (T1CE) sequences. The clinical model was constructed by integrating the final selected clinical and radiological variables. The radiomics signatures included four single-sequence signatures and one fusion signature were built using the respective remaining optimized features. And the nomogram was constructed based on the independent predictors by using multivariable logistic regression. The area under curve (AUC), DeLong test, calibration curve, and decision curve analysis (DCA) were used to evaluate the performance. Results Ultimately, 20 radiomics features were retained from the four sequences—T1WI (n = 4), T2WI (n = 5), ADC (n = 5), and T1CE (n = 6)—to construct four single-sequence radiomics signatures and one fusion radiomics signature. The fusion radiomics signature performed better than four single-sequence radiomics signatures and clinical model (AUCs of 0.835 and 0.773 vs. 0.680-0.737 and 0.666-0.709 in the training and test datasets, respectively). The nomogram constructed by incorporating CEA, tumour stage and rad-score performed best, with AUCs of 0.869 and 0.864 in the training and test datasets, respectively. Delong test showed that the nomogram was significantly different from the clinical model and four single-sequence radiomics signatures (P < 0.05). Moreover, calibration curves demonstrated good agreement, and DCA highlighted benefits of the nomogram. Conclusions The comprehensive nomogram can preoperatively and noninvasively predict PNI status, provide a convenient and practical tool for treatment strategy, and help optimize individualized clinical decision-making in RC patients.
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Affiliation(s)
- Yang Zhang
- Cancer Center, Department of Radiology, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, China
| | - Jiaxuan Peng
- Medical College, Jinzhou Medical University, Jinzhou, China
| | - Jing Liu
- Cancer Center, Department of Radiology, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, China
| | - Yanqing Ma
- Cancer Center, Department of Radiology, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, China
| | - Zhenyu Shu
- Cancer Center, Department of Radiology, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, China
- *Correspondence: Zhenyu Shu,
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11
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Qi Y, Feng F, Zhang N, Zhang H, Cheng G. Magnetic Resonance Image under the Low-Rank Matrix Denoising Algorithm in Evaluating the Efficacy of Neoadjuvant Chemo-Radiotherapy for Rectal Cancer. SCIENTIFIC PROGRAMMING 2022; 2022:1-10. [DOI: 10.1155/2022/5299385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
This study was to explore the application value of magnetic resonance imaging (MRI) images obtained by low-rank matrix recovery algorithm (LRMR algorithm) in evaluating the curative effect of rectal cancer patients receiving the neoadjuvant chemo-radiotherapy (nCRT). In this study, an image denoising model was designed based on the LRMR algorithm, the original low-rank data matrix was recovered from the error, and the low-rank matrix was restored by solving the optimal kernel norm, so as to effectively separate the image data information and the interference noise. In addition, the model was applied to 60 patients with rectal cancer who received nCRT to extract the texture parameters and lesion-related data from the MRI images. The results showed that the MRI images optimized by LRMR algorithm were clearer than the original images, contained less excess noise, and had improved imaging accuracy and image quality. The results of typical cases suggested that the front of the rectal wall membrane of a patient in the T-downstage group was not smooth before treatment, the internal angiography was blurred, and the wall membrane was thickened, but the wall membrane became thinner after treatment, the highest position was reduced from 1.46 cm to 0.38 cm, the average value of the apparent diffusion coefficient (ADC) increased from 0.732 × 10−3 mm2/s to 1.196 × 10−3 mm2/s, and the lesion tissue was thicker. It was found that the height, length, and ADC of the lesion after the nCRT showed statistically great difference in contrast to the values before the treatment
. Such results indicated that the nCRT showed obvious effects in the clinical treatment of rectal cancer. In short, the LRMR algorithm could remove the interference noise in the MRI image, and from the information about rectal cancer tumor lesions extracted from that, the height value and length value of tumor lesions in patients given neoadjuvant chemo-radiotherapy were reduced compared with those before treatment, and the apparent diffusion coefficient value was increased, indicating that neoadjuvant chemo-radiotherapy has a significant effect in the clinical treatment of rectal cancer.
