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Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer.

ABSTRACT: The risk of poor post-operative outcome and the benefits of surgical resection as a curative therapy require careful assessment by the clinical care team for patients with primary and secondary liver cancer. Advances in surgical techniques have improved patient outcomes but identifying which individual patients are at greatest risk of poor post-operative liver performance remains a challenge. Here we report results from a multicentre observational clinical trial (ClinicalTrials.gov NCT03213314) which aimed to inform personalised pre-operative risk assessment in liver cancer surgery by evaluating liver health using quantitative multiparametric magnetic resonance imaging (MRI). We combined estimation of future liver remnant (FLR) volume with corrected T1 (cT1) of the liver parenchyma as a representation of liver health in 143 patients prior to treatment. Patients with an elevated preoperative liver cT1, indicative of fibroinflammation, had a longer post-operative hospital stay compared to those with a cT1 within the normal range (6.5 vs 5 days; p = 0.0053). A composite score combining FLR and cT1 predicted poor liver performance in the 5 days immediately following surgery (AUROC = 0.78). Furthermore, this composite score correlated with the regenerative performance of the liver in the 3 months following resection. This study highlights the utility of quantitative MRI for identifying patients at increased risk of poor post-operative liver performance and a longer stay in hospital. This approach has the potential to inform the assessment of individualised patient risk as part of the clinical decision-making process for liver cancer surgery.

SUBMITTER: Mole DJ

PROVIDER: S-EPMC7710097 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer.

Mole Damian J DJ Fallowfield Jonathan A JA Sherif Ahmed E AE Kendall Timothy T Semple Scott S Kelly Matt M Ridgway Gerard G Connell John J JJ McGonigle John J Banerjee Rajarshi R Brady J Michael JM Zheng Xiaozhong X Hughes Michael M Neyton Lucile L McClintock Joanne J Tucker Garry G Nailon Hilary H Patel Dilip D Wackett Anthony A Steven Michelle M Welsh Fenella F Rees Myrddin M

PloS one 20201202 12

The risk of poor post-operative outcome and the benefits of surgical resection as a curative therapy require careful assessment by the clinical care team for patients with primary and secondary liver cancer. Advances in surgical techniques have improved patient outcomes but identifying which individual patients are at greatest risk of poor post-operative liver performance remains a challenge. Here we report results from a multicentre observational clinical trial (ClinicalTrials.gov NCT03213314) ...[more]

PMID: 33264327

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Project description:BackgroundPrimary sclerosing cholangitis, autoimmune hepatitis and autoimmune sclerosing cholangitis are forms of chronic, progressive autoimmune liver disease (AILD) that can affect the pediatric population.ObjectiveTo determine whether quantitative MRI- and laboratory-based biomarkers are associated with conventional imaging findings of portal hypertension (radiologic portal hypertension) in children and young adults with AILD.Materials and methodsForty-four patients with AILD enrolled in an institutional registry underwent a research abdominal MRI examination at 1.5 tesla (T). Five quantitative MRI techniques were performed: liver MR elastography, spleen MR elastography, liver iron-corrected T1 mapping, liver T2 mapping, and liver diffusion-weighted imaging (DWI, quantified as apparent diffusion coefficients). Two anatomical sequences were used to document splenomegaly, varices and ascites. We calculated aspartate aminotransferase (AST)-to-platelet ratio index (APRI) and fibrosis-4 (FIB-4) scores - laboratory-based biomarkers of liver fibrosis. We used receiver operating characteristic (ROC) curve analyses to establish the diagnostic performance of quantitative MRI and laboratory biomarkers for indicating the presence of radiologic portal hypertension.ResultsTwenty-three (52%) patients were male; mean age was 15.2±4.0 years. Thirteen (30%) patients had radiologic portal hypertension. Liver and spleen stiffness demonstrated the greatest diagnostic performance for indicating the presence of portal hypertension (area-under-the-ROC-curve [AUROC]=0.98 and 0.96, respectively). The APRI and FIB-4 scores also demonstrated good diagnostic performance (AUROC=0.87 and 0.88, respectively).ConclusionMRI-derived measures of liver and spleen stiffness as well as laboratory-based APRI and FIB-4 scores are highly associated with imaging findings of portal hypertension in children and young adults with AILD and thus might be useful for predicting portal hypertension impending onset and directing personalized patient management.

