Year: 2025
Type: article
Abstract: Clinical application of AI/DL-aided acquisitions for quantitative bi-parametric (q-bp)MRI requires validation and harmonization across vendor platforms. An AI/DL-accelerated q-bpMRI, including 5-echo T2 and 4-b-value apparent diffusion coefficient (ADC) mapping, was implemented on two 3T clinical scanners by two vendors alongside the qualitative standard-of-care (SOC) MRI protocols for six patients with biopsy-confirmed prostate cancer (PCa). AI/DL versus SOC bpMRI image quality was compared for MR-visible PCa lesions on a 4-point Likert-like scale. Quantitative validation and protocol bias assessment were performed using a multiparametric phantom with reference T2 and diffusion kurtosis values mimicking prostate tissue ranges. Six-minute q-bpMRI achieved acceptable diagnostic quality comparable to the SOC. Better SNR was observed for DL/AI versus SOC ADC with method-dependent distortion susceptibility and resolution enhancement. The measured biases were unaffected by AI/DL reconstruction and related to acquisition protocol parameters: constant for spin-echo T2 (−7 ms to +5 ms) and ADC (4b-fit: −0.37 µm2/ms and 2b-fit: −0.19 µm2/ms), while nonlinear for echo-planar T2 (−37 ms to +14 ms). Measured phantom ADC bias dependence on b-value range was consistent with that observed for PCa lesions. Bias correction harmonized lesion T2 and ADC values across different AI/DL-aided q-bpMRI acquisitions. The developed workflow enables harmonization of AI/DL-accelerated quantitative T2 and ADC mapping in multi-vendor clinical settings.
Source: Sensors
DOI: 10.3390/s25185858
Authors: Dariya Malyarenko, Scott D. Swanson, Jacob Richardson, Suzan Lowe, James O’Connor, Yun Jiang, Reve Chahine, Shane A. Wells, Thomas L. Chenevert
Institutions: University of Michigan, Michigan Medicine
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,137
Awards: G1118722989, G4166915956, G5504807245, G7520216043, G9000121009, Correction of Diffusion Gradient Bias in Quantitative Diffusivity Metrics for MultiPlatform Clinical Oncology Trials, Quantitative MRI to automatically delineate intraprostatic tumor for radiation therapy, 3D High Resolution Magnetic Resonance Fingerprinting for Prostate Cancer
OpenAlex ID: W4414353765