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Affiliation(s)
- Yulong Qi
- Medical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, Guangdong, China
- Shantou University Medical College, Shantou 515041, Guangdong, China
| | - Fei Feng
- Medical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, Guangdong, China
| | - Na Zhang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, Guangdong, China
| | - Hui Zhang
- Medical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, Guangdong, China
| | - Guanxun Cheng
- Medical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, Guangdong, China
- Shantou University Medical College, Shantou 515041, Guangdong, China
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12
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García-Figueiras R, Baleato-González S, Canedo-Antelo M, Alcalá L, Marhuenda A. Imaging Advances on CT and MRI in Colorectal Cancer. CURRENT COLORECTAL CANCER REPORTS 2021. [DOI: 10.1007/s11888-021-00468-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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13
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Low-Rank Matrix Denoising Algorithm-Based MRI Image Feature for Therapeutic Effect Evaluation of NCRT on Rectal Cancer. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:3080640. [PMID: 34880974 PMCID: PMC8648445 DOI: 10.1155/2021/3080640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 10/31/2021] [Accepted: 11/03/2021] [Indexed: 11/17/2022]
Abstract
This study aimed to explore the therapeutic effects of neoadjuvant chemoradiotherapy (NCRT) on rectal cancer patients using the MRI based on low-rank matrix denoising algorithm, which was then compared with the postoperative pathological examination to evaluate its application value in tumor staging after NCRT treatment. 15 patients with rectal cancer who met the requirements of radiotherapy and chemotherapy after conventional MRI were selected as the research subjects. The conventional MRI images before and after NCRT treatment were divided in two groups. One group was not processed and set as the conventional group; the other group was processed with low-rank matrix denoising algorithm and set as the optimized group. The two groups of images were observed for the changes in the ADC value and length and thickness of the tumor before and after NCRT treatment. The two groups were compared with the pathological examination for the complete remission of pathology (pCR) after the NCRT treatment and the tumor stage results. The results showed that Root Mean Square Error (RMSE) and Peak Signal to Noise Ratio (PSNR) (18.9121 and 74.9911 dB) after introducing the low-rank matrix denoising algorithm were significantly better than those before (20.1234 and 70.1234 dB) (P < 0.05); there were notable differences in the tumor index data within the two groups before and after NCRT treatment (P < 0.05), indicating that the NCRT treatment was effective. The pathological examination results of pCR data of the two groups were not much different (P > 0.05); the examination results between the two groups were different, but no notable difference was noted (P < 0.05); in the optimized group, there was no notable difference between the MRI results and the pathological examination results (P < 0.05), while in the conventional group, there were notable differences in the MRI results and pathological examination results (P < 0.05). In conclusion, MRI images based on low-rank matrix denoising algorithm are clearer, which can improve the diagnosis rate of patients and better display the changes of the microenvironment after NCRT treatment. It also indicates that NCRT treatment has significant clinical effects in the treatment of rectal cancer patients, which is worth promoting.
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14
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Shoghi KI, Badea CT, Blocker SJ, Chenevert TL, Laforest R, Lewis MT, Luker GD, Manning HC, Marcus DS, Mowery YM, Pickup S, Richmond A, Ross BD, Vilgelm AE, Yankeelov TE, Zhou R. Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine. ACTA ACUST UNITED AC 2021; 6:273-287. [PMID: 32879897 PMCID: PMC7442091 DOI: 10.18383/j.tom.2020.00023] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.
