Assessment of Invasive Breast Cancer Heterogeneity Using Whole-Tumor Magnetic Resonance Imaging Texture Analysis

Ko, Eun Sook; Kim, Jae‐Hun; Lim, Yaeji; Han, Boo‐Kyung; Cho, Eun Yoon; Nam, Seok Jin

doi:10.1097/md.0000000000002453

Cited by 33 publications

(32 citation statements)

References 21 publications

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“…Ko et al reported that entropies derived from T 1 -weighted contrast-enhanced and T 2weighted imaging differed significantly among breast cancers with different differentiation degrees. 30 Since there were only three cases of well-differentiated gastric cancers in our cohort, more patients should be accumulated in our future work to make more reliable conclusions.…”

Section: Discussionmentioning

confidence: 90%

Whole‐volume apparent diffusion coefficient‐based entropy parameters for assessment of gastric cancer aggressiveness

Liu

Zheng

Zhang

et al. 2017

Magnetic Resonance Imaging

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Purpose: To explore the role of whole-volume apparent diffusion coefficient (ADC)-based entropy parameters in the preoperative assessment of gastric cancer's aggressiveness. Materials and Methods: In all, 64 patients with gastric cancers who underwent 3.0T magnetic resonance imaging (MRI) were retrospectively included. Regions of interest were drawn manually using in-house software, around gastric cancer lesions on each slice of the diffusion-weighted images and ADC maps. Entropy-related parameters based on ADC maps were calculated automatically: (1) first-order entropy; (2-5) second-order entropies, including entropy(H) 0 , entropy(H) 45 , entropy(H) 90 , and entropy(H) 135 ; (6) entropy(H) mean ; and (7) entropy(H) range . Correlations between entropy-related parameters and pathological characteristics were analyzed with the Spearman correlation test. The parameters were compared among different pathological characteristics with independent-samples Kruskal-Wallis or Mann-Whitney U-test. Additionally, diagnostic performances of parameters in differentiating different pathological characteristics were analyzed by receiver operating characteristic (ROC) curve analysis. Results: All the entropy-related parameters significantly correlated with T, N, and overall stages, especially the firstorder entropy (r 5 0.588, 0.585, and 0.677, respectively, all P < 0.05). All the entropy-related parameters showed significant differences in gastric cancers at different T, N, and overall stages, as well as at different status of vascular invasion (P < 0.001-0.027). And four parameters, including entropy, entropy(H) 0 , entropy(H) 45 , and entropy(H) 90 , showed significant differences between gastric cancers with and without perineural invasion (P 0.006-0.040). Conclusion: Entropy-related parameters derived from whole-volume ADC texture analysis could help assess the aggressiveness of gastric cancers via analyzing intratumoral heterogeneity quantitatively, especially the first-order entropy. Level of Evidence: 2 Technical Efficacy: Stage 2

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Section: Discussionmentioning

confidence: 90%

Whole‐volume apparent diffusion coefficient‐based entropy parameters for assessment of gastric cancer aggressiveness

Liu

Zheng

Zhang

et al. 2017

Magnetic Resonance Imaging

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“…Wu et al 25 reported an association between peritumoral heterogeneity and a gene signature partially associated with immune cell recruitment and inflammation. Others have reported high lymphocytic infiltration to be associated with texture entropy features, 69 qualitative tumor enhancement profile and margin appearance in TN tumors, 70 and background parenchymal enhancement within 20 mm from the tumor. 71 Associations between intratumoral 72 and peritumoral 73 textural heterogeneity features with immune response at the molecular and morphometric scale have also been reported in the context of lung computed tomography.…”

Section: Discussionmentioning

confidence: 96%

Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy forHER2 (ERBB2)–Positive Breast Cancer

et al. 2019

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Key Points Question Can quantitative imaging features extracted from the tumor and tumor environment on breast magnetic resonance imaging characterize tumor biological features relevant to outcome of targeted therapy? Findings In this diagnostic study of 209 patients, among HER2 ( ERBB2 )-positive breast cancers, an intratumoral and peritumoral imaging signature capable of discriminating the response-associated HER2 -enriched molecular subtype was identified. When evaluated among recipients of HER2 -targeted therapy, this signature was found to be associated with response to neoadjuvant chemotherapy. Meaning Quantitative analysis of the tumor and its surroundings may provide valuable cues into breast cancer biological features and likelihood of response to targeted therapy.

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“…Texture analysis was used to evaluate collagen heterogeneity in localized ROI’s through quantification of entropy, uniformity, and fractal dimension. Entropy is a measure of irregularity in the distribution of collagen within tissue and quantified using histogram analysis by the equation: , where P(V) represents the intensity occurrence probability and V represents the area fraction of collagen 21 . Uniformity is a measure of how close the image is to a uniform distribution and is quantified by the equation: .…”

Section: Methodsmentioning

confidence: 99%

Collagen Complexity Spatially Defines Microregions of Total Tissue Pressure in Pancreatic Cancer

Nieskoski

Marra

Gunn

et al. 2017

Sci Rep

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The poor efficacy of systemic cancer therapeutics in pancreatic ductal adenocarcinoma (PDAC) is partly attributed to deposition of collagen and hyaluronan, leading to interstitial hypertension collapsing blood and lymphatic vessels, limiting drug delivery. The intrinsic micro-regional interactions between hyaluronic acid (HA), collagen and the spatial origins of mechanical stresses that close off blood vessels was investigated here. Multiple localized pressure measurements were analyzed with spatially-matched histochemical images of HA, collagen and vessel perfusion. HA is known to swell, fitting a linear elastic model with total tissue pressure (TTP) increasing above interstitial fluid pressure (IFP) directly with collagen content. However, local TTP appears to originate from collagen area fraction, as well as increased its entropy and fractal dimension, and morphologically appears to be maximized when HA regions are encapsulated by collagen. TTP was inversely correlated with vascular patency and verteporfin uptake, suggesting interstitial hypertension results in vascular compression and decreased molecular delivery in PDAC. Collagenase injection led to acute decreases in total tissue pressure and increased drug perfusion. Large microscopic variations in collagen distributions within PDAC leads to microregional TPP values that vary on the hundred micron distance scale, causing micro-heterogeneous limitations in molecular perfusion, and narrows viable treatment regimes for systemically delivered therapeutics.

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Assessment of Invasive Breast Cancer Heterogeneity Using Whole-Tumor Magnetic Resonance Imaging Texture Analysis

Abstract: Supplemental Digital Content is available in the text

Cited by 33 publications

References 21 publications

Whole‐volume apparent diffusion coefficient‐based entropy parameters for assessment of gastric cancer aggressiveness

Whole‐volume apparent diffusion coefficient‐based entropy parameters for assessment of gastric cancer aggressiveness

Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy forHER2 (ERBB2)–Positive Breast Cancer

Collagen Complexity Spatially Defines Microregions of Total Tissue Pressure in Pancreatic Cancer

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