Nuclear Texture Analysis Research Articles

Association Between Proportion of Nuclei With High Chromatin Entropy and Prognosis in Gynecological Cancers.

BackgroundNuclear texture analysis measuring differences in chromatin structure has provided prognostic biomarkers in several cancers. There is a need for improved cell-by-cell chromatin analysis to detect nuclei with highly disorganized chromatin. The purpose of this study was to develop a method for detecting nuclei with high chromatin entropy and to evaluate the association between the presence of such deviating nuclei and prognosis.MethodsA new texture-based biomarker that characterizes each cancer based on the proportion of high–chromatin entropy nuclei (<25% vs ≥25%) was developed on a discovery set of 175 uterine sarcomas. The prognostic impact of this biomarker was evaluated on a validation set of 179 uterine sarcomas, as well as on independent validation sets of 246 early-stage ovarian carcinomas and 791 endometrial carcinomas. More than 1 million images of nuclei stained for DNA were included in the study. All statistical tests were two-sided.ResultsAn increased proportion of high–chromatin entropy nuclei was associated with poor clinical outcome. The biomarker predicted five-year overall survival for uterine sarcoma patients with a hazard ratio (HR) of 2.02 (95% confidence interval [CI] = 1.43 to 2.84), time to recurrence for ovarian cancer patients (HR = 2.91, 95% CI = 1.74 to 4.88), and cancer-specific survival for endometrial cancer patients (HR = 3.74, 95% CI = 2.24 to 6.24). Chromatin entropy was an independent prognostic marker in multivariable analyses with clinicopathological parameters (HR = 1.81, 95% CI = 1.21 to 2.70, for sarcoma; HR = 1.71, 95% CI = 1.01 to 2.90, for ovarian cancer; and HR = 2.03, 95% CI = 1.19 to 3.45, for endometrial cancer).ConclusionsA novel method detected high–chromatin entropy nuclei, and an increased proportion of such nuclei was associated with poor prognosis. Chromatin entropy supplemented existing prognostic markers in multivariable analyses of three gynecological cancer cohorts.

Changes in Chromatin Structure in Curettage Specimens Identifies High-Risk Patients in Endometrial Cancer.

Most endometrial carcinoma patients are diagnosed at an early stage with a good prognosis. However, a relatively low fraction with lethal disease constitutes a substantial number of patients due to the high incidence rate. Preoperative identification of patients with high risk and low risk for poor outcome is necessary to tailor treatment. Nucleotyping refers to characterization of cell nuclei by image cytometry, including the assessment of chromatin structure by nuclear texture analysis. This method is a strong prognostic marker in many cancers but has not been evaluated in preoperative curettage specimens from endometrial carcinoma. The prognostic impact of changes in chromatin structure quantified with Nucleotyping was evaluated in preoperative curettage specimens from 791 endometrial carcinoma patients prospectively included in the MoMaTEC multicenter trial. Nucleotyping was an independent prognostic marker of disease-specific survival in preoperative curettage specimens among patients with Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stage I-II disease (HR=2.9; 95% CI, 1.2-6.5; P = 0.013) and significantly associated with age, FIGO stage, histologic type, histologic grade, myometrial infiltration, lymph node status, curettage histology type, and DNA ploidy. Nucleotyping in preoperative curettage specimens is an independent prognostic marker for disease-specific survival, with potential to supplement existing parameters for risk stratification to tailor treatment. This is the first study to evaluate the prognostic impact of Nucleotyping in curettage specimens from endometrial carcinoma and shows that this may be a clinically useful prognostic marker in endometrial cancer. External validation is warranted. Cancer Epidemiol Biomarkers Prev; 26(1); 61-67. ©2016 AACR.

