Tissue architecture analysis in prostate cancer and its precursors: An innovative approach to computerized histometry

Phase II Trial of Chemopreventive Effects of Levonorgestrel on Ovarian and Fallopian Tube Epithelium in Women at High Risk for Ovarian Cancer: An NRG Oncology Group/GOG Study

A large body of epidemiologic evidence has shown that use of progestin-containing preparations lowers ovarian cancer risk. The purpose of the current study was to gather further preclinical evidence supporting progestins as cancer chemopreventives by demonstrating progestin-activation of surrogate endpoint biomarkers pertinent to cancer prevention in the genital tract of women at increased risk of ovarian cancer. There were 64 women enrolled in a multi-institutional randomized trial who chose to undergo risk-reducing bilateral salpingo-oophorectomy (BSO) and to receive the progestin levonorgestrel or placebo for 4 to 6 weeks prior to undergoing BSO. The ovarian and fallopian tube epithelia (FTE) were compared immunohistochemically for effects of levonorgestrel on apoptosis (primary endpoint). Secondary endpoints included TGFβ isoform expression, proliferation, and karyometric features of nuclear abnormality. In both the ovary and fallopian tube, levonorgestrel did not confer significant changes in apoptosis or expression of the TGFβ1, 2, or 3 isoforms. In the ovarian epithelium, treatment with levonorgestrel significantly decreased the proliferation index. The mean ovarian Ki-67 value in the placebo arm was 2.027 per 100 cells versus 0.775 per 100 cells in the levonorgestrel arm (two-sided P value via Mann-Whitney U test = 0.0114). The karyometric signature of nuclei in both the ovarian and FTE deviated significantly from normal controls (women at average risk of ovarian cancer), but was significantly less abnormal in women treated with levonorgestrel. These karyometric data further support the idea that progestins may clear genetically abnormal cells and act as chemopreventive agents against ovarian and fallopian tube cancer.

Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3'-Diaminobenzidine&Haematoxylin

The comparative study of the results of various segmentation methods for the digital images of the follicular lymphoma cancer tissue section is described in this paper. The sensitivity and specificity and some other parameters of the following adaptive threshold methods of segmentation: the Niblack method, the Sauvola method, the White method, the Bernsen method, the Yasuda method and the Palumbo method, are calculated. Methods are applied to three types of images constructed by extraction of the brown colour information from the artificial images synthesized based on counterpart experimentally captured images. This paper presents usefulness of the microscopic image synthesis method in evaluation as well as comparison of the image processing results. The results of thoughtful analysis of broad range of adaptive threshold methods applied to: (1) the blue channel of RGB, (2) the brown colour extracted by deconvolution and (3) the ’brown component’ extracted from RGB allows to select some pairs: method and type of image for which this method is most efficient considering various criteria e.g. accuracy and precision in area detection or accuracy in number of objects detection and so on. The comparison shows that the White, the Bernsen and the Sauvola methods results are better than the results of the rest of the methods for all types of monochromatic images. All three methods segments the immunopositive nuclei with the mean accuracy of 0.9952, 0.9942 and 0.9944 respectively, when treated totally. However the best results are achieved for monochromatic image in which intensity shows brown colour map constructed by colour deconvolution algorithm. The specificity in the cases of the Bernsen and the White methods is 1 and sensitivities are: 0.74 for White and 0.91 for Bernsen methods while the Sauvola method achieves sensitivity value of 0.74 and the specificity value of 0.99. According to Bland-Altman plot the Sauvola method selected objects are segmented without undercutting the area for true positive objects but with extra false positive objects. The Sauvola and the Bernsen methods gives complementary results what will be exploited when the new method of virtual tissue slides segmentation be develop.

Virtual Slides

The virtual slides for this article can be found here: slide 1: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617947952577 and slide 2: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617948230017.

Towards an automated virtual slide screening: theoretical considerations and practical experiences of automated tissue-based virtual diagnosis to be implemented in the Internet

Aims

To develop and implement an automated virtual slide screening system that distinguishes normal histological findings and several tissue – based crude (texture – based) diagnoses.

Theoretical considerations

Virtual slide technology has to handle and transfer images of GB Bytes in size. The performance of tissue based diagnosis can be separated into a) a sampling procedure to allocate the slide area containing the most significant diagnostic information, and b) the evaluation of the diagnosis obtained from the information present in the selected area. Nyquist's theorem that is broadly applied in acoustics, can also serve for quality assurance in image information analysis, especially to preset the accuracy of sampling. Texture – based diagnosis can be performed with recursive formulas that do not require a detailed segmentation procedure. The obtained results will then be transferred into a "self-learning" discrimination system that adjusts itself to changes of image parameters such as brightness, shading, or contrast.

