Dataset Information

Rapid quantification of myocardial fibrosis: a new macro-based automated analysis.

ABSTRACT:

Background

Fibrosis is associated with various cardiac pathologies and dysfunction. Current quantification methods are time-consuming and laborious. We describe a semi-automated quantification technique for myocardial fibrosis and validated this using traditional methods.

Methods

Pulmonary Hypertension (PH) was induced in adult Wistar rats by subcutaneous monocrotaline (MCT) injection(40 mg/kg). Cryosections of myocardial tissue (5 ?m) of PH rats (n = 9) and controls (n = 9) were stained using Picrosirius red and scanned with a digital microscopic MIRAX slide scanner. From these sections 21 images were taken randomly of each heart. Using ImageJ software a macro for automated image analysis of the amount of fibrosis was developed. For comparison, fibrosis was quantified using traditional polarisation microscopy. Both methods were correlated and validated against stereology as the gold standard. Furthermore, the method was tested in paraffin-embedded human tissues.

Results

Automated analysis showed a significant increase of fibrosis in PH hearts vs. control. Automated analysis correlated with traditional polarisation and stereology analysis (r(2) = 0.92 and r(2) = 0.95 respectively). In human heart, lungs, kidney, and liver, a similar correlation with stereology (r(2) = 0.91) was observed. Time required for automated analysis was 22% and 33% of the time needed for stereology and polarisation analysis respectively.

Conclusion

Automated quantification of fibrosis is feasible, objective, and time-efficient.

SUBMITTER: Hadi AM

PROVIDER: S-EPMC3162624 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature

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Publications

Rapid quantification of myocardial fibrosis: a new macro-based automated analysis.

Hadi Awal M AM Mouchaers Koen T B KT Schalij Ingrid I Grunberg Katrien K Meijer Gerrit A GA Vonk-Noordegraaf Anton A van der Laarse Willem J WJ Beliën Jeroen A M JA

Cellular oncology (Dordrecht, Netherlands) 20110503 4

<h4>Background</h4>Fibrosis is associated with various cardiac pathologies and dysfunction. Current quantification methods are time-consuming and laborious. We describe a semi-automated quantification technique for myocardial fibrosis and validated this using traditional methods.<h4>Methods</h4>Pulmonary Hypertension (PH) was induced in adult Wistar rats by subcutaneous monocrotaline (MCT) injection(40 mg/kg). Cryosections of myocardial tissue (5 μm) of PH rats (n = 9) and controls (n = 9) were ...[more]

PMID: 21538025

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Project description:PurposeTo assess the performance of an automated myocardial T2 and extracellular volume (ECV) quantification method using transfer learning of a fully convolutional neural network (CNN) pretrained to segment the myocardium on T1 mapping images.Materials and methodsA single CNN previously trained and tested using 11 550 manually segmented native T1-weighted images was used to segment the myocardium for automated myocardial T2 and ECV quantification. Reference measurements from 1525 manually processed T2 maps and 1525 ECV maps (from 305 patients) were used to evaluate the performance of the pretrained network. Correlation coefficient (R) and Bland-Altman analysis were used to assess agreement between automated and reference values on per-patient, per-slice, and per-segment analyses. Furthermore, transfer learning effectiveness in the CNN was evaluated by comparing its performance to four CNNs trained using manually segmented T2-weighted and postcontrast T1-weighted images and initialized using random-weights or weights of the pretrained CNN.ResultsT2 and ECV measurements using the pretrained CNN strongly correlated with reference values in per-patient (T2: R = 0.88, 95% confidence interval [CI]: 0.85, 0.91; ECV: R = 0.91, 95% CI: 0.89, 0.93), per-slice (T2: R = 0.83, 95% CI: 0.81, 0.85; ECV: R = 0.84, 95% CI: 0.82, 0.86), and per-segment (T2: R = 0.75, 95% CI: 0.74, 0.77; ECV: R = 0.76, 95% CI: 0.75, 0.77) analyses. In Bland-Altman analysis, the automatic and reference values were in good agreement in per-patient (T2: 0.3 msec ± 2.9; ECV: -0.3% ± 1.7), per-slice (T2: 0.1 msec ± 4.6; ECV: -0.3% ± 2.5), and per-segment (T2: 0.0 msec ± 6.5; ECV: -0.4% ± 3.5) analyses. The performance of the pretrained network was comparable to networks refined or trained from scratch using additional manually segmented images.ConclusionTransfer learning extends the utility of pretrained CNN-based automated native T1 mapping analysis to T2 and ECV mapping without compromising performance. Supplemental material is available for this article. © RSNA, 2020.

