Objective: A cohort of high dose-rate (HDR) monotherapy patients was analyzed to (i) establish the frequency of non-malignant urethral stricture; (ii) explore the relation between stricture formation with the dose distribution along the length of the urethra, and MRI radiomics features of the prostate gland.
Methods: A retrospective review of treatment records of patients who received 19 Gy single fraction of HDR brachytherapy (BT) was carried out. A matched pair analysis used one control for each stricture case matched with pre-treatment International Prostate Symptom Score (IPSS) score, number of needles used and clinical target volume volume for each stricture case identified.For all data sets, pre-treatment weighted MRI images were used to define regions of interests along the urethra and within the whole prostate gland. MRI textural radiomics features-energy, contrast and homogeneity were selected. Wilcoxon signed-rank test was performed to investigate significant differences in dosimetric parameters and MRI radiomics feature values between cases and controls.
Results: From Nov 2010 to July 2017, there were 178 patients treated with HDR BT delivering 19 Gy in a single dose. With a median follow-up of 28.2 months, a total of 5/178 (3%) strictures were identified.10 patients were included in the matched pair analysis. The urethral dosimetric parameters investigated were not statistically different between cases and controls ( > 0.05). With regards to MRI radiomics feature analysis, significant differences were found in contrast and homogeneity between cases and controls ( < 0.05). However, this did not apply to the energy feature ( = 0.28).
Conclusion: In this matched pair analysis, no association between post-treatment stricture and urethral dosimetry was identified. Our study generated a preliminary clinical hypothesis suggesting that the MRI radiomics features of homogeneity and contrast of the prostate gland can potentially identify patients who develop strictures after HDR BT. Although the sample size is small, this warrants further validation in a larger patient cohort.
Advances In Knowledge: Urethral stricture has been reported as a specific late effect with prostate HDR brachytherapy. Our study reported a relatively low stricture rate of 3% and no association between post-treatment stricture and urethral dosimetry was identified. MRI radiomics features can potentially identify patients who are more prone to develop strictures.
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http://dx.doi.org/10.1259/bjr.20190760 | DOI Listing |
World J Gastrointest Oncol
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Department of Hepatobiliary and Pancreaticosplenic Surgery, Jingzhou Hospital Affiliated to Yangtze University, Jingzhou 434100, Hubei Province, China.
Background: The liver, as the main target organ for hematogenous metastasis of colorectal cancer, early and accurate prediction of liver metastasis is crucial for the diagnosis and treatment of patients. Herein, this study aims to investigate the application value of a combined machine learning (ML) based model based on the multiparameter magnetic resonance imaging for prediction of rectal metachronous liver metastasis (MLM).
Aim: To investigate the efficacy of radiomics based on multiparametric magnetic resonance imaging images of preoperative first diagnosed rectal cancer in predicting MLM from rectal cancer.
Transl Cancer Res
December 2024
Department of Radiology, Shanghai Chest Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
Background: The pathological sub-classification of lung cancer is crucial in diagnosis, treatment and prognosis for patients. Quick and timely identification of pathological subtypes from imaging examinations rather than histological tests could help guiding therapeutic strategies. The aim of the study is to construct a non-invasive radiomics-based model for predicting the subtypes of lung cancer on brain metastases (BMs) from multiple magnetic resonance imaging (MRI) sequences.
View Article and Find Full Text PDFSci Data
January 2025
Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.
Pituitary neuroendocrine tumors remain one of the most common intracranial tumors. While radiomic research related to pituitary tumors is progressing, public data sets for external validation remain scarce. We introduce an open dataset comprising high-resolution T1 contrast-enhanced MR scans of 136 patients with pituitary tumors, annotated for tumor segmentation and accompanied by clinical, radiological and pathological metadata.
View Article and Find Full Text PDFAcad Radiol
January 2025
Department of Radiology, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China (X.W., X.C., Y.C., S.C., M.W.). Electronic address:
Rationale And Objectives: To develop and validate a deep learning radiomics nomogram (DLRN) based on T2-weighted MRI to distinguish between borderline ovarian tumors (BOTs) and stage I epithelial ovarian cancer (EOC) preoperatively.
Materials And Methods: This retrospective multicenter study enrolled 279 patients from three centers, divided into a training set (n = 207) and an external test set (n = 72). The intra- and peritumoral radiomics analysis was employed to develop a combined radiomics model.
Insights Imaging
January 2025
Department of Radiology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, China.
Objective: To evaluate the feasibility of utilizing artificial intelligence (AI)-predicted biparametric MRI (bpMRI) image features for predicting the aggressiveness of prostate cancer (PCa).
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