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1.  Effect of image compression and scaling on automated scoring of immunohistochemical stainings and segmentation of tumor epithelium 
Diagnostic Pathology  2012;7:29.
Background
Digital whole-slide scanning of tissue specimens produces large images demanding increasing storing capacity. To reduce the need of extensive data storage systems image files can be compressed and scaled down. The aim of this article is to study the effect of different levels of image compression and scaling on automated image analysis of immunohistochemical (IHC) stainings and automated tumor segmentation.
Methods
Two tissue microarray (TMA) slides containing 800 samples of breast cancer tissue immunostained against Ki-67 protein and two TMA slides containing 144 samples of colorectal cancer immunostained against EGFR were digitized with a whole-slide scanner. The TMA images were JPEG2000 wavelet compressed with four compression ratios: lossless, and 1:12, 1:25 and 1:50 lossy compression. Each of the compressed breast cancer images was furthermore scaled down either to 1:1, 1:2, 1:4, 1:8, 1:16, 1:32, 1:64 or 1:128. Breast cancer images were analyzed using an algorithm that quantitates the extent of staining in Ki-67 immunostained images, and EGFR immunostained colorectal cancer images were analyzed with an automated tumor segmentation algorithm. The automated tools were validated by comparing the results from losslessly compressed and non-scaled images with results from conventional visual assessments. Percentage agreement and kappa statistics were calculated between results from compressed and scaled images and results from lossless and non-scaled images.
Results
Both of the studied image analysis methods showed good agreement between visual and automated results. In the automated IHC quantification, an agreement of over 98% and a kappa value of over 0.96 was observed between losslessly compressed and non-scaled images and combined compression ratios up to 1:50 and scaling down to 1:8. In automated tumor segmentation, an agreement of over 97% and a kappa value of over 0.93 was observed between losslessly compressed images and compression ratios up to 1:25.
Conclusions
The results of this study suggest that images stored for assessment of the extent of immunohistochemical staining can be compressed and scaled significantly, and images of tumors to be segmented can be compressed without compromising computer-assisted analysis results using studied methods.
Virtual slides
The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2442925476534995
doi:10.1186/1746-1596-7-29
PMCID: PMC3375185  PMID: 22436596
Breast cancer; Colorectal cancer; Immunohistochemistry; Texture analysis; Image processing; Computer-Assisted; Image compression; Image scaling
2.  Identification of tumor epithelium and stroma in tissue microarrays using texture analysis 
Diagnostic Pathology  2012;7:22.
Background
The aim of the study was to assess whether texture analysis is feasible for automated identification of epithelium and stroma in digitized tumor tissue microarrays (TMAs). Texture analysis based on local binary patterns (LBP) has previously been used successfully in applications such as face recognition and industrial machine vision. TMAs with tissue samples from 643 patients with colorectal cancer were digitized using a whole slide scanner and areas representing epithelium and stroma were annotated in the images. Well-defined images of epithelium (n = 41) and stroma (n = 39) were used for training a support vector machine (SVM) classifier with LBP texture features and a contrast measure C (LBP/C) as input. We optimized the classifier on a validation set (n = 576) and then assessed its performance on an independent test set of images (n = 720). Finally, the performance of the LBP/C classifier was evaluated against classifiers based on Haralick texture features and Gabor filtered images.
Results
The proposed approach using LPB/C texture features was able to correctly differentiate epithelium from stroma according to texture: the agreement between the classifier and the human observer was 97 per cent (kappa value = 0.934, P < 0.0001) and the accuracy (area under the ROC curve) of the LBP/C classifier was 0.995 (CI95% 0.991-0.998). The accuracy of the corresponding classifiers based on Haralick features and Gabor-filter images were 0.976 and 0.981 respectively.
Conclusions
The method illustrates the capability of automated segmentation of epithelial and stromal tissue in TMAs based on texture features and an SVM classifier. Applications include tissue specific assessment of gene and protein expression, as well as computerized analysis of the tumor microenvironment.
Virtual slides
The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/4123422336534537
doi:10.1186/1746-1596-7-22
PMCID: PMC3315400  PMID: 22385523
Image analysis; Texture classification; Pattern recognition; Stroma; Epithelium; Local binary patterns; Haralick; Gabor; Support vector machine
3.  Phospholipase PLA2G7, associated with aggressive prostate cancer, promotes prostate cancer cell migration and invasion and is inhibited by statins 
Oncotarget  2011;2(12):1176-1190.