Highlights of This Issue

The association between aspirin use and risk of pancreatic cancer has been inconsistent across studies. Risch and colleagues performed a population-based study of pancreatic cancer patients and control subjects in Shanghai, China. Participants were asked about episodes of regular use of aspirin, tablets per day or week, and ages that use started and stopped. Ever-regular use of aspirin was associated with lowered risk of pancreatic cancer. Risk decreased 8% per each cumulative year of use. Regular use of aspirin thus appears to reduce risk of pancreatic cancer by almost half.The effects of menthol on smoking behavior and carcinogen exposure have been inconclusive. Menthol-glucuronide (MG) has been identified as the most significant metabolite directly related to smoking. Hsu and colleagues studied MG in relation to smoking behavior and metabolomic profiles. Smokers smoked two cigarettes in the laboratory one hour apart, and blood nicotine, MG, and exhaled carbon monoxide (CO) boosts were determined (the difference before and after smoking). MG boost was positively correlated with CO boost, nicotine boost, average puff volume, puff duration, and total smoke exposure. Plasma MG boost is a new smoking behavior biomarker that may provide novel information over self-reported use of menthol cigarettes.While most endometrial carcinoma patients are diagnosed at an early stage with a good prognosis, the relatively low fraction of endometrial carcinoma patients with lethal disease constitutes a substantial number of patients due to the high incidence rate. Preoperative identification of these high-risk patients is necessary to tailor treatment. Nucleotyping refers to the characterization of cell nuclei by image cytometry and assessment of chromatin structure by nuclear texture analysis. This method has not been evaluated in preoperative curettage specimens from endometrial carcinoma patients. The prognostic impact of changes in chromatin structure quantified with Nucleotyping was evaluated by Hveem and colleagues in specimens from endometrial carcinoma patients. Nucleotyping in preoperative curettage specimens is an independent prognostic marker for disease-specific survival, with potential to supplement existing parameters for endometrial carcinoma risk stratification.Early-life socioeconomic status (SES) may play a role in cancer risk in adulthood; however, measuring SES retrospectively presents challenges. Stroup and colleagues used parental occupation on birth certificates to ascertain early-life SES. Cancer incidence was then determined by linkage to the Utah Cancer Registry. Females with low SES at birth had lower risk of breast cancer compared with those in the highest SES group. SES was inversely associated with melanoma and prostate cancer. Women born into lower SES neighborhoods had a significantly increased risk for invasive cervical cancer, and neighborhood SES had similar effects for melanoma and prostate cancers. Individual SES derived from parental occupation at birth was associated with altered risk for several cancer sites.

Single Molecule Localization Microscopy of Mammalian Cell Nuclei on the Nanoscale.

Nuclear texture analysis is a well-established method of cellular pathology. It is hampered, however, by the limits of conventional light microscopy (ca. 200 nm). These limits have been overcome by a variety of super-resolution approaches. An especially promising approach to chromatin texture analysis is single molecule localization microscopy (SMLM) as it provides the highest resolution using fluorescent based methods. At the present state of the art, using fixed whole cell samples and standard DNA dyes, a structural resolution of chromatin in the 50–100 nm range is obtained using SMLM. We highlight how the combination of localization microscopy with standard fluorophores opens the avenue to a plethora of studies including the spatial distribution of DNA and associated proteins in eukaryotic cell nuclei with the potential to elucidate the functional organization of chromatin. These views are based on our experience as well as on recently published research in this field.

Entropy-based adaptive nuclear texture features are independent prognostic markers in a total population of uterine sarcomas.

