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Gong X, Ye Z, Shen Y, Song B. Enhancing the role of MRI in rectal cancer: advances from staging to prognosis prediction. Eur Radiol 2025:10.1007/s00330-025-11463-x. [PMID: 40045072 DOI: 10.1007/s00330-025-11463-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Revised: 12/19/2024] [Accepted: 01/28/2025] [Indexed: 03/17/2025]
Abstract
Rectal cancer (RC) is one of the major health challenges worldwide. Accurate staging, restaging, invasiveness assessment, and treatment efficacy evaluation are crucial for its clinical management. Magnetic resonance imaging (MRI) plays a significant role in these processes. However, standard MRI techniques, including T2-weighted and diffusion-weighted imaging, have uncertainties in identifying early-stage tumors, high-risk nodules, extramural vascular invasion, and treatment efficacy, potentially leading to inappropriate treatment. Recent advances suggest that the integration of traditional MRI methods, including diffusion-weighted imaging, opposed-phase or contrast-enhanced T1-weighted imaging, as well as emerging synthetic MRI, could address these challenges. Additionally, improvements in imaging technology have spurred research into advanced functional MRI techniques such as diffusion kurtosis imaging and amide proton transfer weighted MRI, yielding promising results in RC assessment. Total neoadjuvant therapy has emerged as a new treatment paradigm for locally advanced RC, with neoadjuvant immunotherapy and chemotherapy offering viable alternatives to neoadjuvant chemoradiotherapy. However, the lack of standards for the early prediction of patient survival and tumor response to neoadjuvant therapy highlights a critical unmet need in matching therapies to suitable patients. Furthermore, organ preservation strategies after neoadjuvant therapy provide personalized options based on tumor response and patient preferences, yet traditional MRI assessments show significant variability. Radiomics and artificial intelligence hold promise for revealing complex patterns in MRI images associated with patient prognosis and treatment response. This review provides an overview of current MRI advancements in RC assessment and emphasizes how future research can refine tailored treatment strategies to improve patient outcomes. KEY POINTS: Question The accurate diagnosis of early-stage rectal tumors, high-risk nodules, treatment responses, and the early prediction of patient survival and therapeutic outcomes remain an unmet need. Findings Visual MRI has improved staging, restaging, and invasiveness evaluation. Advanced MRI, radiomics and artificial intelligence provide significant potential for tumor characterization and outcome prediction. Clinical relevance Advances in visual MRI are improving routine imaging protocols and radiomics and artificial intelligence show promise in enhancing treatment decisions through precise tumor characterization and outcome prediction.
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Affiliation(s)
- Xiaoling Gong
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Zheng Ye
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yu Shen
- Colorectal Cancer Center, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Bin Song
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.
- Department of Radiology, Sanya People's Hospital, Sanya, China.
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Zhang H, Yi H, Qin S, Liu X, Liu G. CLIP-based multimodal endorectal ultrasound enhances prediction of neoadjuvant chemoradiotherapy response in locally advanced rectal cancer. PLoS One 2024; 19:e0315339. [PMID: 39661640 PMCID: PMC11633952 DOI: 10.1371/journal.pone.0315339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2024] [Accepted: 11/22/2024] [Indexed: 12/13/2024] Open
Abstract
BACKGROUND Forecasting the patient's response to neoadjuvant chemoradiotherapy (nCRT) is crucial for managing locally advanced rectal cancer (LARC). This study investigates whether a predictive model using image-text features extracted from endorectal ultrasound (ERUS) via Contrastive Language-Image Pretraining (CLIP) can predict tumor regression grade (TRG) before nCRT. METHODS A retrospective analysis of 577 LARC patients who received nCRT followed by surgery was conducted from January 2018 to December 2023. ERUS scans and TRG were used to assess nCRT response, categorizing patients into good (TRG 0) and poor (TRG 1-3) responders. Image and text features were extracted using the ResNet50+RBT3 (RN50) and ViT-B/16+RoBERTa-wwm (VB16) components of the Chinese-CLIP model. LightGBM was used for model construction and comparison. A subset of 100 patients from each responder group was used to compare the CLIP method with manual radiomics methods (logistic regression, support vector machines, and random forest). SHapley Additive exPlanations (SHAP) technique was used to analyze feature contributions. RESULTS The RN50 and VB16 models achieved AUROC scores of 0.928 (95% CI: 0.90-0.96) and 0.900 (95% CI: 0.86-0.93), respectively, outperforming manual radiomics methods. SHAP analysis indicated that image features dominated the RN50 model, while both image and text features were significant in the VB16 model. CONCLUSIONS The CLIP-based predictive model using ERUS image-text features and LightGBM showed potential for improving personalized treatment strategies. However, this study is limited by its retrospective design and single-center data.
