Biopsy-free AI-aided precision MRI assessment in prediction of prostate cancer biochemical recurrence.

BACKGROUND: To investigate the predictive ability of high-throughput MRI with deep survival networks for biochemical recurrence (BCR) of prostate cancer (PCa) after prostatectomy. METHODS: Clinical-MRI and histopathologic data of 579 (train/test, 463/116) PCa patients were retrospectively collected. The deep survival network (iBCR-Net) is based on stepwise processing operations, which first built an MRI radiomics signature (RadS) for BCR, and predicted the T3 stage and lymph node metastasis (LN+) of tumour using two predefined AI models. Subsequently, clinical, imaging and histopathological variables were integrated into iBCR-Net for BCR prediction. RESULTS: RadS, derived from 2554 MRI features, was identified as an independent predictor of BCR. Two predefined AI models achieved an accuracy of 82.6% and 78.4% in staging T3 and LN+. The iBCR-Net, when expressed as a presurgical model by integrating RadS, AI-diagnosed T3 stage and PSA, can match a state-of-the-art histopathological model (C-index, 0.81 to 0.83 vs 0.79 to 0.81, p > 0.05); and has maximally 5.16-fold, 12.8-fold, and 2.09-fold (p < 0.05) benefit to conventional D'Amico score, the Cancer of the Prostate Risk Assessment (CAPRA) score and the CAPRA Postsurgical score. CONCLUSIONS: AI-aided iBCR-Net using high-throughput MRI can predict PCa BCR accurately and thus may provide an alternative to the conventional method for PCa risk stratification.

Longitudinal Multiparametric MRI Assessment of Irradiated Salivary Gland in a Rat Model: Correlated With Histological Findings.

BACKGROUND: Several magnetic resonance imaging (MRI) sequences have been applied to assess injured glands but without histological validation. PURPOSE: To evaluate longitudinal changes in multiparametric MRI (mp-MRI) of irradiated salivary glands in a rat model and investigate correlations between mp-MRI and histological findings. STUDY TYPE: Prospective. ANIMAL MODEL: Submandibular glands of 36 rats were radiated using a single dose of 15 Gy X-ray (irradiation [IR] group), and 6 other rats were enrolled into sham-IR group. mp-MRI were scanned 1 day after sham-IR (n = 6), or 1, 2, 4, 8, 12, 24 weeks after IR (n = 36, 6 per subgroup). FIELD STRENGTH/SEQUENCE: A 3.0-T/Diffusion-weighted imaging (DWI), readout-segmented echo-planar imaging (EPI) sequence; intravoxel incoherent motion DWI, single-shot EPI sequence; T1 mapping, dual-flip-angle gradient-echo sequence with volumetric interpolated breath-hold examination; T2 mapping, turbo spin-echo sequence. ASSESSMENT: Parameters including apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D* ), perfusion fraction (f), T1 and T2 value were obtained. Histological examinations, including hematoxylin and eosin staining (for acinar cell fraction [AC%] detection), Masson's trichrome staining (for degree of fibrosis [F%] determination) and CD34-immunohistochemical staining (for microvessel density [MVD] calculation), were performed at corresponding time points. STATISTICAL TESTS: One-way analysis of variance was used to compare the mp-MRI and histological parameters among different groups. Spearman correlation analysis was applied to determine the correlation between mp-MRI and histological parameters. Two-sided P ≤ 0.05 was considered statistically significant. RESULTS: Changes of mp-MRI parameters (ADC, D, D* , f, T1, T2) and histological results (AC%, F%, MVD) among the seven groups were all significant. ADC, D, and T2 values negatively correlated with AC% (ADC, r = -0.728; D, r = -0.773; T2, r = -0.600), f positively correlated with MVD (r = 0.496), and T1 values positively correlated with F% (r = 0.714). DATA CONCLUSION: mp-MRI might be able to noninvasively and quantitatively evaluate the dynamic pathological changes within the irradiated salivary glands. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.