Nuclear texture analysis measures the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image and is a promising quantitative tool for prognosis of cancer. The aim of this study was to evaluate the prognostic value of entropy-based adaptive nuclear texture features in a total population of 354 uterine sarcomas. Isolated nuclei (monolayers) were prepared from 50 µm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices, and two superior adaptive texture features were calculated from each matrix. The 5-year crude survival was significantly higher (P < 0.001) for patients with high texture feature values (72%) than for patients with low feature values (36%). When combining DNA ploidy classification (diploid/nondiploid) and texture (high/low feature value), the patients could be stratified into three risk groups with 5-year crude survival of 77, 57, and 34% (Hazard Ratios (HR) of 1, 2.3, and 4.1, P < 0.001). Entropy-based adaptive nuclear texture was an independent prognostic marker for crude survival in multivariate analysis including relevant clinicopathological features (HR = 2.1, P = 0.001), and should therefore be considered as a potential prognostic marker in uterine sarcomas. © The Authors. Published 2014 International Society for Advancement of Cytometry

Molecular characteristics and chromatin texture features in acute promyelocytic leukemia

BackgroundAcute promyelocytic leukemia is a cytogenetically well defined entity. Nevertheless, some features observed at diagnosis are related to a worse outcome of the patients.MethodsIn a prospective study, we analyzed peripheral (PB) leukocyte count, immunophenotype, methylation status of CDKN2B, CDKN2A and TP73; FLT3 and NPM1 mutations besides nuclear chromatin texture characteristics of the leukemic cells. We also examined the relation of these features with patient’s outcome.ResultsAmong 19 cases, 4 had a microgranular morphology, 7 presented PB leukocytes >10x109/l, 2 had FLT3-ITD and 3 had FLT3-TKD (all three presenting a methylated CDKN2B). NPM1 mutation was not observed. PB leukocyte count showed an inverse relation with standard deviation of gray levels, contrast, cluster prominence, and chromatin fractal dimension (FD). Cases with FLT3-ITD presented a microgranular morphology, PB leukocytosis and expression of HLA-DR, CD34 and CD11b. Concerning nuclear chromatin texture variables, these cases had a lower entropy, contrast, cluster prominence and FD, but higher local homogeneity, and R245, in keeping with more homogeneously distributed chromatin. In the univariate Cox analysis, a higher leukocyte count, FLT3-ITD mutation, microgranular morphology, methylation of CDKN2B, besides a higher local homogeneity of nuclear chromatin, a lower chromatin entropy and FD were associated to a worse outcome. All these features lost significance when the cases were stratified for FLT3-ITD mutation. Methylation status of CDNK2A and TP73 showed no relation to patient’s survival.Conclusionin APL, patients with FLT3-ITD mutation show different clinical characteristics and have blasts with a more homogeneous chromatin texture. Texture analysis demonstrated that FLTD-ITD was accompanied not only by different cytoplasmic features, but also by a change in chromatin structure in routine cytologic preparations. Yet we were not able to detect chromatin changes by nuclear texture analysis of patients with the FTLD-TKD or methylation of specific genes.

Abstract 4061: Computer-assisted Gleason grading of prostate cancer: Two novel approaches using nuclear shape and texture feature to classify pathologic Gleason grade patterns 3 and 4

Abstract Introduction: We used two novel computer-assisted imaging applications that incorporate nuclear shape and texture analysis to differentiate Gleason grade patterns 3 and 4 of H&amp;Ein a tissue microarray (TMA). The two approaches utilized a variational adaptive segmentation scheme (AdACM) (Rutgers) and the cardinal multiridgelet transform (CMRT) based texture analysis (University of Pittsburgh). Methods: The TMA include 0.6 mm cores from blocks that included Gleason patterns of CaP radical prostatectomy cases from 40 patients. The TMA comprised 13 Gleason patterns 6 (3+3), 8 pattern 7 (3+4), 7 pattern 8 (4+4) and 5 pattern 9 (4+5) Gleason grade (GG) patterns. The AdACM uses 200 × 200 pixel images extracted for nuclear &amp; architectural textural features. All features were based on mathematical energy terms with a shape prior in a multi-level set formulation. The CMRT is an image transform that is translation- and rotation-invariant, and provides a means of displaying texture contents for selection of discriminative features. With a 3-scale decomposition, it gives 8 ridgelet packets and 16 statistical texture features in a 256 x 256 pixel image patch that are averaged over 9 non-overlapping patches in a given image for separation of GG patterns 3 and 4. Results: The CMRT study utilized 3 of 16 texture features extracted from images and trained a Gaussian kernel support vector machine (SVM), a leave-one-out cross-validation showed an accuracy of 94% and AUC of 0.97. For AdACM, nuclear features and architectural features were extracted. Linear Discriminant Analysis (LDA) was employed for feature selection and best features from all three classes could discriminate Gleason grade 3 vs. 4 with an accuracy of 86% via a SVM classifier. Conclusions: Unique quantitative imaging of tissue nuclear shape and texture features can accurately differentiate Gleason patterns 3 and 4. Our research will next evaluate CaP outcomes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4061. doi:1538-7445.AM2012-4061

