ArticleCancer imaging : the official publication of the International Cancer Imaging Society2021
Differentiating prostate cancer from benign prostatic hyperplasia using whole-lesion histogram and texture analysis of diffusion- and T2-weighted imaging.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Solitary fibrous tumor of the prostate: a case report and the systematic review of 74 published cases.Frontiers in oncology · 2025Pooled it
- Whole-volume histogram analysis of spectral-computed tomography iodine maps characterizes HER2 expression in gastric cancer.World journal of gastroenterology · 2024Trial
- Systematic effects of patient factors and scanner/protocol factors on a Restriction Spectrum Imaging (RSI) quantitative MRI biomarker for prostate cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Article
- Objective value of the apparent diffusion coefficient (ADC) map from ultrahigh b-value diffusion-weighted imaging (DWI) in 3T MRI as a non-invasive predictor for Gleason score in prostate cancer.Quantitative imaging in medicine and surgery · 2026Article
- Biparametric MRI in prostate cancer: utility of whole-prostate and whole-lesion histogram and texture analysis for clinically significant prostate cancer.Japanese journal of radiology · 2026Article
- A deep learning derived prostate zonal volume-based biomarker from T2-weighted MRI to distinguish between prostate cancer and benign prostatic hyperplasia.Medical physics · 2025Article
- Cancer detection in patients with prostate-specific antigen levels within the grey zone: can synthetic magnetic resonance imaging aid in the differentiation between prostate cancer and noncancerous lesions?Quantitative imaging in medicine and surgery · 2024Article
- Development and validation of a nomogram incorporating multi-parametric MRI and hematological indicators for discriminating benign from malignant central prostatic nodules: a retrospective analysis.American journal of translational research · 2024Article
- Assessment of chemotherapy resistance changes in human colorectal cancer xenografts in rats based on MRI histogram features.Frontiers in oncology · 2024Article
- Whole-tumour apparent diffusion coefficient (ADC) histogram analysis to identify MYCN-amplification in neuroblastomas: preliminary results.European radiology · 2022Article
- Synthetic correlated diffusion imaging hyperintensity delineates clinically significant prostate cancer.Scientific reports · 2022Article
- Radiomics-Based Machine Learning Models for Predicting P504s/P63 Immunohistochemical Expression: A Noninvasive Diagnostic Tool for Prostate Cancer.Frontiers in oncology · 2022Article
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundTo explore the usefulness of analyzing histograms and textures of apparent diffusion coefficient (ADC) maps and T2-weighted (T2W) images to differentiate prostatic cancer (PCa) from benign prostatic hyperplasia (BPH) using histopathology as the reference.
methodsNinety patients with PCa and 112 patients with BPH were included in this retrospective study. Differences in whole-lesion histograms and texture parameters of ADC maps and T2W images between PCa and BPH patients were evaluated using the independent samples t-test. The diagnostic performance of ADC maps and T2W images in being able to differentiate PCa from BPH was assessed using receiver operating characteristic (ROC) curves.
resultsThe mean, median, 5
conclusionsHistogram and texture parameters derived from the ADC maps and T2W images for entire prostatic lesions could be used as imaging biomarkers to differentiate PCa and BPH biologic characteristics, however, histogram parameters outperformed texture parameters in the diagnostic performance.
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