Dataset Information

Development and testing quantitative metrics from multi-parametric magnetic resonance imaging that predict Gleason score for prostate tumors.

ABSTRACT:

Background

Radiologists currently subjectively examine multi-parametric magnetic resonance imaging (MRI) to detect possible clinically significant lesions using the Prostate Imaging Reporting and Data System (PI-RADS) protocol. The assessment of imaging, however, relies on the experience and judgement of radiologists creating opportunity for inter-reader variability. Quantitative metrics, such as z-score and signal to clutter ratio (SCR), are therefore needed.

Methods

Multi-parametric MRI (T1, T2, diffusion, dynamic contrast-enhanced images) were resampled, rescaled, translated, and stitched to form spatially registered multi-parametric cubes for patients undergoing radical prostatectomy. Multi-parametric signatures that characterize prostate tumors were inserted into z-score and SCR. The multispectral covariance matrix was computed for the outlined normal prostate. The z-score from each MRI image was computed and summed. To reduce noise in the covariance matrix, following matrix decomposition, the noisy eigenvectors were removed. Also, regularization and modified regularization was applied to the covariance matrix by minimizing the discrimination score. The filtered and regularized covariance matrices were inserted into the SCR calculation. The z-score and SCR were quantitatively compared to Gleason scores from clinical pathology assessment of the histology of sectioned wholemount prostates.

Results

Twenty-six consecutive patients were enrolled in this retrospective study. Median patient age was 60 years (range, 49 to 75 years), median prostate-specific antigen (PSA) was 5.8 ng/mL (range, 2.3 to 23.7 ng/mL), and median Gleason score was 7 (range, 6 to 9). A linear fit of the summed z-score against Gleason score found a correlation of R=0.48 and a P value of 0.015. A linear fit of the SCR from regularizing covariance matrix against Gleason score found a correlation of R=0.39 and a P value of 0.058. The SCR employing the modified regularizing covariance matrix against Gleason score found a correlation of R=0.52 and a P value of 0.007. A linear fit of the SCR from filtering out 3 and 4 eigenvectors from the covariance matrix against Gleason score found correlations of R=0.50 and 0.44, respectively, and P values of 0.011 and 0.027, respectively.

Conclusions

Z-score and SCR using filtered and regularized covariance matrices derived from spatially registered multi-parametric MRI correlates with Gleason score with highly significant P values.

SUBMITTER: Mayer R

PROVIDER: S-EPMC8899928 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Publications

Development and testing quantitative metrics from multi-parametric magnetic resonance imaging that predict Gleason score for prostate tumors.

Mayer Rulon R Simone Charles B CB Turkbey Baris B Choyke Peter P

Quantitative imaging in medicine and surgery 20220301 3

<h4>Background</h4>Radiologists currently subjectively examine multi-parametric magnetic resonance imaging (MRI) to detect possible clinically significant lesions using the Prostate Imaging Reporting and Data System (PI-RADS) protocol. The assessment of imaging, however, relies on the experience and judgement of radiologists creating opportunity for inter-reader variability. Quantitative metrics, such as z-score and signal to clutter ratio (SCR), are therefore needed.<h4>Methods</h4>Multi-parame ...[more]

PMID: 35284265

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Project description:ObjectiveThe aim of this study was to characterize response to photodynamic therapy (PDT) in a mouse cancer model using a multi-parametric quantitative MRI protocol and to identify MR parameters as potential biomarkers for early assessment of treatment outcome.MethodsCT26.WT colon carcinoma tumors were grown subcutaneously in the hind limb of BALB/c mice. Therapy consisted of intravenous injection of the photosensitizer Bremachlorin, followed by 10 min laser illumination (200 mW/cm2) of the tumor 6 h post injection. MRI at 7 T was performed at baseline, directly after PDT, as well as at 24 h, and 72 h. Tumor relaxation time constants (T1 and T2) and apparent diffusion coefficient (ADC) were quantified at each time point. Additionally, Gd-DOTA dynamic contrast-enhanced (DCE) MRI was performed to estimate transfer constants (Ktrans) and volume fractions of the extravascular extracellular space (ve) using standard Tofts-Kermode tracer kinetic modeling. At the end of the experiment, tumor viability was characterized by histology using NADH-diaphorase staining.ResultsThe therapy induced extensive cell death in the tumor and resulted in significant reduction in tumor growth, as compared to untreated controls. Tumor T1 and T2 relaxation times remained unchanged up to 24 h, but decreased at 72 h after treatment. Tumor ADC values significantly increased at 24 h and 72 h. DCE-MRI derived tracer kinetic parameters displayed an early response to the treatment. Directly after PDT complete vascular shutdown was observed in large parts of the tumors and reduced uptake (decreased Ktrans) in remaining tumor tissue. At 24 h, contrast uptake in most tumors was essentially absent. Out of 5 animals that were monitored for 2 weeks after treatment, 3 had tumor recurrence, in locations that showed strong contrast uptake at 72 h.ConclusionDCE-MRI is an effective tool for visualization of vascular effects directly after PDT. Endogenous contrast parameters T1, T2, and ADC, measured at 24 to 72 h after PDT, are also potential biomarkers for evaluation of therapy outcome.