The Prognostic Value of Adaptive Nuclear Texture Features from Patient Gray Level Entropy Matrices in Early Stage Ovarian Cancer

Background: Nuclear texture analysis gives information about the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image, providing texture features that may be used as quantitative tools for prognosis of human cancer. The aim of the study was to evaluate the prognostic value of adaptive nuclear texture features in early stage ovarian cancer.Methods: 246 cases of early stage ovarian cancer were included in the analysis. Isolated nuclei (monolayers) were prepared from 50 μm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices. A compact set of adaptive features was computed from these matrices.Results: Univariate Kaplan-Meier analysis showed significantly better relapse-free survival (p &lt; 0.001) for patients with low adaptive feature values compared to patients with high adaptive feature values. The 10-year relapse-free survival was about 78% for patients with low feature values and about 52% for patients with high feature values. Adaptive features were found to be of independent prognostic significance for relapse-free survival in a multivariate analysis.Conclusion: Adaptive nuclear texture features from entropy matrices contain prognostic information and are of independent prognostic significance for relapse-free survival in early stage ovarian cancer.

The prognostic value of adaptive nuclear texture features from patient gray level entropy matrices in early stage ovarian cancer.

Background: Nuclear texture analysis gives information about the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image, providing texture features that may be used as quantitative tools for prognosis of human cancer. The aim of the study was to evaluate the prognostic value of adaptive nuclear texture features in early stage ovarian cancer. Methods: 246 cases of early stage ovarian cancer were included in the analysis. Isolated nuclei (monolayers) were prepared from 50 μm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices. A compact set of adaptive features was computed from these matrices. Results: Univariate Kaplan-Meier analysis showed significantly better relapse-free survival (p < 0.001) for patients with low adaptive feature values compared to patients with high adaptive feature values. The 10-year relapse-free survival was about 78% for patients with low feature values and about 52% for patients with high feature values. Adaptive features were found to be of independent prognostic significance for relapse-free survival in a multivariate analysis. Conclusion: Adaptive nuclear texture features from entropy matrices contain prognostic information and are of independent prognostic significance for relapse-free survival in early stage ovarian cancer.

Comparison of nuclear texture analysis and image cytometric DNA analysis for the assessment of dysplasia in Barrett's oesophagus

Background:Dysplasia is a marker of cancer risk in Barrett's oesophagus (BO), but this risk is variable and diagnosis is subject to inter-observer variability. Cancer risk in BO is increased when chromosomal instability is present. Nucleotyping (NT) is a new method that uses high-resolution digital images of nuclei to assess chromatin organisation both quantitatively and qualitatively. We aimed to evaluate NT as a marker of dysplasia in BO and compare with image cytometric DNA analysis (ICM).Methods:In all, 120 patients with BO were studied. The non-dysplastic group (n=60) had specialised intestinal metaplasia only on two consecutive endoscopies after 51 months median follow-up (IQR=25–120 months). The dysplastic group (n=60) had high-grade dysplasia or carcinoma in situ. The two groups were then randomly assigned to a training set and a blinded test set in a 1 : 1 ratio. Image cytometric DNA analysis and NT was then carried out on Feulgen-stained nuclear monolayers.Results:The best-fit model for NT gave a correct classification rate (CCR) for the training set of 83%. The test set was then analysed using the same textural features and yielded a CCR of 78%. Image cytometric DNA analysis alone yielded a CCR of 73%. The combination of ICM and NT yielded a CCR of 84%.Conclusion:Nucleotyping differentiates dysplastic and non-dysplastic BO, with a greater sensitivity than ICM. A combination score based on both techniques performed better than either test in isolation. These data demonstrate that NT/ICM on nuclear monolayers is a very promising single platform test of genomic instability, which may aid pathologists in the diagnosis of dysplasia and has potential as a biomarker in BO.

