Quantification of myocardial fibrosis by digital image analysis and interactive stereology

Abstract

BackgroundCardiac fibrosis disrupts the normal myocardial structure and has a direct impact on heart function and survival. Despite already available digital methods, the pathologist’s visual score is still widely considered as ground truth and used as a primary method in histomorphometric evaluations. The aim of this study was to compare the accuracy of digital image analysis tools and the pathologist’s visual scoring for evaluating fibrosis in human myocardial biopsies, based on reference data obtained by point counting performed on the same images.MethodsEndomyocardial biopsy material from 38 patients diagnosed with inflammatory dilated cardiomyopathy was used. The extent of total cardiac fibrosis was assessed by image analysis on Masson’s trichrome-stained tissue specimens using automated Colocalization and Genie software, by Stereology grid count and manually by Pathologist’s visual score.ResultsA total of 116 slides were analyzed. The mean results obtained by the Colocalization software (13.72 ± 12.24%) were closest to the reference value of stereology (RVS), while the Genie software and Pathologist score gave a slight underestimation. RVS values correlated strongly with values obtained using the Colocalization and Genie (r > 0.9, p < 0.001) software as well as the pathologist visual score. Differences in fibrosis quantification by Colocalization and RVS were statistically insignificant. However, significant bias was found in the results obtained by using Genie versus RVS and pathologist score versus RVS with mean difference values of: -1.61% and 2.24%. Bland-Altman plots showed a bidirectional bias dependent on the magnitude of the measurement: Colocalization software overestimated the area fraction of fibrosis in the lower end, and underestimated in the higher end of the RVS values. Meanwhile, Genie software as well as the pathologist score showed more uniform results throughout the values, with a slight underestimation in the mid-range for both.ConclusionBoth applied digital image analysis methods revealed almost perfect correlation with the criterion standard obtained by stereology grid count and, in terms of accuracy, outperformed the pathologist’s visual score. Genie algorithm proved to be the method of choice with the only drawback of a slight underestimation bias, which is considered acceptable for both clinical and research evaluations.Virtual slidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9857909611227193

Immuno‐modification of enhancing stem cells targeting for myocardial repair

“…All surgical procedures were approved by the Committee for Animal Research of the University of California San Francisco (San Francisco, CA, USA). The ischaemia reperfusion model has been extensively tested in our laboratory . In brief, forty five female nude rats (200–250 g) were intubated endotracheally, connected to a rodent ventilator (Harvard Apparatus: Holliston, MA, USA), and anesthetized by inhalation of 2% isoflurane.…”

“…To differentiate the MI pattern in the three groups, we developed a method to semi‐quantify the fibrosis pattern in different regions . Up to five evenly distributed views within the MI were selected for each slide and up to 12 slides per animal with Masson's trichrome stain were scored on a 1 to 4 scale.…”

Commentary

“…For instance, a recent position paper advocates that accurate assessment of common morphological end points in lung (e.g., alveolar number or size) requires the application of 3-D stereology (Hsia et al 2010). However, while mandated use of 3-D measurements may be justified in some settings, several recent studies across various disease indications in humans have shown that 2-D tIA of digital images yields data sets that are (1) concordant with scores acquired by conventional manual evaluation and diagnostic scoring and (2) at times provide an even more accurate measurement for the severity and stage of a disease (Daunoravicius et al 2014;Zhong et al 2016;Laurinaviciene et al 2011;Turashvili et al 2009;Vennalaganti et al 2015;Lee et al 2013;Farris et al 2014;Snead et al 2016;Ohlschlegel et al 2013). The utility of 2-D tIA gains additional importance in tissue specimens harvested in the course of human clinical trials because 2-D digital imaging approaches still provide useful information when tissue sample sizes are too small (e.g., needle core biopsies) to permit 3-D evaluation or when ethical considerations preclude optimal processing of tissue (i.e., euthanasia with rapid removal and fixation of tumor-ridden organs as practiced in animal experiments is not possible in human patients).…”

Analysis of digital histopathology images for breast cancer diagnosis

“…Malignant tumors (Tridosaja) are very harmful, because they can affect all three major body systems, i.e. the nervous system (Vata or air), the venous system (Pitta or fire), and the arterial system (Kapha or water) lose mutual coordination and thus cannot prevent tissue damage, resulting in a deadly morbid condition [12,13]. In modern medical point of view, the cancer is defined as abnormal cell division due to a number of conditions.…”

“…It has been found that breast cancer is common to a large part of women [12]. In India, the death toll due to breast cancer is increasing at a rapid pace [13]. It is becoming a major challenge in India due to lack of awareness and lethargy of the Indian women towards health care and regular check-up.…”