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Affiliation(s)
- Kooresh I Shoghi
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Cristian T Badea
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC
| | - Stephanie J Blocker
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC
| | | | - Richard Laforest
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Michael T Lewis
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX
| | - Gary D Luker
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - H Charles Manning
- Vanderbilt Center for Molecular Probes-Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN
| | - Daniel S Marcus
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Yvonne M Mowery
- Department of Radiation Oncology, Duke University Medical Center, Durham, Durham, NC
| | - Stephen Pickup
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania.,Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| | - Ann Richmond
- Department of Pharmacology, Vanderbilt School of Medicine, Nashville, TN
| | - Brian D Ross
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - Anna E Vilgelm
- Department of Pathology, The Ohio State University, Columbus, OH
| | - Thomas E Yankeelov
- Departments of Biomedical Engineering, Diagnostic Medicine, and Oncology, Oden Institute for Computational Engineering and Sciences, Austin, TX; and.,Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Rong Zhou
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania.,Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
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15
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The Clinical Value of the Combined Detection of Enhanced CT, MRI, CEA, and CA199 in the Diagnosis of Rectal Cancer. JOURNAL OF ONCOLOGY 2021; 2021:8585371. [PMID: 34335762 PMCID: PMC8292063 DOI: 10.1155/2021/8585371] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 07/05/2021] [Indexed: 12/19/2022]
Abstract
Background To explore the clinical value of enhanced computed tomography (enhanced CT), magnetic resonance imaging (MRI), carcinoembryonic antigen (CEA), and cancer antigen 199 (CA199) in the diagnosis of rectal cancer (RC). Methods A total of 156 patients with RC confirmed by postoperative pathology admitted to the Affiliated Yantai Yuhuangding Hospital of Qingdao University from March 2018 to November 2020 were included in the malignant group, and 52 patients with chronic proctitis in the benign control group. All patients underwent preoperative enhanced CT, MRI scans, and serum CEA and CA199 tests. The accuracy, sensitivity, and specificity of single and combined enhanced CT, MRI, CEA, and CA199 tests for the clinical staging of RC were calculated. Results The postoperative pathological diagnosis showed that 35 cases of 156 RC patients were at T1 stage, 29 cases were at T2 stage, 24 cases were at T3 stage, 11 cases were at T4 stage, 23 cases were at N0 stage, 21 cases were at N1 stage, 8 cases were at N2 stage, 3 cases were at M0 stage, and 2 cases were at M1 stage. The positive rate of MRI in the diagnosis of RC was higher than that of enhanced CT. Serum CEA and CA199 levels in the malignant group were significantly increased compared with the benign group. The sensitivity, specificity, and accuracy of the combined detection were significantly higher than those of the single detection. Conclusion Compared with enhanced CT, MRI has a higher detection rate of T and N stage in patients with RC. Combined enhanced CT, MRI, CEA, and CA199 can provide more accurate diagnosis and preoperative staging of RC patients.
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Felder SI, Feuerlein S, Parsee A, Imanirad I, Sanchez J, Dessureault S, Kim R, Hoffe S, Frakes J, Costello J. Endoscopic and MRI response evaluation following neoadjuvant treatment for rectal cancer: a pictorial review with matched MRI, endoscopic, and pathologic examples. Abdom Radiol (NY) 2021; 46:1783-1804. [PMID: 33111189 DOI: 10.1007/s00261-020-02827-6] [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: 07/16/2020] [Revised: 10/05/2020] [Accepted: 10/10/2020] [Indexed: 10/23/2022]
Abstract
A nonoperative management strategy, or Watch-and-Wait, following neoadjuvant therapies of locally advanced rectal adenocarcinoma is increasingly considered for select patients. Yet, standardized tumor response assessment to best select and surveil suitable patients remains an unmet clinical challenge. Endoscopic and MRI currently provide the most reliable tumor response estimations. However, resources illustrating variable tumor responses to neoadjuvant therapies remain limited. This pictorial review aims to provide detailed and annotated examples of common endoscopic and MRI findings of rectal cancer treatment response, while also emphasizing their respective diagnostic shortcomings and consequently, the necessity for a multidisciplinary approach to optimally manage these patients.
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17
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Two Zn(II) coordination polymers: Selective detection Fe3+ ion and inhibitory activity on the liver cancer viability by regulating the prolyl hydroxylase-3. ARAB J CHEM 2021. [DOI: 10.1016/j.arabjc.2021.102998] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
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18
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Di Re AM, Sun Y, Sundaresan P, Hau E, Toh JWT, Gee H, Or M, Haworth A. MRI radiomics in the prediction of therapeutic response to neoadjuvant therapy for locoregionally advanced rectal cancer: a systematic review. Expert Rev Anticancer Ther 2021; 21:425-449. [PMID: 33289435 DOI: 10.1080/14737140.2021.1860762] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Introduction: The standard of care for locoregionally advanced rectal cancer is neoadjuvant therapy (NA CRT) prior to surgery, of which 10-30% experience a complete pathologic response (pCR). There has been interest in using imaging features, also known as radiomics features, to predict pCR and potentially avoid surgery. This systematic review aims to describe the spectrum of MRI studies examining high-performing radiomic features that predict NA CRT response.Areas covered: This article reviews the use of pre-therapy MRI in predicting NA CRT response for patients with locoregionally advanced rectal cancer (T3/T4 and/or N1+). The primary outcome was to identify MRI radiomic studies; secondary outcomes included the power and the frequency of use of radiomic features.Expert opinion: Advanced models incorporating multiple radiomics categories appear to be the most promising. However, there is a need for standardization across studies with regards to; the definition of NA CRT response, imaging protocols, and radiomics features incorporated. Further studies are needed to validate current radiomics models and to fully ascertain the value of MRI radiomics in the response prediction for locoregionally advanced rectal cancer.