Nuclear morphometry and texture analysis of B‐cell non‐Hodgkin lymphoma: Utility in subclassification on cytosmears

Non-Hodgkin lymphoma (NHL) is a heterogeneous group of lymphoid neoplasms and accurate subclassification is an essential prerequisite for proper management of patients. This study was aimed at evaluating the utility of nuclear morphometry and textural features on cytology smears to classify the cases of NHL on aspiration cytology. Fine needle aspiration smears of 50 cases of B-cell NHL were included. Various morphometric and texture parameters were obtained by manually tracing the nuclei on digitized images in each case and discriminant analysis performed using various features taken individually as well as all together. The percentage of cells correctly classified to a particular NHL subtype using the discriminant functions so obtained was noted.Our results show that discriminant analysis done on size parameters could correctly classify a greater number of cells than on shape parameters (36.4% vs. 21.2%, respectively). Texture parameters based on single pixel values (first order texture) were inferior (42.8%) to those based on pair of pixels (58.7%) in subtyping of cells. Discriminant analysis based on color parameters was more effective (61.9%) as compared to rest of the morphometric and textural parameters. Using all the morphometric and textural parameters together, 83.3% of cells could be correctly classified to a particular NHL subtype.The present study, perhaps the first study of detailed morphometric analysis on cytosmears, shows that satisfactory classification of NHL on aspiration cytology is possible using nuclear morphometry and textural parameters considered together. These results are promising for further studies on this subject and development of automated cytodiagnosis.

P024 Computerized nuclear texture analysis for the characterization of atypic immature cells in MDS

P024 Computerized nuclear texture analysis for the characterization of atypic immature cells in MDS

Statistical Nuclear Texture Analysis in Cancer Research: A Review of Methods and Applications

In digital pathology, the field of nuclear texture analysis gives information about the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image, providing statistical texture measures that may be used as quantitative tools for diagnosis and prognosis of human cancer. In the present work, we have reviewed nuclear texture analysis in human cancer research, with emphasis on (i) statistical texture analysis methods, (ii) methods for feature evaluation and feature set selection, (iii) classification methods and error estimation, and (iv) the recent literature in the field, focusing on diagnosis- and prognosis-related applications. The application study covers the period from 1995 to 2007. In order to find nuclear features that discriminate robustly between cases from different diagnostic or prognostic classes, a statistical evaluation of features must be performed, and this demands careful experimental design. The present review reveals that it is quite common to evaluate a large number of features on a limited learning set of clinical material, without testing the chosen classifier on an independent validation data set. This easily leads to overoptimistic results. Out of 160 papers, we found only 30 papers in which the classifier was evaluated on an independent validation data set. Even in these studies, some good results have been hampered by small validation groups. However, it is encouraging to note that those publications meeting the requirements of an optimal study are generally showing good results. Thus, it is well documented that nuclear texture analysis is showing promising results as a novel diagnostic and/or prognostic marker. Hopefully, we will soon see that these promising studies will be replicated in large, prospective, multicenter trials.