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Affiliation(s)
- Hanchen Zhang
- Department of Medical Ultrasonics, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Nuclear Medicine, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hang Yi
- Department of Medical Ultrasonics, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Si Qin
- Department of Medical Ultrasonics, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoyin Liu
- Department of Medical Ultrasonics, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Guangjian Liu
- Department of Medical Ultrasonics, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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Zhang Y, Li G, Chen J, Jiang M, Gao Y, Li K, Wen H, Yan J. The value of predicting neoadjuvant chemotherapy early efficacy in nasopharyngeal carcinoma based on amide proton transfer imaging and diffusion weighted imaging. Quant Imaging Med Surg 2024; 14:7330-7340. [PMID: 39429559 PMCID: PMC11485347 DOI: 10.21037/qims-24-188] [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: 01/29/2024] [Accepted: 08/23/2024] [Indexed: 10/22/2024]
Abstract
Background Early detection of nasopharyngeal carcinoma (NPC) patients who are not sensitive to neoadjuvant chemotherapy (NAC) can guard against overtreatment. This study aimed to evaluate the effectiveness of amide proton transfer (APT) imaging and diffusion-weighted imaging (DWI) in predicting the early response to NAC in patients with NPC. Methods This prospective study enrolled fifty patients with biopsy-confirmed NPC from September 2021 to May 2023. Magnetic resonance imaging (MRI) including APT and DWI, was performed before NAC. After NAC, patients were divided into complete response (CR), partial response (PR), and stable disease (SD) and progressive disease (PD) groups based on the Response Evaluation Criteria in Solid Tumours Version 1.1. The Kruskal-Wallis H test was used for statistical analysis. The differences in APT and apparent diffusion coefficient (ADC) values among the different efficacy groups were compared, the receiver operating characteristic (ROC) curve was drawn for statistically significant parameters, and the area under the curve (AUC) was calculated. Results Fifty patients (mean age: 47±14 years; 42 males and 8 females) were included in the final analysis (11 were in the CR group, 30 in the PR group, 9 in the SD group, and 0 in the PD group). The ADC values showed no significant differences among the different treatment response groups. The SD group showed significantly lower APTmax (P=0.025), APTskewness (P=0.025) and APT90% (P=0.001) values than the CR and PR groups. Setting APT90% =3.10% as the cut-off value, optimal diagnostic performance (AUC: 0.831; sensitivity: 0.778; specificity: 0.878) was obtained in predicting the SD group. Conclusions APT imaging can predict the early tumour response to NAC in patients with NPC. APT imaging may be superior to DWI in predicting tumour response.
