A new automated radiogrammetric method to estimate bone mineral density (BMD) from a single radiograph of the hand and forearm is described. Five regions of interest in radius, ulna and the three middle metacarpal bones are identified and approximately 1800 geometrical measurements from these bones are used to obtain a BMD estimate of the distal forearm, referred to as BMDDXR (from digital X-ray radiogrammetry, DXR). The measured dimensions for each bone are the cortical thickness and the outer width, in combination with an stimate of the cortical porosity. The short-term in vivo precision of BMDDXR was observed to be 0.60% in a clinical study of 24 women and the in vitro variation over 12 different radiological clinics was found to be 1% of the young normal BMDDXR level. In a cohort of 416 women BMDDXR was found to be closely correlated with BMD at the distal forearm measured by dual-energy X-ray absoptiometry (r = 0.86, p < 0.0001) and also with BMD at the spine, total hip and femoral neck (r = 0.62, 0.69 and 0.73, respectively, p<0.0001 for all). The annual decline was estimated from the cohort to be 1.05% in the age group 55-65 years. Relative to this age-related loss, the reported short-term precision allows for monitoring intervals of 1.0 years and 1.6 years in order to detect expected age-related changes with a confidence of 80% and 95%, respectively. It is concluded that the DXR method offers a BMD estimate with a good correlation with distal forearm BMD, a low variation between geographical sites and a precision that potentially allows for relatively short observation intervals.

In the spectrum of breast cancers, categorization according to the four gene expression-based subtypes 'Luminal A,' 'Luminal B,' 'HER2-enriched,' and 'Basal-like' is the method of choice for prognostic and predictive value. As gene expression assays are not yet universally available, routine immunohistochemical stains act as surrogate markers for these subtypes. Thus, congruence of surrogate markers and gene expression tests is of utmost importance. In this study, 3 cohorts of primary breast cancer specimens (total n = 436) with up to 28 years of survival data were scored for Ki67, ER, PR, and HER2 status manually and by digital image analysis (DIA). The results were then compared for sensitivity and specificity for the Luminal B subtype, concordance to PAM50 assays in subtype classification and prognostic power. The DIA system used was the Visiopharm Integrator System. DIA outperformed manual scoring in terms of sensitivity and specificity for the Luminal B subtype, widely considered the most challenging distinction in surrogate subclassification, and produced slightly better concordance and Cohen's κ agreement with PAM50 gene expression assays. Manual biomarker scores and DIA essentially matched each other for Cox regression hazard ratios for all-cause mortality. When the Nottingham combined histologic grade (Elston-Ellis) was used as a prognostic surrogate, stronger Spearman's rank-order correlations were produced by DIA. Prognostic value of Ki67 scores in terms of likelihood ratio χ 2 (LR χ 2 ) was higher for DIA that also added significantly more prognostic information to the manual scores (LR− Δχ 2 ). In conclusion, the system for DIA evaluated here was in most aspects a superior alternative to manual biomarker scoring. It also has the potential to reduce time consumption for pathologists, as many of the steps in the workflow are either automatic or feasible to manage without pathological expertise.

The purpose of this study was to develop and validate a new software, HER2-CONNECT(TM), for digital image analysis of the human epidermal growth factor receptor 2 (HER2) in breast cancer specimens. The software assesses immunohistochemical (IHC) staining reactions of HER2 based on an algorithm evaluating the cell membrane connectivity. The HER2-CONNECT algorithm was aligned to match digital image scorings of HER2 performed by 5 experienced assessors in a training set and confirmed in a separate validation set. The training set consisted of 167 breast carcinoma tissue core images in which the assessors individually and blinded outlined regions of interest and gave their HER2 score 0/1+/2+/3+ to the specific tumor region. The validation set consisted of 86 core images where the result of the automated image analysis software was correlated to the scores provided by the 5 assessors. HER2 fluorescence in situ hybridization (FISH) was performed on all cores and used as a reference standard. The overall agreement between the image analysis software and the digital scorings of the 5 assessors was 92.1% (Cohen's Kappa: 0.859) in the training set and 92.3% (Cohen's Kappa: 0.864) in the validation set. The image analysis sensitivity was 99.2% and specificity 100% when correlated to FISH. In conclusion, the Visiopharm HER2 IHC algorithm HER2-CONNECT(TM) can discriminate between amplified and non-amplified cases with high accuracy and diminish the equivocal category and thereby provides a promising supplementary diagnostic tool to increase consistency in HER2 assessment.

Detection of diabetic retinopathy by automated detection of single fundus lesions can be achieved with a performance comparable to that of experienced ophthalmologists. The results warrant further investigation of automated fundus image analysis as a tool for diabetic retinopathy screening.

Automated detection of untreated diabetic retinopathy in fundus photographs from a screening population of patients with diabetes can be made with adjustable priority settings, emphasizing high-sensitivity identification of diabetic retinopathy or high-specificity identification of absence of retinopathy, covering opposing extremes of visual evaluation strategies demonstrated by human observers.