Differential modulation of nuclear texture, histone acetylation, and MDR1 gene expression in human drug-sensitive and -resistant OV1 cell lines

Image cytometric study of pathological specimens or cell lines has suggested that epigenetic mechanisms are likely to play a major role in determining chromatin patterns evaluable through nuclear texture analysis. We previously reported that nuclear textural changes observed in the OV1-VCR etoposide-resistant ovarian carcinoma cell line were associated with an increased acetylated histone H4 level. In this study we analyzed the effects of treatments with the HDAC inhibitor trichostatin A (TSA) or with nickel subsulfide on histone H4 acetylation, nuclear texture, and MDR1 gene expression in drug-sensitive IGROV1 and drug-resistant OV1-VCR cell lines. In IGROV1 cells, TSA induced an increase in acetylated H4 level associated with a chromatin textural decondensation and an increase in MDR1 gene expression. In OV1-VCR cells, a similar increase in H4 acetylation was observed, but nuclear texture or MDR1 gene expression remained unchanged. ChIP analysis revealed that MDR1 gene expression remained stable in TSA-treated OV1-VCR cells despite a localized increase in H4 acetylation at the promoter level. Analysis of the methylation status of MDR1 promoter showed an increase in DNA methylation at 3 specific sites in OV1-VCR cells, that could participate to TSA low responsiveness in these cells. Treatment with nickel subsulfide induced a decrease in H4 acetylation without any effect on nuclear texture characteristics in both cell lines. In OV1-VCR cells, nickel subsulfide induced a significant down-regulation of the MDR1 gene expression. These results indicate that modulation of histone H4 acetylation level can be associated with up- or down-regulation of the MDR1 gene in OV1 cells. However, this modulation does not always result in chromatin pattern alterations and these data emphasize the complexity of chromatin texture regulation in tumor cells.

Prediction of radiosensitivity in human bladder cell lines using nuclear chromatin phenotype

Nuclear texture analysis measures phenotypic changes in chromatin distribution within a cell nucleus, while the alkaline Comet assay is a sensitive method for measuring the extent of DNA breakage in individual cells. The authors aim to use both methods to provide information about the sensitivity of cells to ionizing radiation. The alkaline Comet assay was performed on six human bladder carcinoma cell lines and one human urothelial cell line exposed to gamma-radiation doses from 0 to 10 Gy. Nuclear chromatin texture analysis of 40 features was then performed in the same cell lines exposed to 0, 2, and 6 Gy to explore if nuclear phenotype was related to radiation sensitivity. Comet assay results demonstrated that the cell lines exhibited different levels of radiosensitivity and could be divided into a radiosensitive and a radioresistant group at >6 Gy. Using stepwise discriminant analysis, a subset of important nuclear texture features that best discriminated between sensitive and resistant cell lines were identified A classification function, defined using these features, correctly classified 81.75% of all cells into their radiosensitive or radioresistant groups based on their pretreatment chromatin phenotype. Posttreatment chromatin changes also varied between cell lines, with sensitive cell lines showing a relaxed chromatin conformation following radiation, whereas resistant cell lines exhibited chromatin condensation. The authors conclude that the alkaline Comet assay and nuclear texture methodologies may prove to be valuable aids in predicting the response of tumor cells to radiotherapy.

Prognostic Value of Adaptive Textural Features–The Effect of Standardizing Nuclear First-Order Gray Level Statistics and Mixing Information from Nuclei Having Different Area

Background: Nuclear texture analysis is a useful method to obtain quantitative information for use in prognosis of cancer. The first-order gray level statistics of a digitized light microscopic nuclear image may be influenced by variations in the image input conditions. Therefore, we have previously standardized the nuclear gray level mean value and standard deviation. However, there is a clear relation between nuclear DNA content, area, first-order statistics, and texture. For nuclei with approximately the same DNA content, the mean gray level increases with an increasing nuclear area. The aims of the present methodical work were to study: (1) whether the prognostic value of adaptive textural features varies with nuclear area, and (2) the effect of standardizing nuclear first-order statistics. Methods: Nuclei from 134 cases of ovarian cancer were grouped into intervals according to nuclear area. Adaptive features were extracted from two different image sets, i.e., standardized and non-standardized nuclear images. Results: The prognostic value of adaptive textural features varied strongly with nuclear area. A standardization of the first-order statistics significantly reduced this prognostic information. Several single features discriminated the two classes of cancer with a correct classification rate of 70%. Conclusion: Nuclei having an area between 2000–4999 pixels contained most of the class distance information between the good and poor prognosis classes of cancer. By considering the relation between nuclear area and texture, we avoided a loss of information caused by standardizing the first-order statistics and mixing data from cells having different nuclear area.