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Affiliation(s)
- Yulin Zhang
- Department of Medical Imaging, the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Guomin Li
- Department of Medical Imaging, the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Jinyan Chen
- Department of Medical Imaging, the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Meien Jiang
- Department of Medical Imaging, the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Yunyu Gao
- Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Kunsong Li
- Department of Oncology, the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Hua Wen
- Department of Medical Imaging, the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Jianhao Yan
- Department of Medical Imaging, the Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
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Wang Y, Wang L, Huang H, Ma J, Lin L, Liu L, Song Q, Liu A. Amide proton transfer-weighted magnetic resonance imaging for the differentiation of parotid gland tumors. Front Oncol 2023; 13:1223598. [PMID: 37664057 PMCID: PMC10471989 DOI: 10.3389/fonc.2023.1223598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 07/28/2023] [Indexed: 09/05/2023] Open
Abstract
Purpose To assess the usefulness of amide proton transfer-weighted (APTw) imaging in the differentiation of parotid gland tumors. Materials and methods Patients with parotid gland tumors who underwent APTw imaging were retrospectively enrolled and divided into groups according to pathology. Two radiologists evaluated the APTw image quality independently, and APTw images with quality score ≥3 were enrolled. The maximum and average values of APTw imaging for tumor lesions (APTmax and APTmean) were measured. The differences in APTmax and APTmean were compared between malignant tumors (MTs) and benign tumors (BTs), as well as between MTs and pleomorphic adenomas (PAs) and between MTs and Warthin tumors (WTs). Independent-samples t-test, Kruskal-Wallis H test, and receiver operating characteristic (ROC) curve analyses were used for statistical analysis. Results Seventy-three patients were included for image quality evaluation. In this study, 32/73 and 29/73 parotid tumors were scored as 4 and 3, respectively. After excluding lesions with quality score ≤2 (12/73), the APTmean and APTmax of MTs were 4.15% ± 1.33% and 7.43% ± 1.61%, higher than those of BTs 2.74% ± 1.04% and 5.25% ± 1.54%, respectively (p < 0.05). The areas under the ROC curve (AUCs) of the APTmean and APTmax for differentiation between MTs and BTs were 0.819 and 0.821, respectively. MTs indicated significantly higher APTmean and APTmax values than those of PAs (p < 0.05) and WTs (p < 0.05). The AUCs of the APTmean and APTmax for differentiation between MTs and PAs were 0.830 and 0.815 and between MTs and WTs were 0.847 and 0.920, respectively. Conclusion Most APTw images for parotid tumors had acceptable image quality for APTw value evaluation. Both APTmax and APTmean can be used to differentiate MTs from BTs and to differentiate MTs from subtype parotid gland tumors.
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Affiliation(s)
- Yihua Wang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Lijun Wang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Haitao Huang
- Department of Stomatology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Juntao Ma
- Department of Stomatology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Liangjie Lin
- Clinical and Technical Support, Philips Healthcare, Beijing, China
| | - Lin Liu
- Department of Stomatology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
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Peng Y, Zou X, Chen G, Hu X, Shen Y, Hu D, Li Z. Chemical Shift-Encoded Sequence (IDEAL-IQ) and Amide Proton Transfer (APT) MRI for Prediction of Histopathological Factors of Rectal Cancer. Bioengineering (Basel) 2023; 10:720. [PMID: 37370651 DOI: 10.3390/bioengineering10060720] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 06/07/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
To investigate whether parameters from IDEAL-IQ/amide proton transfer MRI (APTWI) could help predict histopathological factors of rectal cancer. Preoperative IDEAL-IQ and APTWI sequences of 67 patients with rectal cancer were retrospectively analyzed. The intra-tumoral proton density fat fraction (PDFF), R2* and magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)) were measured according to the histopathological factors of rectal cancer. The relationship between MR parameters and histopathological factors were analyzed, along with diagnostic performance of MR parameters. PDFF, R2* and MTRasym (3.5 ppm) were statistically different between T1+T2/T3+T4 stages, non-metastatic/metastatic lymph nodes, lower/higher tumor grade and negative/positive status of MRF and EMVI (p < 0.001 for PDFF, p = 0.000-0.015 for R2* and p = 0.000-0.006 for MTRasym (3.5 ppm)). There were positive correlations between the above parameters and the histopathological features of rectal cancer (r = 0.464-0.723 for PDFF (p < 0.001), 0.299-0.651 for R2* (p = 0.000-0.014), and 0.337-0.667 for MTRasym (3.5 ppm) (p = 0.000-0.005)). MTRasym (3.5 ppm) correlated moderately and mildly with PDFF (r = 0.563, p < 0.001) and R2* (r = 0.335, p = 0.006), respectively. PDFF provided a significantly higher diagnostic ability than MTRasym (3.5 ppm) for distinguishing metastatic from non-metastatic lymph nodes (z = 2.407, p = 0.0161). No significant differences were found in MR parameters for distinguishing other histopathological features (p > 0.05). IDEAL-IQ and APTWI were associated with histopathological factors of rectal cancer, and might serve as non-invasive biomarkers for characterizing rectal cancer.
