Morphometrical malignancy grading is a valuable prognostic factor in invasive ductal breast cancer

Association between Nuclear Morphometry Parameters and Gleason Grade in Patients with Prostatic Cancer

Objective: Gleason scoring system remains the pathological method of choice for prostate cancer (Pca) grading. However, this method of tumor tissue architectural structure grading is still affected by subjective assessment and might succumb to several disadvantages, mainly inter-observer variability. These limitations might be diminished by determining characteristic cellular heterogeneity parameters which might improve Gleason scoring homogeneity. One of the quantitative tools of tumor assessment is the morphometric characterization of tumor cell nuclei. We aimed to test the relationship between various morphometric measures and the Gleason score assigned to different prostate cancer samples. Materials and Methods: We reviewed 60 prostate biopsy samples performed at a tertiary uro-oncology center. Each slide was assigned a Gleason grade according to the International Society of Urological Pathology contemporary grading system by a single experienced uro-pathologist. Samples were assigned into groups from grades 3 to 5. Next, the samples were digitally scanned (×400 magnification) and sampled on a computer using Image-Pro-Plus software©. Manual segmentation of approximately 100 selected tumor cells per sample was performed, and a computerized measurement of 54 predetermined morphometric properties of each cell nuclei was recorded. These characteristics were used to compare the pathological group grades assigned to each specimen. Results: Initially, of the 54 morphometric parameters evaluated, 38 were predictive of Gleason grade (p < 0.05). On multivariate analysis, 7 independent parameters were found to be discriminative of different Pca grades: minimum radius shape, intensity—minimal gray level, intensity—maximal gray level, character—gray level (green), character—gray level (blue), chromatin color, fractal dimension, and chromatin texture. A formula to predict the presence of Gleason grade 3 vs. grades 4 or 5 was developed (97.2% sensitivity, 100% specificity). Discussion: The suggested morphometry method based on seven selected parameters is highly sensitive and specific in predicting Gleason score ≥ 4. Since discriminating Gleason score 3 from ≥4 is essential for proper treatment selection, this method might be beneficial in addition to standard pathological tissue analysis in reducing variability among pathologists.

Role of Nuclear Morphometry in Breast Cancer and its Correlation with Cytomorphological Grading of Breast Cancer: A Study of 64 Cases

Background:

Fine needle aspiration cytology (FNAC) is a simple, rapid, inexpensive, and reliable method of diagnosis of breast mass. Cytoprognostic grading in breast cancers is important to identify high-grade tumors. Computer-assisted image morphometric analysis has been developed to quantitate as well as standardize various grading systems.

Aims:

To apply nuclear morphometry on cytological aspirates of breast cancer and evaluate its correlation with cytomorphological grading with derivation of suitable cutoff values between various grades.

Settings and Designs:

Descriptive cross-sectional hospital-based study.

Materials and Methods:

This study included 64 breast cancer cases (29 of grade 1, 22 of grade 2, and 13 of grade 3). Image analysis was performed on Papanicolaou stained FNAC slides by NIS –Elements Advanced Research software (Ver 4.00). Nuclear morphometric parameters analyzed included 5 nuclear size, 2 shape, 4 texture, and 2 density parameters.

Results:

Nuclear size parameters showed an increase in values with increasing cytological grades of carcinoma. Nuclear shape parameters were not found to be significantly different between the three grades. Among nuclear texture parameters, sum intensity, and sum brightness were found to be different between the three grades.

Conclusion:

Nuclear morphometry can be applied to augment the cytology grading of breast cancer and thus help in classifying patients into low and high-risk groups.

Ductal carcinoma in situ of the breast (DCIS) with heterogeneity of nuclear grade: prognostic effects of quantitative nuclear assessment

BACKGROUND

Previously, 50% of patients with breast ductal carcinoma in situ (DCIS) had more than one nuclear grade, and neither worst nor predominant nuclear grade was significantly associated with development of invasive carcinoma. Here, we used image analysis in addition to histologic evaluation to determine if quantification of nuclear features could provide additional prognostic information and hence impact prognostic assessments.

METHODS

Nuclear image features were extracted from about 200 nuclei of each of 80 patients with DCIS who underwent lumpectomy alone, and received no adjuvant systemic therapy. Nuclear images were obtained from 20 representative nuclei per duct, from each of a group of 5 ducts, in two separate fields, for 10 ducts. Reproducibility of image analysis features was determined, as was the ability of features to discriminate between nuclear grades. Patient information was available about clinical factors (age and method of DCIS detection), pathologic factors (DCIS size, nuclear grade, margin size, and amount of parenchymal involvement), and 39 image features (morphology, densitometry, and texture). The prognostic effects of these factors and features on the development of invasive breast cancer were examined with Cox step-wise multivariate regression.

RESULTS

Duplicate measurements were similar for 89.7% to 97.4% of assessed image features. For the pooled assessment with approximately 200 nuclei per patient, a discriminant function with one densitometric and two texture features was significantly (p < 0.001) associated with nuclear grading, and provided 78.8% correct jackknifed classification of a patient's nuclear grade. In multivariate assessments, image analysis nuclear features had significant prognostic associations (p <or= 0.05) with the development of invasive breast cancer. Texture (difference entropy, p < 0.001; contrast, p < 0.001; peak transition probability, p = 0.01), densitometry (range density, p = 0.004), and measured margin (p = 0.05) were associated with development of invasive disease for the pooled data across all ducts.

CONCLUSION

Image analysis provided reproducible assessments of nuclear features which quantitated differences in nuclear grading for patients. Quantitative nuclear image features indicated prognostically significant differences in DCIS, and may contribute additional information to prognostic assessments of which patients are likely to develop invasive disease.