LACK OF ASSOCIATION OF PROSTATE CARCINOMA NUCLEAR GRADING WITH PROSTATE SPECIFIC ANTIGEN RECURRENCE AFTER RADICAL PROSTATECTOMY

Grading prostate cancer using the Gleason system relies only on architectural tumor growth, in contrast to other systems, such as the WHO system, which grade prostate carcinoma based on nuclear features as well as architectural patterns. The prognostic significance of nuclear grading remains controversial since most studies were performed before prostate specific antigen (PSA) screening became widely available. We evaluated the significance of nuclear grade for predicting PSA recurrence in a contemporary cohort of patients treated with radical prostatectomy for clinically localized prostate carcinoma. Nuclear grades 1 to 3 were determined in 141 consecutive radical prostatectomies in 1995. Predominant and worst nuclear grade was determined by a consensus of 3 pathologists. Statistical analysis compared nuclear grade with Gleason score using the chi-square test. The Cox proportional hazards analysis was performed to calculate the ability of nuclear grade, Gleason score and other variables to predict PSA recurrence. We identified a significant association of Gleason score with worst nuclear grade (p = 0.007). All 6 cases with a Gleason score of 8 or greater had a worst nuclear grade of 3, in contrast to 36 of 60 (60%) with a score 6 or less, in which the worst nuclear grade was 3. Of the 141 patients 31 (21.9%) had PSA recurrence at a median followup of 3.7 years. The univariate Cox model revealed significant associations of PSA recurrence with Gleason score 8 or greater (hazards ratio 5.5, p = 0.005), extraprostatic extension (hazards ratio 3.4, p = 0.001), positive surgical margin (hazards ratio 2.6, p = 0.009), seminal vesicle involvement (hazards ratio 7.3, p <0.001), preoperative serum PSA (hazards ratio 1.03, p = 0.007), tumor stage (hazards ratio 3.6, p = 0.001) and maximal tumor dimension (hazards ratio 2.4, p <0.001). However, overall and worst nuclear grade did not predict PSA recurrence (p = 0.89 and 0.13, respectively). Nuclear grade did not fit any multivariate model tested, which otherwise included Gleason score, log(PSA), surgical margin status, extraprostatic extension, seminal vesicle status, tumor size and pathological stage. By varying sample fixation time we also showed that benign prostate tissue in the same section as prostate carcinoma had grade 2 or 3 nuclear changes, that is moderate to marked anaplasia. High nuclear grade is associated with high Gleason score. However, prostate carcinoma with a Gleason score of 6 or less shows extreme variability. Nuclear grade determined by light microscopy failed to predict PSA recurrence in a contemporary series of men with clinically localized prostate cancer treated with radical prostatectomy. Nuclear morphology is subject to tissue fixation and processing artifact. Any nuclear morphometric study must consider this artifact.