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Affiliation(s)
- Yang Peng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Xianlun Zou
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Gen Chen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Xuemei Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Yaqi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
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Huang C, Wang L, Chen H, Fu W, Shao L, Zhou D, Wu J, Ye Y. A positive feedback loop between ID3 and PPARγ via DNA damage repair regulates the efficacy of radiotherapy for rectal cancer. BMC Cancer 2023; 23:429. [PMID: 37170184 PMCID: PMC10176823 DOI: 10.1186/s12885-023-10874-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 04/21/2023] [Indexed: 05/13/2023] Open
Abstract
OBJECTIVE To study the effect of inhibitor of differentiation 3 (ID3) on radiotherapy in patients with rectal cancer and to explore its primary mechanism. METHODS Cell proliferation and clonogenic assays were used to study the relationship between ID3 and radiosensitivity. Co-immunoprecipitation and immunofluorescence were performed to analyze the possible mechanism of ID3 in the radiosensitivity of colorectal cancer. At the same time, a xenograft tumor model of HCT116 cells in nude mice was established to study the effect of irradiation on the tumorigenesis of ID3 knockdown colorectal cancer cells in vivo. Immunohistochemistry was performed to analyze the relationship between ID3 expression and the efficacy of radiotherapy in 46 patients with rectal cancer. RESULTS Proliferation and clonogenic assays revealed that the radiosensitivity of colorectal cancer cells decreased with ID3 depletion through p53-independent pathway. With the decrease in ID3 expression, MDC1 was downregulated. Furthermore, the expression of ID3, MDC1, and γH2AX increased and formed foci after irradiation. ID3 interacted with PPARγ and form a positive feedback loop to enhance the effect of ID3 on the radiosensitivity of colorectal cancer. Irradiation tests in nude mice also confirmed that HCT116 cells with ID3 knockdown were more affected by irradiation. Immunohistochemical study showed that rectal cancer patients with low expression of ID3 had better radiotherapy efficacy. CONCLUSIONS ID3 and PPARγ influence the radiosensitivity of colorectal cancer cells by interacting with MDC1 to form a positive feedback loop that promotes DNA damage repair. Patients with low expression of ID3 who received neoadjuvant chemoradiotherapy can obtain a better curative effect.
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Affiliation(s)
- Chuanzhong Huang
- Laboratory of Immuno-Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
- School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China
- Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, 350014, China
| | - Ling Wang
- Laboratory of Immuno-Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
- School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China
- Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, 350014, China
| | - Huijing Chen
- Laboratory of Immuno-Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
- School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China
| | - Wankai Fu
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Lingdong Shao
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Dongmei Zhou
- Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, 350014, China
- Departments of Pathology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Junxin Wu
- Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, 350014, China.
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China.
| | - Yunbin Ye
- Laboratory of Immuno-Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China.
- School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China.
- Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, 350014, China.
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Wang L, Wu X, Tian R, Ma H, Jiang Z, Zhao W, Cui G, Li M, Hu Q, Yu X, Xu W. MRI-based pre-Radiomics and delta-Radiomics models accurately predict the post-treatment response of rectal adenocarcinoma to neoadjuvant chemoradiotherapy. Front Oncol 2023; 13:1133008. [PMID: 36925913 PMCID: PMC10013156 DOI: 10.3389/fonc.2023.1133008] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 02/06/2023] [Indexed: 02/24/2023] Open
Abstract
Objectives To develop and validate magnetic resonance imaging (MRI)-based pre-Radiomics and delta-Radiomics models for predicting the treatment response of local advanced rectal cancer (LARC) to neoadjuvant chemoradiotherapy (NCRT). Methods Between October 2017 and August 2022, 105 LARC NCRT-naïve patients were enrolled in this study. After careful evaluation, data for 84 patients that met the inclusion criteria were used to develop and validate the NCRT response models. All patients received NCRT, and the post-treatment response was evaluated by pathological assessment. We manual segmented the volume of tumors and 105 radiomics features were extracted from three-dimensional MRIs. Then, the eXtreme Gradient Boosting algorithm was implemented for evaluating and incorporating important tumor features. The predictive performance of MRI sequences and Synthetic Minority Oversampling Technique (SMOTE) for NCRT response were compared. Finally, the optimal pre-Radiomics and delta-Radiomics models were established respectively. The predictive performance of the radionics model was confirmed using 5-fold cross-validation, 10-fold cross-validation, leave-one-out validation, and independent validation. The predictive accuracy of the model was based on the area under the receiver operator characteristic (ROC) curve (AUC). Results There was no significant difference in clinical factors between patients with good and poor reactions. Integrating different MRI modes and the SMOTE method improved the performance of the radiomics model. The pre-Radiomics model (train AUC: 0.93 ± 0.06; test AUC: 0.79) and delta-Radiomcis model (train AUC: 0.96 ± 0.03; test AUC: 0.83) all have high NCRT response prediction performance by LARC. Overall, the delta-Radiomics model was superior to the pre-Radiomics model. Conclusion MRI-based pre-Radiomics model and delta-Radiomics model all have good potential to predict the post-treatment response of LARC to NCRT. Delta-Radiomics analysis has a huge potential for clinical application in facilitating the provision of personalized therapy.
