ArticleDiagnostic and interventional radiology (Ankara, Turkey)2023
Prostate zones and tumor morphological parameters on magnetic resonance imaging for predicting the tumor-stage diagnosis of prostate cancer.
Article in Diagnostic and interventional radiology (Ankara, Turkey), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Detecting Clinically Significant Prostate Cancer in PI-RADS 3 Lesions Using T2w-Derived Radiomics Feature Maps in 3T Prostate MRI.Current oncology (Toronto, Ont.) · 2024Article
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10 authors.
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Abstract
purposeTo determine whether the morphological parameters of prostate zones and tumors on magnetic resonance imaging (MRI) can predict the tumor-stage (T-stage) of prostate cancer (PCa) and establish an optimal T-stage diagnosis protocol based on three-dimensional reconstruction and quantization after image segmentation.
methodsA dataset of the prostate MRI scans and clinical data of 175 patients who underwent biopsy and had pathologically proven PCa from January 2018 to November 2020 was retrospectively analyzed. The authors manually segmented and measured the volume, major axis, and cross-sectional area of the peripheral zone (PZ), transition zone, central zone (CZ), anterior fibromuscular stroma, and tumor. The differences were evaluated by the One-Way analysis of variance, Pearson's chi-squared test, or independent samples t-test. Spearman's correlation coefficient and receiver operating characteristic curve analyses were also performed. The cut-off values of the T-stage diagnosis were generated using Youden's J index.
resultsThe prostate volume (PV), PZ volume (PZV), CZ volume, tumor's major axis (TA), tumor volume (TV), and volume ratio of the TV and PV were significantly different among stages T1 to T4. The cut-off values of the PV, PZV, CZV, TA, TV, and the ratio of TV/PV for the discrimination of the T1 and T2 stages were 53.63 cm
conclusionThe morphological parameters of the prostate zones and tumors on the MRIs are simple and valuable diagnostic factors for predicting the T-stage of patients with PCa, which can help make accurate diagnoses and lateral treatment decisions.
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