Cardiovascular Magnetic Resonance Radiomics to Identify Components of the Extracellular Matrix in Dilated Cardiomyopathy

Abstract

Background: Current cardiovascular magnetic resonance sequences cannot discriminate between different myocardial extracellular space (ECSs), including collagen, noncollagen, and inflammation. We sought to investigate whether cardiovascular magnetic resonance radiomics analysis can distinguish between noncollagen and inflammation from collagen in dilated cardiomyopathy.

Methods: We identified data from 132 patients with dilated cardiomyopathy scheduled for an invasive septal biopsy who underwent cardiovascular magnetic resonance at 3 T. Cardiovascular magnetic resonance imaging protocol included native and postcontrast T₁ mapping and late gadolinium enhancement (LGE). Radiomic features were computed from the midseptal myocardium, near the biopsy region, on native T₁, extracellular volume (ECV) map, and LGE images. Principal component analysis was used to reduce the number of radiomic features to 5 principal radiomics. Moreover, a correlation analysis was conducted to identify radiomic features exhibiting a strong correlation (r>0.9) with the 5 principal radiomics. Biopsy samples were used to quantify ECS, myocardial fibrosis, and inflammation.

Results: Four histopathological phenotypes were identified: low collagen (n=20), noncollagenous ECS expansion (n=49), mild to moderate collagenous ECS expansion (n=42), and severe collagenous ECS expansion (n=21). Noncollagenous expansion was associated with the highest risk of myocardial inflammation (65%). Although native T₁ and ECV provided high diagnostic performance in differentiating severe fibrosis (C statistic, 0.90 and 0.90, respectively), their performance in differentiating between noncollagen and mild to moderate collagenous expansion decreased (C statistic: 0.59 and 0.55, respectively). Integration of ECV principal radiomics provided better discrimination and reclassification between noncollagen and mild to moderate collagen (C statistic, 0.79; net reclassification index, 0.83 [95% CI, 0.45-1.22]; P<0.001). There was a similar trend in the addition of native T₁ principal radiomics (C statistic, 0.75; net reclassification index, 0.93 [95% CI, 0.56-1.29]; P<0.001) and LGE principal radiomics (C statistic, 0.74; net reclassification index, 0.59 [95% CI, 0.19-0.98]; P=0.004). Five radiomic features per sequence were identified with correlation analysis. They showed a similar improvement in performance for differentiating between noncollagen and mild to moderate collagen (native T₁, ECV, LGE C statistic, 0.75, 0.77, and 0.71, respectively). These improvements remained significant when confined to a single radiomic feature (native T₁, ECV, LGE C statistic, 0.71, 0.70, and 0.64, respectively).

Conclusions: Radiomic features extracted from native T₁, ECV, and LGE provide incremental information that improves our capability to discriminate noncollagenous expansion from mild to moderate collagen and could be useful for detecting subtle chronic inflammation in patients with dilated cardiomyopathy.

Keywords: cardiomyopathy, dilated; histology; magnetic resonance imaging; radiomics.

Figure 1:. Measurement of collagen volume fraction and extracellular space and histopathological phenotyping

(A) Images are hematoxylin-eosin-stained and picrosirius red-stained tissue sections. By using ImageJ software (National Institution of Health, Bethesda, MD, USA), high-power magnification digital images (200×) were used for semiautomated image analysis to assess ECS (top row) and CVF (bottom row), which were calculated as the percentage of ECS area (black area) and collagen area (light blue area), respectively, divided by total myocardial area, excluding subendocardial areas. Non-collagenous ECS was calculated as total ECS minus collagen area. ECS, CVF, and non-collagenous ECS, in this case, correspond to 24%, 6%, and 18%, respectively. (B) Subjects were classified into four histopathological phenotypes: low CVF (CVF <5%); mild-to-moderate fibrosis (5%≤ CVF <20%) with non-collagenous ECS expansion ≥15%; mild-to-moderate fibrosis (5%≤ CVF <20%) without non-collagenous ECS expansion≥15%; and severe fibrosis (20%≤ CVF) CVF; collagen volume fraction, ECS; extracellular space

Figure 1:. Measurement of collagen volume fraction and extracellular space and histopathological phenotyping

(A) Images are hematoxylin-eosin-stained and picrosirius red-stained tissue sections. By using ImageJ software (National Institution of Health, Bethesda, MD, USA), high-power magnification digital images (200×) were used for semiautomated image analysis to assess ECS (top row) and CVF (bottom row), which were calculated as the percentage of ECS area (black area) and collagen area (light blue area), respectively, divided by total myocardial area, excluding subendocardial areas. Non-collagenous ECS was calculated as total ECS minus collagen area. ECS, CVF, and non-collagenous ECS, in this case, correspond to 24%, 6%, and 18%, respectively. (B) Subjects were classified into four histopathological phenotypes: low CVF (CVF <5%); mild-to-moderate fibrosis (5%≤ CVF <20%) with non-collagenous ECS expansion ≥15%; mild-to-moderate fibrosis (5%≤ CVF <20%) without non-collagenous ECS expansion≥15%; and severe fibrosis (20%≤ CVF) CVF; collagen volume fraction, ECS; extracellular space

Figure 2:. Proposed radiomics-driven feature model using native T₁, ECV, and LGE

For the radiomic feature analyses, a large region of interest was placed on the inferior septal myocardium at the mid-ventricular level of each image, corresponding to the biopsy region. A total of 1023 first-order and textural features were extracted per sequence, and principal component analysis was performed to extract the components representing the top variations of the radiomic features per sequence. For model development, we selected the top 5 components (principal radiomics) based on the number of phenotypes in the dataset. DCM; dilated cardiomyopathy, ECS; extracellular space, ECV; extracellular volume, LGE; late gadolinium enhancement

Figure 3:. Comparisons of native T₁ and ECV among 4 different histopathological phenotypes

Native T₁ values provide high diagnostic concordance in predicting histological phenotype severity associated with myocardial fibrosis. However, native T₁ values only mildly increased and substantially overlapped between the non-collagenous and collagenous expansion. There is a similar trend in ECV values. Reference values at our institution; native T1:1314±29 ms, ECV: 26±4% ECS; extracellular space, ECV; extracellular volume

Figure 4:. ROC curves of principal radiomics, pre-selected five radiomic features, and one radiomic feature for discriminating the non-collagen and mild-to-moderate collagen

Receiver operating characteristic (ROC) curve and corresponding area under the curve (AUC) for differentiation of non-collagenous and collagenous deposition ECV; extracellular volume, LGE; late gadolinium enhancement

Figure 5:. Representative cases of non-collagenous and collagenous expansion with similar extracellular space

(A) Hematoxylin-eosin and picrosirius red-stained samples showed ECS expansion of 33% but less fibrosis (CVF=9%). Immunohistochemistry of this case confirmed myocardial inflammation. CMR images showed a relatively smaller LV cavity size without LGE. (B) The ECS and CVF examples corresponded to 31% and 18%, which revealed the difference in CVF despite similar ECS expansion, and no inflammation was observed. Native T₁, ECV, and LGE texture features of case B seem to be heterogeneous, comparing those of case A. There was a small amount of LGE in the inferior wall. CVF; collagen volume fraction, ECS; extracellular space, ECV; extracellular volume, LGE; late gadolinium enhancement, LV; left ventricular