Methods

Non-overlapping compartments of the original virtual slide (image) will be chosen at random and according to Nyquist's theorem (predefined error-rate). The compartments will be standardized by local filter operations, and are subject for texture analysis. The texture analysis is performed on the basis of a recursive formula that computes the median gray value and the local noise distribution. The computations will be performed at different magnifications that are adjusted to the most frequently used objectives (*2, *4.5, *10, *20, *40). The obtained data are statistically analyzed in a hierarchical sequence, and in relation to the clinical significance of the diagnosis.

Results

The system has been tested with a total of 896 lung cancer cases that include the diagnoses groups: cohort (1) normal lung – cancer; cancer subdivided: cohort (2) small cell lung cancer – non small cell lung cancer; non small cell lung cancer subdivided: cohort (3) squamous cell carcinoma – adenocarcinoma – large cell carcinoma. The system can classify all diagnoses of the cohorts (1) and (2) correctly in 100%, those of cohort (3) in more than 95%. The percentage of the selected area can be limited to only 10% of the original image without any increased error rate.

Conclusion

The developed system is a fast and reliable procedure to fulfill all requirements for an automated "pre-screening" of virtual slides in lung pathology.

Risk stratification after radical prostatectomy in men with pathologically organ-confined prostate cancer using volume-weighted mean nuclear volume

OBJECTIVE

We examined the impact of volume-weighted mean nuclear volume (MNV) on biochemical failure after radical prostatectomy (RP) in pathologically organ-confined prostate cancer (PC) and developed a prognostic factor-based stratification model for these patients.

PATIENTS AND METHODS

We analyzed 141 patients with pathologically organ-confined PC treated solely with RP. Unbiased estimates of MNV were calculated from biopsy specimens based on a stereological method, and compared with other clinical and pathologic findings including patient age, pre-treatment PSA, biopsy and RP specimen Gleason score, pathologic stage, total cancer volume, index cancer volume, tumor differentiation, number of tumor foci, main tumor location, and surgical margin status, with regard to prediction of disease outcome after RP using Cox proportional hazard models.

RESULTS

The median follow-up was 38.6 months (range 4--119 months). Twenty patients (14.2%) experienced biochemical failure. On multivariate analysis, MNV was demonstrated to be an independent prognostic factor, along with pre-treatment PSA and total cancer volume (P=0.0004, 0.0184, and 0.0285, respectively). All patients were stratified into three groups according to their prognostic scores developed on the basis of multivariate analysis, with statistically significant prognostic differences revealed for each of the between-group comparisons.

CONCLUSION

The results demonstrated that estimates of MNV contribute most significantly to the prediction of biochemical control of pathologically organ-confined PC. The combination of MNV with other independent predictors such as pre-treatment PSA and total cancer volume provided a statistically verifiable basis for risk stratification, facilitating more accurate prediction of disease outcome.

Hereditary non-polipomatous colorectal cancer: hereditary predisposition, diagnosis and prevention

BACKGROUND: Colorectal cancer is the third in frequency and the second in mortality in developed countries. In Brazil, it is among the six more common malignant neoplasias. About 20% of colorectal tumors have some hereditary component. AIM: This study presents a review of genetic and clinic aspects, as well as diagnosis and prevention of the hereditary non-polipomatous colorectal cancer, that is the more frequent form of hereditary colorectal cancer. This approach is important because, currently there are possibilities of management, prevention and surveillance specific to individuals at-risk for hereditary non-polipomatous colorectal cancer that can lead to a great improvement in patients' survival and their at-risk relatives.

Differences in gene expression in prostate cancer, normal appearing prostate tissue adjacent to cancer and prostate tissue from cancer free organ donors

Background

Typical high throughput microarrays experiments compare gene expression across two specimen classes – an experimental class and baseline (or comparison) class. The choice of specimen classes is a major factor in the differential gene expression patterns revealed by these experiments. In most studies of prostate cancer, histologically malignant tissue is chosen as the experimental class while normal appearing prostate tissue adjacent to the tumor (adjacent normal) is chosen as the baseline against which comparison is made. However, normal appearing prostate tissue from tumor free organ donors represents an alterative source of baseline tissue for differential expression studies.

Methods

To examine the effect of using donor normal tissue as opposed to adjacent normal tissue as a baseline for prostate cancer expression studies, we compared, using oligonucleotide microarrays, the expression profiles of primary prostate cancer (tumor), adjacent normal tissue and normal tissue from tumor free donors.

Results

Statistical analysis using Significance Analysis of Microarrays (SAM) demonstrates the presence of unique gene expression profiles for each of these specimen classes. The tumor v donor expression profile was more extensive that the tumor v adjacent normal profile. The differentially expressed gene lists from tumor v donor, tumor v adjacent normal and adjacent normal v donor comparisons were examined to identify regulated genes. When donors were used as the baseline, similar genes are highly regulated in both tumor and adjacent normal tissue. Significantly, both tumor and adjacent normal tissue exhibit significant up regulation of proliferation related genes including transcription factors, signal transducers and growth regulators compared to donor tissue. These genes were not picked up in a direct comparison of tumor and adjacent normal tissues.