Project description:ObjectivesThe authors developed a fully automated framework to quantify myocardial blood flow (MBF) from contrast-enhanced cardiac magnetic resonance (CMR) perfusion imaging and evaluated its diagnostic performance in patients.BackgroundFully quantitative CMR perfusion pixel maps were previously validated with microsphere MBF measurements and showed potential in clinical applications, but the methods required laborious manual processes and were excessively time-consuming.MethodsCMR perfusion imaging was performed on 80 patients with known or suspected coronary artery disease (CAD) and 17 healthy volunteers. Significant CAD was defined by quantitative coronary angiography (QCA) as ≥70% stenosis. Nonsignificant CAD was defined by: 1) QCA as <70% stenosis; or 2) coronary computed tomography angiography as <30% stenosis and a calcium score of 0 in all vessels. Automatically generated MBF maps were compared with manual quantification on healthy volunteers. Diagnostic performance of the automated MBF pixel maps was analyzed on patients using absolute MBF, myocardial perfusion reserve (MPR), and relative measurements of MBF and MPR.ResultsThe correlation between automated and manual quantification was excellent (r = 0.96). Stress MBF and MPR in the ischemic zone were lower than those in the remote myocardium in patients with significant CAD (both p < 0.001). Stress MBF and MPR in the remote zone of the patients were lower than those in the normal volunteers (both p < 0.001). All quantitative metrics had good area under the curve (0.864 to 0.926), sensitivity (82.9% to 91.4%), and specificity (75.6% to 91.1%) on per-patient analysis. On a per-vessel analysis of the quantitative metrics, area under the curve (0.837 to 0.864), sensitivity (75.0% to 82.7%), and specificity (71.8% to 80.9%) were good.ConclusionsFully quantitative CMR MBF pixel maps can be generated automatically, and the results agree well with manual quantification. These methods can discriminate regional perfusion variations and have high diagnostic performance for detecting significant CAD. (Technical Development of Cardiovascular Magnetic Resonance Imaging; NCT00027170).

Project description:Background: Multiparametric magnetic resonance imaging (mpMRI) has emerged as a non-invasive modality to diagnose and monitor prostate cancer. Quantitative metrics on the regions of abnormality have shown to be useful descriptors to discriminate clinically significant cancers. In this study, we evaluate the reproducibility of quantitative imaging features using repeated mpMRI on the same patients. Methods: We retrospectively obtained the deidentified records of patients, who underwent two mpMRI scans within 2 weeks of the first baseline scan. The patient records were obtained as deidentified data (including imaging), obtained through the TCIA (The Cancer Imaging Archive) repository and analyzed in our institution with an institutional review board-approved Health Insurance Portability and Accountability Act-compliant retrospective study protocol. Indicated biopsied regions were used as a marker for our study radiologists to delineate the regions of interest. We extracted 307 quantitative features in each mpMRI modality [T2-weighted MR sequence image (T2w) and apparent diffusion coefficient (ADC) with b values of 0 and 1,400 mm/s2] across the two sequential scans. Concordance correlation coefficients (CCCs) were computed on the features extracted from sequential scans. Redundant features were removed by computing the coefficient of determination (R 2) among them and replaced with a feature that had the highest dynamic range within intercorrelated groups. Results: We have assessed the reproducibility of quantitative imaging features among sequential scans and found that habitat region characterization improves repeatability in ADC maps. There were 19 T2w features and two ADC features in radiologist drawn regions (native raw image), compared to 18 T2w and 15 ADC features in habitat regions (sphere), which were reproducible (CCC ?0.65) and non-redundant (R 2 ? 0.99). We also found that z-transformation of the images prior to feature extraction reduced the number of reproducible features with no detrimental effect. Conclusion: We have shown that there are quantitative imaging features that are reproducible across sequential prostate mpMRI acquisition at a preset level of filters. We also found that a habitat approach improves feature repeatability in ADC. A validated set of reproducible image features in mpMRI will allow us to develop clinically useful disease risk stratification, enabling the possibility of using imaging as a surrogate to invasive biopsies.

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Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer.

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Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer.

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