Project description:Pulmonary fibrosis is characterized by abnormal interstitial extracellular matrix and cellular accumulations. Methods quantifying fibrosis severity in lung histopathology samples are semi-quantitative, subjective, and analyze only portions of sections. We sought to determine whether automated computerized imaging analysis shown to continuously measure fibrosis in mice could also be applied in human samples. A pilot study was conducted to analyze a small number of specimens from patients with Hermansky-Pudlak syndrome pulmonary fibrosis (HPSPF) or idiopathic pulmonary fibrosis (IPF). Digital images of entire lung histological serial sections stained with picrosirius red and alcian blue or anti-CD68 antibody were analyzed using dedicated software to automatically quantify fibrosis, collagen, and macrophage content. Automated fibrosis quantification based on parenchymal tissue density and fibrosis score measurements was compared to pulmonary function values or Ashcroft score. Automated fibrosis quantification of HPSPF lung explants was significantly higher than that of IPF lung explants or biopsies and was also significantly higher in IPF lung explants than in IPF biopsies. A high correlation coefficient was found between some automated quantification measurements and lung function values for the three sample groups. Automated quantification of collagen content in lung sections used for digital image analyses was similar in the three groups. CD68 immunolabeled cell measurements were significantly higher in HPSPF explants than in IPF biopsies. In conclusion, computerized image analysis provides access to accurate, reader-independent pulmonary fibrosis quantification in human histopathology samples. Fibrosis, collagen content, and immunostained cells can be automatically and individually quantified from serial sections. Robust automated digital image analysis of human lung samples enhances the available tools to quantify and study fibrotic lung disease.

Project description:BackgroundIn vivo high-resolution micro-computed tomography allows for longitudinal image-based measurements in animal models of lung disease. The combination of repetitive high resolution imaging with fully automated quantitative image analysis in mouse models of lung fibrosis lung benefits preclinical research. This study aimed to develop and validate such an automated micro-computed tomography analysis algorithm for quantification of aerated lung volume in mice; an indicator of pulmonary fibrosis and emphysema severity.MethodologyMice received an intratracheal instillation of bleomycin (n = 8), elastase (0.25 U elastase n = 9, 0.5 U elastase n = 8) or saline control (n = 6 for fibrosis, n = 5 for emphysema). A subset of mice was scanned without intervention, to evaluate potential radiation-induced toxicity (n = 4). Some bleomycin-instilled mice were treated with imatinib for proof of concept (n = 8). Mice were scanned weekly, until four weeks after induction, when they underwent pulmonary function testing, lung histology and collagen quantification. Aerated lung volumes were calculated with our automated algorithm.Principal findingsOur automated image-based aerated lung volume quantification method is reproducible with low intra-subject variability. Bleomycin-treated mice had significantly lower scan-derived aerated lung volumes, compared to controls. Aerated lung volume correlated with the histopathological fibrosis score and total lung collagen content. Inversely, a dose-dependent increase in lung volume was observed in elastase-treated mice. Serial scanning of individual mice is feasible and visualized dynamic disease progression. No radiation-induced toxicity was observed. Three-dimensional images provided critical topographical information.ConclusionsWe report on a high resolution in vivo micro-computed tomography image analysis algorithm that runs fully automated and allows quantification of aerated lung volume in mice. This method is reproducible with low inherent measurement variability. We show that it is a reliable quantitative tool to investigate experimental lung fibrosis and emphysema in mice. Its non-invasive nature has the unique benefit to allow dynamic 4D evaluation of disease processes and therapeutic interventions.

Dataset Information

Rapid quantification of myocardial fibrosis: a new macro-based automated analysis.

Background

Methods

Results

Conclusion

Publications

Rapid quantification of myocardial fibrosis: a new macro-based automated analysis.

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