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Affiliation(s)
- Likun Wang
- Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Department of Molecular Imaging and Nuclear Medicine, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Department of Ultrasound Medicine, The First Affiliated Hospital of Hebei North University, Zhangjiakou, China
| | - Xueliang Wu
- Graduate School, Tianjin Medical University, Tianjin, China.,Department of Gastrointestinal Surgery, Tianjin Medical University Nankai Hospital, Tianjin, China
| | - Ruoxi Tian
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Hongqing Ma
- Department of General Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Zekun Jiang
- College of Computer Science, Sichuan University, Chengdu, China
| | - Weixin Zhao
- College of Computer Science, Sichuan University, Chengdu, China
| | - Guoqing Cui
- Medical Image Center, The First Affiliated Hospital of Hebei North University, Zhangjiakou, China
| | - Meng Li
- Graduate School, Hebei North University, Zhangjiakou, China
| | - Qinsheng Hu
- Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiangyang Yu
- Department of Gastrointestinal Surgery, Tianjin Medical University Nankai Hospital, Tianjin, China
| | - Wengui Xu
- Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
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Song Q, Tian S, Ma C, Meng X, Chen L, Wang N, Lin L, Wang J, Song Q, Liu A. Amide proton transfer weighted imaging combined with dynamic contrast-enhanced MRI in predicting lymphovascular space invasion and deep stromal invasion of IB1-IIA1 cervical cancer. Front Oncol 2022; 12:916846. [PMID: 36172148 PMCID: PMC9512406 DOI: 10.3389/fonc.2022.916846] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 08/08/2022] [Indexed: 12/09/2022] Open
Abstract
Objectives To investigate the value of amide proton transfer weighted (APTw) imaging combined with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting intermediate-risk factors of deep stromal invasion (DSI) and lymphovascular vascular space invasion (LVSI) in cervical cancer. Methods Seventy patients with cervical cancer who underwent MRI before operation from July 2019 to February 2022 were retrospectively included in this study. Clinical information including age, histologic subtype etc. were recorded for patients. ATPw imaging parameter APTmean and DCE-MRI parameters Ktrans, Kep and Ve were measured and analyzed. The independent-sample t-test, Mann-Whitney U test, or Chi-square test was used to compare the differences of parameters between DSI/LVSI positive and negative groups. Logistic analysis was used to develop a combined predictive model. The receiver operating characteristic curve was for predictive performance. ANOVA and Kruskal-Wallis test were used to compare the differences of consecutive parameters among multiple groups. Results Ktrans and SCC-Ag were independent factors in predicting DSI; Ktrans+SCC-Ag had the highest AUC 0.819 with sensitivity and specificity of 71.74% and 91.67%, respectively. APTmean and Ktrans were independent factors in predicting LVSI; APTmean+Ktrans had the highest AUC 0.874 with sensitivity and specificity of 92.86% and 75.00%, respectively. Ktrans and Ve could discriminate coexistence of DSI and LVSI from presence of single one, APTmean could discriminate the presence of DSI or LVSI from no risk factor presence. Conclusion The combination of APTw and DCE-MRI is valuable in predicting intermediate-risk factors of DSI and LVSI in cervical cancer.
