Objective: To explore the value of intravoxel incoherent motion (IVIM) sequences in predicting intra-tumoral tertiary lymphoid structures (TLSs).
Materials And Methods: This prospective study pre-operatively enrolled hepatocellular carcinoma (HCC) patients who underwent magnetic resonance imaging including IVIM sequences, between January 2019 and April 2021. Intra-tumoral TLSs presence was assessed on pathological slide images. Clinical and radiological characteristics were collected. IVIM quantitative parameters and radiomics features were obtained based on the whole delineated tumor volume. By using feature selection techniques, 22 radiomics features, clinical-radiological features (lymphocyte count and satellite nodules), and IVIM parameters (apparent diffusion coefficient (ADC_90Percentile), perfusion fraction (f_Maximum)) were selected. The logistic regression algorithm was used to construct the prediction model based on the combination of these features. The diagnostic performance was assessed using the area under the receiver operating characteristic (AUC). The recurrence-free survival (RFS) was evaluated with Kaplan-Meier curves.
Results: A total of 168 patients were divided into training (n=128) and testing (n=40) cohorts (mean age: 56.83±14.43 years; 149 [88.69%] males; 130 TLSs+). In testing cohort, the model combining multimodal features demonstrated a good performance (AUC: 0.86) and significantly outperformed models based on single-modality features. The model based on radiomics features (AUC: 0.80) had better performance than other features, including IVIM parameter maps (ADC_90Percentile and f_Maximum, AUC: 0.72) and clinical-radiological characteristics (satellite nodules and lymphocyte counts, AUC: 0.59). TLSs+ patients had higher RFS than TSLs- patients (all <0.05).
Conclusion: The nomogram based on the proposed model can be used as a pre-operative predictive biomarker of TLSs.
Critical Relevance Statement: The nomogram incorporating IVIM sequences may serve as a pre-operative predictive biomarker of intra-tumoral tertiary lymphoid structure (TLS) status.
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http://dx.doi.org/10.2147/JHC.S508357 | DOI Listing |
Rheumatology (Oxford)
March 2025
Department of General Internal Medicine, UZ Leuven, Leuven, Belgium.
The breakout session "Imaging in Disease Assessment" featured six abstracts on imaging advancements for vasculitis. Disease extent on cranial MRI and its association with visual complications in giant cell arteritis (GCA) was evaluated, introducing the Propensity for Enhancement for GCA (P EG) score to assess inflammation. Predictors of remission and relapse in chronic periaortitis were analyzed, suggesting the potential for tailored treatment approaches.
View Article and Find Full Text PDFInt J Gen Med
March 2025
Medical Imaging Center, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, Shaanxi Province, People's Republic of China.
Background: Cervical cancer remains a major cause of mortality among women globally, with lymph node metastasis (LNM) being a critical determinant of patient prognosis.
Methods: In this study, MRI scans from 153 cervical cancer patients between January 2018 and January 2024 were analyzed. The patients were assigned to two groups: 103 in the training cohort; 49 in the validation cohort.
J Thorac Imaging
March 2025
Department of Radiology, the First Affiliated Hospital, College of Medicine, Zhejiang University.
Purpose: To develop and validate an accurate computed tomography-based radiomics model for predicting high-grade (micropapillary/solid) patterns in T1-stage lung invasive adenocarcinoma (IAC) after propensity score matching (PSM).
Materials And Methods: We enrolled 546 participants from 2 cohorts with histologically diagnosed lung IAC after complete surgical resection between January 2020 and August 2021. The patients were divided into high-grade and non-high-grade groups and matched using PSM.
Acad Radiol
March 2025
Department of Radiology, The Affiliated Huai'an Clinical College of Xuzhou Medical University, Huai'an, Jiangsu Province, China (Q.W., C.-C.H., H.-W.X., G.-J.B.). Electronic address:
Rationale And Objectives: Accurate determination of human epidermal growth factor receptor 2 (HER2) expression is critical for guiding targeted therapy in breast cancer. This study aimed to develop and validate a deep learning (DL)-based decision-making visual biomarker system (DM-VBS) for predicting HER2 status using radiomics and DL features derived from magnetic resonance imaging (MRI) and mammography (MG).
Materials And Methods: Radiomics features were extracted from MRI, and DL features were derived from MG.
Neuroscience
March 2025
Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, 533000 Baise, China; Life Science and Clinical Medicine Research Center, Affiliated Hospital of Youjiang Medical University for Nationalities, 533000 Baise, China. Electronic address:
Cognitive impairment in cerebral small vessel disease (CSVD) progresses subtly but carries significant clinical consequences, necessitating effective diagnostic tools. This study developed and validated predictive models for CSVD-related cognitive impairment using deep transfer learning (DTL) and radiomics features extracted from hippocampal 3D T1-weighted MRI. A total of 145 CSVD patients and 99 control subjects were enrolled in the study.
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