Prostate cancer is the second leading cause of cancer mortality in men in developed countries. Due to the heterogeneous nature of the disease, design of novel personalized treatments is required to achieve efficient therapeutic responses. We have recently identified phospholipase 2 group VII (PLA2G7) as a potential drug target especially in ERG oncogene positive prostate cancers. Here, the expression profile of PLA2G7 was studied in 1137 prostate cancer and 409 adjacent non-malignant prostate tissues using immunohistochemistry to validate its biomarker potential and putative association with disease progression. In order to reveal the molecular alterations induced by PLA2G7 impairment, lipidomic and gene expression profiling was performed in response to PLA2G7 silencing in cultured prostate cancer cells. Moreover, the antineoplastic effect of statins combined with PLA2G7 impairment was studied in prostate cancer cells to evaluate the potential of repositioning of in vivo compatible drugs developed for other indications towards anti-cancer purposes. The results indicated that PLA2G7 is a cancer-selective biomarker in 50% of prostate cancers and associates with aggressive disease. The alterations induced by PLA2G7 silencing highlighted the potential of PLA2G7 inhibition as an anti-proliferative, pro-apoptotic and anti-migratorial therapeutic approach in prostate cancer. Moreover, the anti-proliferative effect of PLA2G7 silencing was potentiated by lipid-lowering statins in prostate cancer cells. Taken together, our results support the potential of PLA2G7 as a biomarker and a drug target in prostate cancer and present a rationale for combining PLA2G7 inhibition with the use of statins in prostate cancer management.
PMCID: PMC3282076  PMID: 22202492
Prostate cancer; PLA2G7; drug target; biomarker; statins
4.  Radical Prostatectomy Versus Watchful Waiting in Localized Prostate Cancer: the Scandinavian Prostate Cancer Group-4 Randomized Trial 
Background
The benefit of radical prostatectomy in patients with early prostate cancer has been assessed in only one randomized trial. In 2005, we reported that radical prostatectomy improved prostate cancer survival compared with watchful waiting after a median of 8.2 years of follow-up. We now report results after 3 more years of follow-up.
Methods
From October 1, 1989, through February 28, 1999, 695 men with clinically localized prostate cancer were randomly assigned to radical prostatectomy (n = 347) or watchful waiting (n = 348). Follow-up was complete through December 31, 2006, with histopathologic review and blinded evaluation of causes of death. Relative risks (RRs) were estimated using the Cox proportional hazards model. Statistical tests were two-sided.
Results
During a median of 10.8 years of follow-up (range = 3 weeks to 17.2 years), 137 men in the surgery group and 156 in the watchful waiting group died (P = .09). For 47 of the 347 men (13.5%) who were randomly assigned to surgery and 68 of the 348 men (19.5%) who were not, death was due to prostate cancer. The difference in cumulative incidence of death due to prostate cancer remained stable after about 10 years of follow-up. At 12 years, 12.5% of the surgery group and 17.9% of the watchful waiting group had died of prostate cancer (difference = 5.4%, 95% confidence interval [CI] = 0.2 to 11.1%), for a relative risk of 0.65 (95% CI = 0.45 to 0.94; P = .03). The difference in cumulative incidence of distant metastases did not increase beyond 10 years of follow-up. At 12 years, 19.3% of men in the surgery group and 26% of men in the watchful waiting group had been diagnosed with distant metastases (difference = 6.7%, 95% CI = 0.2 to 13.2%), for a relative risk of 0.65 (95% CI = 0.47 to 0.88; P = .006). Among men who underwent radical prostatectomy, those with extracapsular tumor growth had 14 times the risk of prostate cancer death as those without it (RR = 14.2, 95% CI = 3.3 to 61.8; P < .001).
Conclusion
Radical prostatectomy reduces prostate cancer mortality and risk of metastases with little or no further increase in benefit 10 or more years after surgery.
doi:10.1093/jnci/djn255
PMCID: PMC2518167  PMID: 18695132
5.  PROLIFERATION OF B AND T CELLS IN MIXED LYMPHOCYTE CULTURES 
Electrophoretically fractionated CBA/Ca spleen T cells alone respond to allogeneic cells in one-way MLC and to PHA. They do not respond to E. coli LPS. B cells alone do not respond to allogeneic cells nor to PHA, but do respond to LPS. When karyotypically distinguishable syngeneic mixtures of T and B lymphocytes are stimulated with allogeneic cells, at the most 5% of mitoses on 5–9th culture day are of B cell origin. This indicates that B cells are not substantially recruited to proliferate in the MLC.
PMCID: PMC2180546  PMID: 4268630

Results 1-5 (5)