Journal Article

Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy

Finnegan, Mary E., Williams, Scott, Reynolds, Hayley M., Sun, Yu, Montazerolghaem, Maryam, Murphy, Declan G., Tadimalla, Sirisha, Haworth, Annette, Wang, Yu-Feng, Mitchell, Catherine

2022

Overview

Background Biologically targeted radiation therapy treatment planning requires voxel-wise characterisation of tumours. Dynamic contrast enhanced (DCE) DCE MRI has shown promise in defining voxel-level biological characteristics. In this study we consider the relative value of qualitative, semi-quantitative and quantitative assessment of DCE MRI compared with diffusion weighted imaging (DWI) and T2-weighted (T2w) imaging to detect prostate cancer at the voxel level. Methods Seventy prostate cancer patients had multiparametric MRI prior to radical prostatectomy, including T2w, DWI and DCE MRI. Apparent Diffusion Coefficient (ADC) maps were computed from DWI, and semi-quantitative and quantitative parameters computed from DCE MRI. Tumour location and grade were validated with co-registered whole mount histology. Kolmogorov–Smirnov tests were applied to determine whether MRI parameters in tumour and benign voxels were significantly different. Cohen’s d was computed to quantify the most promising biomarkers. The Parker and Weinmann Arterial Input Functions (AIF) were compared for their ability to best discriminate between tumour and benign tissue. Classifier models were used to determine whether DCE MRI parameters improved tumour detection versus ADC and T2w alone. Results All MRI parameters had significantly different data distributions in tumour and benign voxels. For low grade tumours, semi-quantitative DCE MRI parameter time-to-peak (TTP) was the most discriminating and outperformed ADC. For high grade tumours, ADC was the most discriminating followed by DCE MRI parameters Ktrans, the initial rate of enhancement (IRE), then TTP. Quantitative parameters utilising the Parker AIF better distinguished tumour and benign voxel values than the Weinmann AIF. Classifier models including DCE parameters versus T2w and ADC alone, gave detection accuracies of 78% versus 58% for low grade tumours and 85% versus 72% for high grade tumours. Conclusions Incorporating DCE MRI parameters with DWI and T2w gives improved accuracy for tumour detection at a voxel level. DCE MRI parameters should be used to spatially characterise tumour biology for biologically targeted radiation therapy treatment planning.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Accuracy / Biological markers / Biomarkers / Biomarkers, Tumor / Cancer Research / Cancer therapies / Classifiers / Comparative analysis / Computation / Contrast Media / Diffusion coefficient / Diffusion Magnetic Resonance Imaging - methods / Drunk driving / Dynamic contrast enhanced MRI / Histology / Histopathology / Humans / Imaging / Imaging biomarker / Magnetic resonance imaging / Magnetic Resonance Imaging - methods / Male / Mathematical models / Medical imaging / Medicine / Medicine & Public Health / Multiparametric Magnetic Resonance Imaging / Nuclear Medicine / Oncology / Parameters / Patients / Pharmacokinetics / Prostate cancer / Prostatic Neoplasms - pathology / Radiation / Radiation therapy / Radiation therapy / Radiology / Radiotherapy / Registration / Research Article / Software / Tumors