Browsing by Subject "Digital image analysis"

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    Open Access
    Digital image analysis of the tissue surface areas of site-designated and bilaterally pooled prostate biopsies
    (Universidad de Murcia. Departamento de Biología Celular e Histología, 2018) Koivusalo, Laura; Kaipia, Antti; Kujala, Paula; Isola, Jorma; Tolonen, Teemu T.
    Initial reports about the length of bilaterally pooled biopsies showed alarming tissue loss compared to individual biopsies, but the current understanding of “noodle biopsies” and better embedding techniques may have improved their quality. Here, we implemented digital image analysis to study the differences in tissue surface areas between individual and pooled cores. Prostate biopsy reports from 1242 consecutive patients were reviewed. Urologist-dependent bias on the biopsy quality was eliminated by identifying four urologists who submitted equally individual and bilaterally pooled biopsies. Digital image analysis was applied to the tissue surface areas of 936 virtual slides containing 1440 biopsy cores (12 cores per patient x 120 patients) taken by the four urologists. The median (range) surface areas were 73.8 mm2 (40.1-102.5) for the site-designated (n=57) and 77.1 mm2 (49.5-119.2) for the bilaterally pooled biopsies (n=63) (p=0.19). For three urologists, the median surface areas were 69.5 mm2 (60.4-93.2), 75.5 mm2 (48.2-98.7) and 78.2 mm2 (47.1-92.7) for the site-designated and 79.2 mm2 (49.5-116.4), 69.3 mm2 (49.6-119.2) and 79.2 mm2 (55.1-96.7) for the pooled biopsies, respectively (p=0.58-0.75). For one urologist, the median surface area was marginally higher for the pooled biopsies, 68.1 mm2 (40.1-102.5) vs. 81.6 mm2 (62.7-108.8) (p=0.03). In conclusion, the histological yields of individual and pooled prostate biopsies were practically equal. The results should not be considered as a recommendation to increasingly submit unspecified bilateral cores but to encourage pathology laboratories to embed and cut all received prostate biopsies with special attention, regardless of submission type.
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    Publication
    Open Access
    Quantification of protein expression in cells and cellular subcompartments on immunohistochemical sections using a computer supported image analysis system
    (F. Hernández y Juan F. Madrid. Universidad de Murcia. Departamento de Biología Celular e Histología, 2013) Braun, Martin; Kirsten, Robert; Rupp, Niels J.; Moch, Holger; Fend, Falko; Wernert, Nicolas; Kristiansen, Glen; Perner, Sven
    Quantification of protein expression based on immunohistochemistry (IHC) is an important step for translational research and clinical routine. Several manual (‘eyeballing’) scoring systems are used in order to semi-quantify protein expression based on chromogenic intensities and distribution patterns. However, manual scoring systems are time-consuming and subject to significant intra- and interobserver variability. The aim of our study was to explore, whether new image analysis software proves to be sufficient as an alternative tool to quantify protein expression. For IHC experiments, one nucleus specific marker (i.e., ERG antibody), one cytoplasmic specific marker (i.e., SLC45A3 antibody), and one marker expressed in both compartments (i.e., TMPRSS2 antibody) were chosen. Stainings were applied on TMAs, containing tumor material of 630 prostate cancer patients. A pathologist visually quantified all IHC stainings in a blinded manner, applying a four-step scoring system. For digital quantification, image analysis software (Tissue Studio v.2.1, Definiens AG, Munich, Germany) was applied to obtain a continuous spectrum of average staining intensity. For each of the three antibodies we found a strong correlation of the manual protein expression score and the score of the image analysis software. Spearman’s rank correlation coefficient was 0.94, 0.92, and 0.90 for ERG, SLC45A3, and TMPRSS2, respectively (p<0.01). Our data suggest that the image analysis software Tissue Studio is a powerful tool for quantification of protein expression in IHC stainings. Further, since the digital analysis is precise and reproducible, computer supported protein quantification might help to overcome intra- and interobserver variability and increase objectivity of IHC based protein assessment.