Conclusions

The up-regulation of these gene types in both tissue types is an unexpected finding and suggests that normal appearing prostate tissue can undergo genetic changes in response to or in expectation of morphologic cancer. A possible field effect surrounding prostate cancers and the implications of these findings for characterizing gene expression changes in prostate tumors are discussed.

Impact of Volume Weighted Mean Nuclear Volume on Outcomes Following Salvage Radiation Therapy After Radical Prostatectomy

PURPOSE

Although salvage radiation therapy (RT) is a potentially curative treatment option for men with biochemical failure after radical prostatectomy (RP), to our knowledge there are no definitive pretreatment factors predicting patients likely to benefit from this treatment. We examined the impact of volume weighted mean nuclear volume (MNV) of biopsy specimens on disease outcomes and describe its usefulness as a new independent predictor.

MATERIALS AND METHODS

We analyzed 33 patients who received salvage RT for biochemical failure after RP, including 11 who had received neoadjuvant hormone therapy before RP. Salvage RT was delivered to the prostatic bed at a total dose of 60 Gy with a 4-field contoured technique. Unbiased estimates of MNV were calculated from more than 100 cancer nuclei per patient captured from biopsy specimens based on a stereological method and compared with other clinical and pathological findings, including patient age, pretreatment prostate specific antigen (PSA), PSA density, biopsy Gleason score, neoadjuvant therapy, surgical Gleason score, pathological stage, tumor volume, surgical margin status, biochemical disease-free duration before RT, nadir PSA and PSA doubling time before RT, and pre-RT PSA with regard to predicting the disease outcome after salvage RT.

RESULTS

The median followup after salvage RT was 43.4 months. A total of 17 patients (52%) experienced biochemical failure a median of 6.7 months (range 0 to 48.1) after RT. On univariate analysis MNV and log(pre-RT PSA) were significant predictors of disease outcome in all patients and in the 22 nonneoadjuvant patient subset (p = 0.0124 and 0.0159, respectively). Log(nadir PSA) and PSA doubling time were also significant in the latter subset (p = 0.0287 and 0.0475, respectively). However, dual multivariate analysis revealed that MNV was the only independent predictor in the 2 groups (logistic regression analysis p = 0.00931 and 0.03511, and Cox proportional hazards analysis p = 0.00483 and 0.02277, respectively). There was a statistically significant biochemical disease-free survival advantage for small vs large MNV in each data set (p = 0.0072 and 0.0036, respectively).

CONCLUSIONS

Our results suggest that an estimate of MNV contributes significantly to the prediction of biochemical control after salvage RT. However, further investigation in a larger nonneoadjuvant population is needed to confirm its significance in combination with other clinical and pathological findings.

Computer-assisted image analysis-derived intermediate endpoints

The development of prostatic lesions undergoes a slow progression. To establish efficacy of chemopreventive intervention it is therefore necessary to define surrogate endpoint biomarkers. Such biomarkers should be sensitive in their ability to indicate response. They should be objective, ie, the result of measurement, and numerically defined so that a statistical validation of response is possible. They should be able to indicate not only a halt of progression of a lesion, but also a reversal of progression. The spatial and statistical distribution of nuclear chromatin in the secretory and luminal cells in prostatic intraepithelial neoplastic lesions has been shown to be well defined. It can be represented by a set of features. These have been used to define a progression curve along which progression or regression of a lesion can be assessed. One could define a fixed endpoint, or one might choose to accept a statistically significant regression along the progression curve as criterion for chemopreventive efficacy. Expected difficulties could arise from lesion heterogeneity, as it would affect the sampling, and from multifocal lesions of differing progressions. Lesion heterogeneity thus limits the precision with which regression could be detected. These problems might be partially overcome by observations taken in histologically normal appearing regions of the prostate. The nuclear chromatin pattern of secretory cell nuclei measured in such tissue regions from prostates harboring intraepithelial or malignant lesions has been shown to exhibit distinctive changes from the chromatin pattern seen in secretory cell nuclei from prostates free from any such lesions. These changes appear to be expressed in the tissue up to a substantial distance from a lesion. The expression of changes in the nuclear chromatin suggests the existence of an intraepithelial preneoplastic lesion that can be detected by biomarkers, but which is not apparent from visual microscopic inspection. Since chemoprevention might be expected to be most effective at the earliest stages of lesion development, the assessment of such early alterations is seen as highly relevant to efforts to validate the efficacy of chemopreventive intervention.