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Project description:Background & aimsPeople with primary sclerosing cholangitis (PSC) have a variable and often progressive disease course that is associated with biliary and parenchymal changes. These changes are typically assessed by magnetic resonance imaging (MRI), including qualitative assessment of magnetic resonance cholangiopancreatography (MRCP). Our aim was to study the association of novel objective quantitative MRCP metrics with prognostic scores and patient outcomes.MethodsWe performed a retrospective study including 77 individuals with large-duct PSC with baseline MRCP images, which were postprocessed to obtain quantitative measures of bile ducts using MRCP+™. The participants' ANALI scores, liver stiffness by vibration-controlled transient elastography, and biochemical indices were collected at baseline. Adverse outcome-free survival was measured as the absence of decompensated cirrhosis, liver transplantation (LT), or liver-related death over a 12-year period. The prognostic value of MRCP+-derived metrics was assessed by Cox regression modelling.ResultsDuring a total of 386 patients-years, 16 cases of decompensation, 2 LTs, and 5 liver-related deaths were recorded. At baseline, around 50% of the patients were classified as being at risk of developing disease complications. MRCP+ metrics, particularly those describing the severity of bile duct dilatations, were correlated with all prognostic factors. Univariate analysis showed that MRCP+ metrics representing duct diameter, dilatations, and the percentage of ducts with strictures and/or dilatations were associated with survival. In a multivariable-adjusted analysis, the median duct diameter was significantly associated with survival (hazard ratio 10.9, 95% CI 1.3-90.3).ConclusionsMRCP+ metrics in people with PSC correlate with biochemical, elastographic, and radiological prognostic scores and are predictive of adverse outcome-free survival.Lay summaryIn this study, we assessed in people with primary sclerosing cholangitis (PSC) the association of novel objective quantitative MRCP metrics automatically provided by a software tool (MRCP+) with prognostic scores and patient outcomes. We observed that MRCP+ metrics in people with PSC correlate with biochemical, elastographic, and radiological prognostic scores and are predictive of adverse outcome-free survival.

Project description:Background & Aims Magnetic resonance cholangiopancreatography (MRCP) for evaluation of biliary disease currently relies on subjective assessment with limited prognostic value because of the lack of quantitative metrics. Artificial intelligence-enabled quantitative MRCP (MRCP+) is a novel technique that segments biliary anatomy and provides quantitative biliary tree metrics. This study investigated the utility of MRCP+ as a prognostic tool for the prediction of clinical outcomes in primary sclerosing cholangitis (PSC). Methods MRCP images of patients with PSC were post-processed using MRCP+ software. The duration between the MRCP and clinical event (liver transplantation or death) was calculated. Survival analysis and stepwise Cox regression were performed to investigate the optimal combination of MRCP+ metrics for the prediction of clinical outcomes. The resulting risk score was validated in a separate validation cohort and compared with an existing prognostic score (Mayo risk score). Results In this retrospective study, 102 patients were included in a training cohort and a separate 50 patients formed a validation cohort. Between the two cohorts, 34 patients developed clinical outcomes over a median duration of 3 years (23 liver transplantations and 11 deaths). The proportion of bile ducts with diameter 3–5 mm, total bilirubin, and aspartate aminotransferase were independently associated with transplant-free survival. Combined as a risk score, the overall discriminative performance of the MRCP+ risk score (M+BA) was excellent; area under the receiver operator curve 0.86 (95% CI: 0.77, 0.95) at predicting clinical outcomes in the validation cohort with a hazard ratio 5.8 (95% CI: 1.5, 22.1). This was superior to the Mayo risk score. Conclusions A composite score combining MRCP+ with total bilirubin and aspartate aminotransferase (M+BA) identified PSC patients at high risk of liver transplantation or death. Prospective studies are warranted to evaluate the clinical utility of this novel prognostic tool. Impact and Implications Primary sclerosis cholangitis (PSC) is a disease of the biliary tree where inflammation and fibrosis cause areas of narrowing (strictures) and expansion (dilatations) within the biliary ducts leading to liver failure and/or cancer (cholangiocarcinoma). In this study, we demonstrate that quantitative assessment of the biliary tree can better identify patients with PSC who are at high risk of either death or liver transplantation than a current blood-based risk score (Mayo risk score). Graphical abstract Highlights • Many people with PSC will require a liver transplant to extend their life but current stratification methods struggle to identify all patients at high-risk of progression to this stage, especially at the early stages of disease.• A novel post-processing technique (MRCP+) enables quantification of magnetic resonance cholangiopancreatography (MRCP) data, providing quantitative assessments of biliary anatomy and abnormality for enhanced monitoring of biliary diseases such as PSC.• A risk score comprised of the proportion of the bile ducts with diameter 3–5 mm, total bilirubin and aspartate aminotransferase (AST) was highly predictive of clinical outcomes in a validation cohort (hazard ratio = 5.8), outperforming the Mayo risk score.

Dataset Information

Development and testing quantitative metrics from multi-parametric magnetic resonance imaging that predict Gleason score for prostate tumors.

Background

Methods

Results

Conclusions

Publications

Development and testing quantitative metrics from multi-parametric magnetic resonance imaging that predict Gleason score for prostate tumors.

Similar Datasets

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