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Affiliation(s)
- Qingling Song
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Shifeng Tian
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Changjun Ma
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Xing Meng
- Department of Radiology, Dalian Women and Children’s Medical Group, Dalian, China
| | - Lihua Chen
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Nan Wang
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Liangjie Lin
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Jiazheng Wang
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
- *Correspondence: Ailian Liu,
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Jiménez de los Santos ME, Reyes-Pérez JA, Domínguez Osorio V, Villaseñor-Navarro Y, Moreno-Astudillo L, Vela-Sarmiento I, Sollozo-Dupont I. Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer. World J Gastroenterol 2022; 28:2609-2624. [PMID: 35949349 PMCID: PMC9254137 DOI: 10.3748/wjg.v28.i23.2609] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/25/2021] [Accepted: 04/25/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Whole-tumor apparent diffusion coefficient (ADC) histogram analysis is relevant to predicting the neoadjuvant chemoradiation therapy (nCRT) response in patients with locally advanced rectal cancer (LARC).
AIM To evaluate the performance of ADC histogram-derived parameters for predicting the outcomes of patients with LARC.
METHODS This is a single-center, retrospective study, which included 48 patients with LARC. All patients underwent a pre-treatment magnetic resonance imaging (MRI) scan for primary tumor staging and a second restaging MRI for response evaluation. The sample was distributed as follows: 18 responder patients (R) and 30 non-responders (non-R). Eight parameters derived from the whole-lesion histogram analysis (ADCmean, skewness, kurtosis, and ADC10th, 25th, 50th, 75th, 90th percentiles), as well as the ADCmean from the hot spot region of interest (ROI), were calculated for each patient before and after treatment. Then all data were compared between R and non-R using the Mann-Whitney U test. Two measures of diagnostic accuracy were applied: the receiver operating characteristic curve and the diagnostic odds ratio (DOR). We also reported intra- and interobserver variability by calculating the intraclass correlation coefficient (ICC).
RESULTS Post-nCRT kurtosis, as well as post-nCRT skewness, were significantly lower in R than in non-R (both P < 0.001, respectively). We also found that, after treatment, R had a larger loss of both kurtosis and skewness than non-R (∆%kurtosis and ∆skewness, P < 0.001). Other parameters that demonstrated changes between groups were post-nCRT ADC10th, ∆%ADC10th, ∆%ADCmean, and ROI ∆%ADCmean. However, the best diagnostic performance was achieved by ∆%kurtosis at a threshold of 11.85% (Area under the receiver operating characteristic curve [AUC] = 0.991, DOR = 376), followed by post-nCRT kurtosis = 0.78 × 10-3 mm2/s (AUC = 0.985, DOR = 375.3), ∆skewness = 0.16 (AUC = 0.885, DOR = 192.2) and post-nCRT skewness = 1.59 × 10-3 mm2/s (AUC = 0.815, DOR = 168.6). Finally, intraclass correlation coefficient analysis showed excellent intraobserver and interobserver agreement, ensuring the implementation of histogram analysis into routine clinical practice.
CONCLUSION Whole-tumor ADC histogram parameters, particularly kurtosis and skewness, are relevant biomarkers for predicting the nCRT response in LARC. Both parameters appear to be more reliable than ADCmean from one-slice ROI.
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Affiliation(s)
| | | | | | | | | | - Itzel Vela-Sarmiento
- Department of Gastrointestinal Surgery, National Cancer Institute, Mexico 14080, Mexico
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10
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Popita AR, Lisencu C, Rusu A, Popita C, Cainap C, Irimie A, Resiga L, Munteanu A, Fekete Z, Badea R. MRI Evaluation of Complete and Near-Complete Response after Neoadjuvant Therapy in Patients with Locally Advanced Rectal Cancer. Diagnostics (Basel) 2022; 12:diagnostics12040921. [PMID: 35453969 PMCID: PMC9027294 DOI: 10.3390/diagnostics12040921] [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: 03/14/2022] [Revised: 04/03/2022] [Accepted: 04/04/2022] [Indexed: 12/04/2022] Open
Abstract
Purpose To evaluate MRI performance in restaging locally advanced rectal cancers (LARC) after neoadjuvant chemoradiotherapy (nCRT) and interobserver agreement in identifying complete response (CR) and near-complete response (nCR). Methods 40 patients with CR and nCR on restaging MRI, surgery and/or endoscopy were enrolled. Two radiologists independently scored the restaging MRI and reported the presence of split scar sign (SSS) and MRI tumor regression grade (mrTRG). Diagnostic accuracy and ROC curves were calculated for single and combined sequences, with inter-reader agreement. Results Diagnostic performance was good for detecting CR and weaker for nCR. T2WI had the highest AUCs among individual sequences. There was a significant positive correlation between SSS and CR, with high Sp (89.5%/73.7%) and PPV (90%/79.2%) for both Readers. Similar accuracy rates were observed for the combination of sequences, with AUCs of 0.828–0.847 for CR and 0.690–0.762 for nCR. Interobserver agreement was strong for SSS, moderate for T2WI, weak for the combination of sequences. Conclusions Restaging MRI had good diagnostic performance in identifying CR and nCR. SSS had high Sp and PPV in diagnosing CR, with a strong level of interobserver agreement. T2WI with DWI was the optimal combination of sequences for selecting good responders.