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Affiliation(s)
- Angelina Marina Di Re
- Colorectal Department, Westmead Hospital, Cnr Hawkesbury, Westmead, NSW.,School of Physics, University of Sydney, Camperdown, NSW, Australia
| | - Yu Sun
- School of Physics, University of Sydney, Camperdown, NSW, Australia
| | - Purnima Sundaresan
- Radiation Oncology Network, Western Sydney Local Health District, Cnr Hawkesbury, Westmead, NSW, Australia.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia
| | - Eric Hau
- Radiation Oncology Network, Western Sydney Local Health District, Cnr Hawkesbury, Westmead, NSW, Australia.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia.,Centre for Cancer Research, Westmead Institute of Medical Research, Westmead, NSW, Australia
| | - James Wei Tatt Toh
- Colorectal Department, Westmead Hospital, Cnr Hawkesbury, Westmead, NSW.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia.,Centre for Cancer Research, Westmead Institute of Medical Research, Westmead, NSW, Australia
| | - Harriet Gee
- Radiation Oncology Network, Western Sydney Local Health District, Cnr Hawkesbury, Westmead, NSW, Australia.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia
| | - Michelle Or
- Radiation Oncology Network, Western Sydney Local Health District, Cnr Hawkesbury, Westmead, NSW, Australia
| | - Annette Haworth
- School of Physics, University of Sydney, Camperdown, NSW, Australia
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19
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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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20
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Clinical Relevance and Practical Approach for Challenging Rectal Cancer MRI Findings. CURRENT RADIOLOGY REPORTS 2020. [DOI: 10.1007/s40134-020-00359-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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21
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Childs DD, Rocha Lima CMSP, Zhou Y. Mucin-Containing Rectal Cancer: A Review of Unique Imaging, Pathology, and Therapeutic Response Features. Semin Roentgenol 2020; 56:186-200. [PMID: 33858645 DOI: 10.1053/j.ro.2020.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- David D Childs
- Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, NC.
| | | | - Yi Zhou
- Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC
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22
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Huang Z, Zhang W, He D, Cui X, Tian S, Yin H, Song B. Development and validation of a radiomics model based on T2WI images for preoperative prediction of microsatellite instability status in rectal cancer: Study Protocol Clinical Trial (SPIRIT Compliant). Medicine (Baltimore) 2020; 99:e19428. [PMID: 32150094 PMCID: PMC7478495 DOI: 10.1097/md.0000000000019428] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
INTRODUCTION Globally, colorectal cancer (CRC) is the third most commonly diagnosed cancer in males and the second in females. Rectal cancer (RC) accounts for about 28% of all newly diagnosed CRC cases. The treatment of choice for locally advanced RC is a combination of surgical resection and chemotherapy and/or radiotherapy. These patients can potentially be cured, but the clinical outcome depends on the tumor biology. Microsatellite instability (MSI) is an important biomarker in CRC, with crucial diagnostic, prognostic, and predictive implications. It is important to develop a noninvasive, repeatable, and reproducible method to reflect the microsatellite status. Magnetic resonance imaging (MRI) has been recommended as the preferred imaging examination for RC in clinical practice by both the National Comprehensive Cancer Network and the European Society for Medical Oncology guidelines. T2WI is the core sequence of MRI scanning protocol for RC. Radiomics, the high-throughput mining of quantitative image features from standard-of-care medical imaging that enables data to be extracted and applied within clinical-decision support systems to improve diagnostic, prognostic, and predictive accuracy, is gaining importance in cancer research.We proposed a hypothesis: A simple radiomics model based on only T2WI images can accurately evaluate the MSI status of RC preoperatively. OBJECTIVE To develop a radiomics model based on T2WI images for accurate preoperative diagnosis the MSI status of RC. METHOD All patients with RC were retrospectively enrolled. The dataset was randomly split into training cohort (70% of all patients) and testing cohort (30% of all patients). The radiomics features will be extracted from T2WI-MR images of the entire primary tumor region. Least absolute shrinkage and selection operator was used to select the most predictive radiomics features. Logistic regression models were constructed in the training/validation cohort to discriminate the MSI status using clinical factors, radiomics features, or their integration. The diagnostic performance of these 3 models was evaluated in the testing cohort based on their area under the curve, sensitivity, specificity, and accuracy. DISCUSSION This study will help us know whether radiomics model based on T2WI images to preoperative identify MSI status of RC.
