Intratumoral heterogeneity of Ki67 proliferation index outperforms conventional immunohistochemistry prognostic factors in estrogen receptor-positive HER2-negative breast cancer.

In breast cancer (BC), pathologists visually score ER, PR, HER2, and Ki67 biomarkers to assess tumor properties and predict patient outcomes. This does not systematically account for intratumoral heterogeneity (ITH) which has been reported to provide prognostic value. This study utilized digital image analysis (DIA) and computational pathology methods to investigate the prognostic value of ITH indicators in ER-positive (ER+) HER2-negative (HER2-) BC patients. Whole slide images (WSIs) of surgically excised specimens stained for ER, PR, Ki67, and HER2 from 254 patients were used. DIA with tumor tissue segmentation and detection of biomarker-positive cells was performed. The DIA-generated data were subsampled by a hexagonal grid to compute Haralick's texture indicators for ER, PR, and Ki67. Cox regression analyses were performed to assess the prognostic significance of the immunohistochemistry (IHC) and ITH indicators in the context of clinicopathologic variables. In multivariable analysis, the ITH of Ki67-positive cells, measured by Haralick's texture entropy, emerged as an independent predictor of worse BC-specific survival (BCSS) (hazard ratio (HR) = 2.64, p-value = 0.0049), along with lymph node involvement (HR = 2.26, p-value = 0.0195). Remarkably, the entropy representing the spatial disarrangement of tumor proliferation outperformed the proliferation rate per se established either by pathology reports or DIA. We conclude that the Ki67 entropy indicator enables a more comprehensive risk assessment with regard to BCSS, especially in cases with borderline Ki67 proliferation rates. The study further demonstrates the benefits of high-capacity DIA-generated data for quantifying the essentially subvisual ITH properties.

Image based simulation of the low dose computed tomography images suggests 13 mAs 120 kV suitability for non-syndromic craniosynostosis diagnosis without iterative reconstruction algorithms.

OBJECTIVES: The aim of this study was to simulate low dose paediatric head CT images with different noise levels corresponding to various tube current time product values and assess simulated image suitability in non-syndromic craniosynostosis diagnostics. METHOD: 29 paediatric patients who underwent head CT examinations for cranial deformity were enrolled in the study. The low dose CT images, corresponding to 120 kV and 120 mAs, 100 mAs, 80 mAs, 50 mAs and 13 mAs settings, were synthesised by adding noise to original data. Three researchers evaluated suitability for diagnostics of original and simulated images by using questionnaire assessing image suitability. RESULT: 174 separate cases (containing 1 axial and 1 3D image) were evaluated. Percentage of images evaluated as suitable for diagnosis were 98.9% on original images, 100% on 120 mAs, 100% on 100 mAs, 97.1% on 80 mAs, 96.6% on 50 mAs and 96% on 13 mAs. CONCLUSIONS: Images registered with 120 kV 13 mAs can be used to diagnose non-syndromic craniosynostosis with statistically same accuracy as with standard protocol and correspond to decrease of effective dose from 4.98 mSv to 0.33 mSv (median values).

Combination of single quantitative parameters into multiparametric model for ischemia detection is not superior to visual assessment during dobutamine stress echocardiography.

BACKGROUND: To evaluate if the combination of several quantitative parameters into a mathematical model would enhance the detection of myocardial ischemia during dobutamine stress echocardiography (DSE) when compared to conventional wall motion analysis. METHODS: In a prospective study design 151 patients (age 61.8 ± 9.2) in test group and 105 patients (age 64.0 ± 10.6) in validation group were selected and underwent DSE between January 2008 and December 2012. In all patients coronary angiography was performed within 6-8 weeks from DSE, considering at least one stenosis ≥50% per patient as significant coronary artery disease (CAD). Results of DSE visual assessment and myocardial velocity, strain and strain rate parameters derived from speckle tracking imaging were imported automatically to an originally created software. A mathematical model calculating prognosis of at least one stenosis per patient and stenosis in separate arteries was constructed. RESULTS: Myocardial ischemia was visually detected in 60 (39.7 %) and in 58 (54.2 %) patients of the test and validation group, respectively. A total of 76 (50.3 %) patients in the test group and 69 patients (65.7 %) in the validation group had ≥50% coronary stenosis. Sensitivity and specificity of the mathematical model per patient in the test group were 91.6 % and 86.3 % compared to 76.8 % and 89.0 % of the visual assessment, respectively. However, in the validation group the sensitivity, specificity, positive predictive value and negative predictive value dropped down significantly becoming lower to visual assessment. CONCLUSIONS: Myocardial deformation imaging may potentially replace visual assessment with an automated predictive model for stress-induced ischemia detection. However, a multiparametric mathematical model based on quantitative deformation markers did not demonstrate incremental value to visual assessment of wall motion.