Mammakarzinomgraduierung an Gewebestanzen

The grading of invasive breast cancers according to Bloom and Richardson (Nottingham modification) provides one of the most important prognostic factors in addition to size and the status of the lymph nodes. Diagnostic reproducibility has been problematic in daily practice as the required criteria for selection and extent of the grading area are frequently not present in the punch biopsies.A total of 346 cases were retrospectively used to compare routine grading from surgical preparations with an equivalently small sample from punch biopsies. In addition, a modified grading of these small samples was developed with Ki-67 immunochemistry and the measurement of core size. In the case of modified grading, 1-3 points were given for Ki-67 and average maximum core diameter. Tubule development was evaluated with 1 or 2 points. A comparison for recurrence free survival and total survival showed significant prognostic differences between 3-5 points (low risk) and 6-8 points (high risk) in uni- and multivariate analyses. The evaluation criteria for Nottingham-Bloom-Richardson grading in a small tissue sample, such as that from a punch biopsy, can hardly be fulfilled. In our series, prognostic value was only found for nodal negative cases. After modification using objective parameters such as nuclear size measurement and Ki-67 proliferation index, a small tissue sample can prove to be of significant prognostic value for nodal negative as well as nodal positive cases.

p300 Modulates Nuclear Morphology in Prostate Cancer

Alterations in nuclear structure distinguish cancer cells from noncancer cells. These nuclear alterations can be translated into quantifiable features by digital image analysis in a process known as quantitative nuclear morphometry. Recently, quantitative nuclear morphometry has been shown to predict metastasis and biochemical recurrence of prostate cancer. However, little is known about the cellular mechanisms underlying these nuclear morphometric changes. Alterations of nuclear matrix proteins are frequently involved in changes of nuclear structure. A number of co-activators interact with these nuclear structure–related proteins, suggesting that they might be involved in quantitative nuclear morphometry changes. We have shown previously that the transcriptional co-activator p300 is involved in prostate cancer progression. However, the ability of a transcriptional regulator like p300 to modulate nuclear morphology has not been described previously. In the present study, we show that p300 expression in prostate cancer biopsy tissue from 95 patients correlates with quantifiable nuclear alterations. Moreover, we show that transfection of p300 into prostate cancer cells in culture induces quantifiable nuclear alterations, such as diameter, perimeter, and absorbance among others, as assessed by digital image analysis. These alterations correlate individually with aggressive features in prostate cancer, such as expression of the proliferation marker Ki-67 and extraprostatic extension of the tumor. Finally, we found that transfection of p300 into prostate cancer cells specifically increases mRNA and protein levels of nuclear matrix peptides lamins A and C, suggesting that these proteins mediate the p300-induced effects. These findings reveal a new insight into the transcriptional and structural regulation of prostate cancer.

Computerized Morphometric Study of Thyroid Follicular Carcinoma in Correlation with Known Prognostic Factors

This study investigates the correlation between computer-assisted nuclear morphometry and known prognostic factors in thyroid follicular carcinoma. Thirty-six patients with thyroid follicular carcinoma who underwent surgery between 1991 and 2001 were grouped according to sex, age, size of the primary lesion, the presence of vascular invasion, and metastases. Four nuclear parameters were measured and analyzed: mean nuclear area, mean nuclear perimeter, largest to smallest diameter ratio of the nuclei, and coefficient of variation of the nuclear area. Our results indicated that none of the chosen nuclear variables were significantly correlated with the prognostic factors studied. In conclusion, nuclear morphometry does not seem to correlate with known prognostic factors and cannot serve as an additional predicting factor for biologic behavior.

Prognostic value of proliferation in invasive breast cancer: a review

Breast cancer is the leading cause of death among solid tumours in women, and its incidence is increasing in the West. Adjuvant chemotherapy and hormonal treatment improve survival but have potentially serious side effects, and are costly. Because adjuvant treatment should be given to high risk patients only, and traditional prognostic factors (lymph node status, tumour size) are insufficiently accurate, better predictors of high risk and treatment response are needed. Invasive breast cancer metastasises haematogenously very early on, so many breast cancer prognosticators are directly or indirectly related to proliferation. Although studies evaluating the role of individual proliferation regulating genes have greatly increased our knowledge of this complex process, the functional end result-cells dividing-has remained the most important prognostic factor. This article reviews the prognostic value of different proliferation assays in invasive breast cancer, and concludes that increased proliferation correlates strongly with poor prognosis, irrespective of the methodology used. Mitosis counting provides the most reproducible and independent prognostic value, and Ki67/MIB1 labelling and cyclin A index are promising alternatives that need methodological fine tuning.

Endometriosis and the neoplastic process

Endometriosis is a frequent disorder that commonly presents with infertility and pelvic pain. Although the precise aetiology of endometriosis is unclear, it is generally considered to involve multiple genetic, environmental, immunological, angiogenic and endocrine processes. Genetic factors have been implicated in endometriosis but the susceptibility genes remain largely unknown. Although endometriosis is a benign disorder, recent studies of endometriosis suggest endometriosis could be viewed as a neoplastic process. Evidence to support this hypothesis includes the increased susceptibility to develop ovarian clear-cell and endometrioid cancers in the presence of endometriosis, and molecular similarities between endometriosis and cancer. In this article we discuss (i) the evidence suggesting that endometriosis might be viewed as a neoplastic process, and (ii) the implications of this hypothesis for elucidating the pathogenesis of endometriosis and developing novel methods of diagnostic classification and individualised treatments.