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Affiliation(s)
- Zixing Huang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu
| | - Wei Zhang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu
- Department of Radiology, Sichuan Provincial Corps Hospital, Chinese People’ s Armed Police Forces, Leshan
| | - Du He
- Department of Pathology, West China Hospital, Sichuan University, Chengdu
| | - Xing Cui
- Institute of Advanced Research, Infervision, Beijing, China
| | - Song Tian
- Institute of Advanced Research, Infervision, Beijing, China
| | - Hongkun Yin
- Institute of Advanced Research, Infervision, Beijing, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu
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Gürses B, Altınmakas E, Böge M, Aygün MS, Bayram O, Balık E. Multiparametric MRI of rectal cancer-repeatability of quantitative data: a feasibility study. Diagn Interv Radiol 2020; 26:87-94. [PMID: 32071023 DOI: 10.5152/dir.2019.19127] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
PURPOSE In this study, we aimed to analyze the repeatability of quantitative multiparametric rectal magnetic resonance imaging (MRI) parameters with different measurement techniques. METHODS All examinations were performed with 3 T MRI system. In addition to routine sequences for rectal cancer imaging protocol, small field-of-view diffusion-weighted imaging and perfusion sequences were acquired in each patient. Apparent diffusion coefficient (ADC) was used for diffusion analysis and ktrans was used for perfusion analysis. Three different methods were used in measurement of these parameters; measurements were performed twice by one radiologist for intraobserver and separately by three radiologists for interobserver variability analysis. ADC was measured by the lowest value, the value at maximum wall thickness, and freehand techniques. Ktrans was measured at the slice with maximum wall thickness, by freehand drawn region of interest (ROI), and at the dark red spot with maximum value. RESULTS A total of 30 patients with biopsy-proven rectal adenocarcinoma were included in the study. The mean values of the parameters measured by the first radiologist on the first and second measurements were as follows: mean lowest ADC, 721.31±147.18 mm2/s and 718.96±135.71 mm2/s; mean ADC value on the slice with maximum wall thickness, 829.90±144.24 mm2/s and 829.48±149.23 mm2/s; mean ADC value measured by freehand ROI on the slice with maximum wall thickness, 846.56±136.31 mm2/s and 848.23±144.15 mm2/s; mean ktrans value on the slice with maximum wall thickness, 0.219±0.080 and 0.214±0.074; mean ktrans by freehand ROI technique (including as much tumoral tissue as possible), 0.208±0.074 and 0.207±0.069; mean ktrans measured from the dark red foci, 0.308±0.109 and 0.311±0.105. Intraobserver agreement was very good among diffusion and perfusion parameters obtained with all three measurement techniques. Interobserver agreement was very good, except for one of the measurement techniques. As far as interobserver variability is considered, only ADC value measured on the slice with maximum wall thickness differed significantly. CONCLUSION Multiparametric MRI of rectum, using ADC as the diffusion and ktrans as the perfusion parameter is a repeatable technique. This technique may potentially be used in prediction and evaluation of neoadjuvant treatment response. New studies with larger patient groups are needed to validate the role of multiparametric MRI.
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Affiliation(s)
- Bengi Gürses
- Department of Radiology, Koç University School of Medicine, İstanbul, Turkey
| | - Emre Altınmakas
- Department of Radiology, Koç University School of Medicine, İstanbul, Turkey
| | - Medine Böge
- Department of Radiology, Koç University School of Medicine, İstanbul, Turkey
| | - M Serhat Aygün
- Department of Radiology, Koç University School of Medicine, İstanbul, Turkey
| | - Onur Bayram
- Department of General Surgery, Koç University School of Medicine, İstanbul, Turkey
| | - Emre Balık
- Department of General Surgery, Koç University School of Medicine, İstanbul, Turkey
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