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Affiliation(s)
- Anca-Raluca Popita
- “Ion Chiricuţă” Oncology Institute, 400015 Cluj-Napoca, Romania; (A.-R.P.); (C.L.); (C.P.); (A.I.); (L.R.); (A.M.); (Z.F.)
- Medical Imaging Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, 400162 Cluj-Napoca, Romania;
| | - Cosmin Lisencu
- “Ion Chiricuţă” Oncology Institute, 400015 Cluj-Napoca, Romania; (A.-R.P.); (C.L.); (C.P.); (A.I.); (L.R.); (A.M.); (Z.F.)
- Oncology Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, 400015 Cluj-Napoca, Romania
| | - Adriana Rusu
- Diabetes and Nutrition Diseases Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania;
| | - Cristian Popita
- “Ion Chiricuţă” Oncology Institute, 400015 Cluj-Napoca, Romania; (A.-R.P.); (C.L.); (C.P.); (A.I.); (L.R.); (A.M.); (Z.F.)
| | - Calin Cainap
- “Ion Chiricuţă” Oncology Institute, 400015 Cluj-Napoca, Romania; (A.-R.P.); (C.L.); (C.P.); (A.I.); (L.R.); (A.M.); (Z.F.)
- Oncology Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, 400015 Cluj-Napoca, Romania
- Correspondence: ; Tel.: +40-026-459-8363
| | - Alexandru Irimie
- “Ion Chiricuţă” Oncology Institute, 400015 Cluj-Napoca, Romania; (A.-R.P.); (C.L.); (C.P.); (A.I.); (L.R.); (A.M.); (Z.F.)
- Oncology Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, 400015 Cluj-Napoca, Romania
| | - Liliana Resiga
- “Ion Chiricuţă” Oncology Institute, 400015 Cluj-Napoca, Romania; (A.-R.P.); (C.L.); (C.P.); (A.I.); (L.R.); (A.M.); (Z.F.)
| | - Alina Munteanu
- “Ion Chiricuţă” Oncology Institute, 400015 Cluj-Napoca, Romania; (A.-R.P.); (C.L.); (C.P.); (A.I.); (L.R.); (A.M.); (Z.F.)
| | - Zsolt Fekete
- “Ion Chiricuţă” Oncology Institute, 400015 Cluj-Napoca, Romania; (A.-R.P.); (C.L.); (C.P.); (A.I.); (L.R.); (A.M.); (Z.F.)
- Oncology Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, 400015 Cluj-Napoca, Romania
| | - Radu Badea
- Medical Imaging Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, 400162 Cluj-Napoca, Romania;
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Xu Y, Lou X, Liang Y, Zhang S, Yang S, Chen Q, Xu Z, Zhao M, Li Z, Zhao K, Liu Z. Predicting Neoadjuvant Chemoradiotherapy Response in Locally Advanced Rectal Cancer Using Tumor-Infiltrating Lymphocytes Density. J Inflamm Res 2021; 14:5891-5899. [PMID: 34785927 PMCID: PMC8591410 DOI: 10.2147/jir.s342214] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 10/29/2021] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Accumulating evidence revealed the predictive value of tumor-infiltrating lymphocytes (TILs) for neoadjuvant chemoradiotherapy (nCRT) response in solid tumors. This study quantified TILs density using hematoxylin and eosin (H&E) stained whole-slide images (WSIs) and investigated the predictive value of TILs density on nCRT response in locally advanced rectal cancer (LARC) patients. PATIENTS AND METHODS Two hundred and ten patients diagnosed with LARC were enrolled in this study. The density of TILs in the stroma region was quantified by a semi-automatic method in WSIs. Patients were stratified into low-TILs and high-TILs groups using the median value as the threshold. The tumor regression grade (TRG) was used to assess the response to nCRT in tumor resected specimens. Based on TRG, patients were classified into major-responder (TRG 0-1) and non-responder (TRG 2-3) groups. RESULTS The TILs density was significantly correlated with the nCRT response. Specifically, patients with high-TILs tend to have a higher major-responder rate than the low-TILs group (63.8% vs 47.6%, P = 0.026). Univariate analysis showed the TILs density was a predictor for the nCRT response (high vs low, odds ratio [OR] =1.94, 95% confidence interval 1.12-3.37, P = 0.019), and multivariate analysis further confirmed the correlation (adjusted odds ratio [AOR] = 2.41, 1.28-4.56, P = 0.007). CONCLUSION Patients with a high-TIL density have a higher major-responder rate than the low-TILs group, indicating patients with a strong immune response benefit more from nCRT. This semi-automatic method can facilitate the individualized preoperative prediction of the TRG for LARC patients before nCRT.
