Diffusion-weighted imaging (DWI) has not been well explored in differentiation of malignant from benign breast lesions. The aims of this study were to examine the role of apparent diffusion coefficient (ADC) values in differentiation of malignant from benign tumors and distinguishing histological subtypes of malignant lesions, and to determine correlations between ADC values and breast tumors structure. This cohort-study included 174 female patients who underwent contrast-enhanced breast MR examination on a 3T scanner and were divided into two groups: patient group (114 patients with proven tumors) and control group (60 healthy patients). One-hundred-thirty-nine lesions (67 malignant and 72 benign) were detected and pathohistologically analyzed. Differences between variables were tested using chi-square test; correlations were determined using Pearson's correlation test. For determination of cut off values for diagnostic potential, Receiver Operating Characteristic curves were constructed. Statistical significance was set at < 0.05. Mean ADC values were significantly lower in malignant compared to benign lesions (0.68 × 10mm/s vs. 1.12 × 10mm/s, < 0.001). The cut off value of ADC for benign lesions was 0.792 × 10mm/s (sensitivity 98.6%, specificity 65.7%), and for malignant 0.993 × 10mm/s (98.5, 80.6%). There were no significant correlations between malignant lesion subtypes and ADC values. DWI is a clinically useful tool for differentiation of malignant from benign lesions based on mean ADC values. The cut off value for benign lesions was higher than reported recently, due to high amount of fibrosis in included benign lesions. Finally, ADC values might have implications in determination of the biological nature of the malignant lesions.
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http://dx.doi.org/10.3389/fonc.2020.00332 | DOI Listing |
Radiother Oncol
December 2024
Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Cluster of Excellence "Machine Learning", University of Tübingen, Tübingen, Germany. Electronic address:
Purpose: To retrain a model based on a previously identified prognostic imaging biomarker using apparent diffusion coefficient (ADC) values from diffusion-weighted magnetic resonance imaging (DW-MRI) in a preclinical setting and validate the model using clinical DW-MRI data of patients with locally advanced head-and-neck cancer (HNC) acquired before radiochemotherapy.
Material And Methods: A total of 31 HNC patients underwent T2-weighted and DW-MRI using 3 T MRI before radiochemotherapy (35x2Gy). Gross tumor volumes (GTV) were delineated based on T2-weighted and b500 images.
Jpn J Radiol
December 2024
Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan.
Objective: The purpose of this study was to evaluate MRI findings of ovarian endometrioid carcinoma (OEC) as a predictor of histological grade.
Materials And Methods: This study included 60 patients with histopathologically confirmed OEC (20, 30, and 10 with grades 1, 2, and 3, respectively). Clinical and MRI results were retrospectively reviewed.
Jpn J Radiol
December 2024
Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawaharacho, Kyoto, 6068507, Japan.
Purpose: To compare quantitative values and image quality between single-shot echo-planar imaging (SS-EPI) diffusion-weighted imaging (DWI) and two-dimensional turbo gradient- and spin-echo DWI with non-Cartesian BLADE trajectory (TGSE-BLADE DWI) in patients with epidermoid cyst.
Methods: Patients with epidermoid cyst who underwent both SS-EPI DWI and TGSE-BLADE DWI were included in this study. Two raters placed ROIs encircling the entire epidermoid cyst on SS-EPI DWI, and then on TGSE-BLADE DWI.
Sci Rep
December 2024
IRCCS SYNLAB SDN, Via E. Gianturco 113, 80143, Naples, Italy.
Uterine corpus endometrial carcinoma (EC) is one of the most common malignancies in the female reproductive system, characterized by tumor heterogeneity at both radiological and pathological scales. Both radiomics and pathomics have the potential to assess this heterogeneity and support EC diagnosis. This study examines the correlation between radiomics features from Apparent Diffusion Coefficient (ADC) maps and post-contrast T1 (T1C) images with pathomic features from pathology images in 32 patients from the CPTAC-UCEC database.
View Article and Find Full Text PDFAcad Radiol
December 2024
Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Fujian Key Laboratory of Precision Medicine for Cancer, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China (X-Y.X., N.X.). Electronic address:
Rationale And Objectives: To assess the predictive value of MRI-based radiomics of periprostatic fat (PPF) and tumor lesions for predicting Gleason score (GS) upgrading from biopsy to radical prostatectomy (RP) in prostate cancer (PCa).
Methods: A total of 314 patients with pathologically confirmed prostate cancer (PCa) after radical prostatectomy (RP) were included in the study. The patients were randomly assigned to the training cohort (n = 157) and the validating cohort (n = 157) in a 1:1 ratio.
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