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Affiliation(s)
- Yao Xu
- School of Medicine, South China University of Technology, Guangzhou, 510006, People’s Republic of China
- Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, People’s Republic of China
| | - Xiaoying Lou
- Department of Pathology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510665, People’s Republic of China
| | - Yanting Liang
- Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, People’s Republic of China
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, People’s Republic of China
| | - Shenyan Zhang
- Department of Pathology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510665, People’s Republic of China
| | - Shangqing Yang
- School of Life Science and Technology, Xidian University, Xian, 710071, People’s Republic of China
| | - Qicong Chen
- Institute of Computing Science and Technology, Guangzhou University, Guangzhou, 510006, People’s Republic of China
| | - Zeyan Xu
- School of Medicine, South China University of Technology, Guangzhou, 510006, People’s Republic of China
- Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, People’s Republic of China
| | - Minning Zhao
- Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, People’s Republic of China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, 510080, People’s Republic of China
| | - Zhenhui Li
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, 650118, People’s Republic of China
| | - Ke Zhao
- Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, People’s Republic of China
| | - Zaiyi Liu
- School of Medicine, South China University of Technology, Guangzhou, 510006, People’s Republic of China
- Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, People’s Republic of China
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12
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Gao T, Zou C, Li Y, Jiang Z, Tang X, Song X. A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging. Int J Mol Sci 2021; 22:11559. [PMID: 34768990 PMCID: PMC8584005 DOI: 10.3390/ijms222111559] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/12/2021] [Accepted: 10/23/2021] [Indexed: 02/08/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging tool which allows the specific detection of metabolites that contain exchangeable amide, amine, and hydroxyl protons. Decades of development have progressed CEST imaging from an initial concept to a clinical imaging tool that is used to assess tumor metabolism. The first translation efforts involved brain imaging, but this has now progressed to imaging other body tissues. In this review, we summarize studies using CEST MRI to image a range of tumor types, including breast cancer, pelvic tumors, digestive tumors, and lung cancer. Approximately two thirds of the published studies involved breast or pelvic tumors which are sites that are less affected by body motion. Most studies conclude that CEST shows good potential for the differentiation of malignant from benign lesions with a number of reports now extending to compare different histological classifications along with the effects of anti-cancer treatments. Despite CEST being a unique 'label-free' approach with a higher sensitivity than MR spectroscopy, there are still some obstacles for implementing its clinical use. Future research is now focused on overcoming these challenges. Vigorous ongoing development and further clinical trials are expected to see CEST technology become more widely implemented as a mainstream imaging technology.
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Affiliation(s)
- Tianxin Gao
- School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China; (T.G.); (C.Z.); (Z.J.)
| | - Chuyue Zou
- School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China; (T.G.); (C.Z.); (Z.J.)
| | - Yifan Li
- Center for Biomedical Imaging Research, School of Medicine, Tsinghua University, Beijing 100084, China;
| | - Zhenqi Jiang
- School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China; (T.G.); (C.Z.); (Z.J.)
| | - Xiaoying Tang
- School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China; (T.G.); (C.Z.); (Z.J.)
| | - Xiaolei Song
- Center for Biomedical Imaging Research, School of Medicine, Tsinghua University, Beijing 100084, China;
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