Nuclear chromatin texture analysis of nonmalignant tissue can detect adjacent prostatic adenocarcinoma

The aim of this study was to investigate the possibility of identifying prostatic adenocarcinoma by nuclear chromatin texture feature analysis of adjacent histologically benign-looking tissue.Two hundred and forty prostatectomy specimens were selected from the archives of the Department of Pathology, University of Innsbruck. These consisted of 67 cases of benign prostatic hyperplasia (BPH) and 173 cases of prostatic adenocarcinoma (PAC). The specimen collection was divided randomly into a training set and test set. Cytospin preparations of disaggregated cells prepared from paraffin-embedded material were stained specifically for DNA by the Feulgen method. For the cancer cases, only tissue that histologically appeared nonmalignant, from the vicinity of the lesion, was used in the sample preparation. Only normal-appearing diploid cell nuclei were analyzed from both the BPH and PAC groups. A discriminator comprised of three nuclear texture features to separate BPH from PAC cases was derived from the training set of cases, and then applied to the independent test set cases.PAC cases were separated from BPH cases with a sensitivity of 90% and a specificity of 97% on the independent test set of cases.This retrospective investigation demonstrates that by high-resolution image cytometry it is possible to detect the presence of prostatic adenocarcinoma with very high reliability when examining prostate samples that only contain histologically normal-looking cells. This method could become clinically relevant in identification of cancers missed by histologically negative core needle biopsies.

Prognostic Factors in Patients With Metastatic (Stage D2) Prostate Cancer: Experience from the Scandinavian Prostatic Cancer Group Study-2

Purpose Nuclear texture reflects the overall structures of the chromatin organization. We recently reported the principles and prognostic importance of image analysis of nuclei from metastatic prostate cancer. Immunohistochemical up regulation of the adhesion molecule sialyl Lewis x is also reported to be a prognostic parameter. Presently we analyzed statistically the prognostic impact of these 2 new parameters compared to well-known clinical parameters in metastatic prostate cancer. Materials and Methods Prognostic factors, such as sedimentation rate, alkaline and acid phosphatases, hemoglobin, testosterone, performance status, pain due to metastasis, T category, histological grade and patient age, were included in a multivariate Cox proportional hazards regression analysis based on 262 patients from the Scandinavian Prostatic Cancer Group Study-2. Extent of bone lesions, deoxyribonucleic acid ploidy, texture analysis and sialyl Lewis x molecules based on subsets of these 262 patients were also analyzed in the same multivariate model. Results This test identified chromatin texture as the most important factor (p <0.001), followed by reaction of the oligosaccharide sialyl Lewis ( x) (p <0.01). Among the routine clinical and laboratory data, sedimentation rate, alkaline phosphatase and hemoglobin (p <0.05) showed prognostic importance. Performance status, pain due to metastasis and extent of bone lesions showed prognostic value in the univariate analysis (p <0.05). Conclusions These data indicate that computerized nuclear texture analysis as well as up regulation of sialyl Lewis x molecules may be new important prognostic factors in metastatic prostate cancer. Furthermore the prognostic importance of sedimentation rate, alkaline phosphatase and hemoglobin was confirmed.

Nuclear texture analysis: a new prognostic tool in metastatic prostate cancer.

This report describes the prognostic value of computerized nuclear texture analysis in metastatic prostate cancer. Seventy-seven patients with histologically verified prostate carcinomas and skeletal metastases were selected from a Scandinavian multicenter study (SPCG-2). Thirty-six therapy-resistant patients experienced objective progression and cancer-related death within 2 years after orchiectomy. Thirty patients responded well to orchiectomy, i.e., showed objective disease remission and no signs of progression during 3 years of follow-up. From this data set, 10 randomly chosen therapy-resistant and 10 randomly chosen therapy-sensitive carcinomas were used in our previous study to find the optimal combination of features that can discriminate between the two groups (Yogesan et al.: Cytometry 24:268-276, 1996). In addition to these two groups, 11 patients experienced stable disease or disease remission during the first year and a secondary progression during the second or third year of follow-up, with subsequent cancer-related death. Traditional clinical prognostic factors such as histopathological grading and serum markers could not discriminate between these groups of patients. Therefore, image analysis techniques based on texture analysis have been utilized in this study of prognosis of prostate cancer. Feulgen-stained monolayers of nuclei were prepared from paraffin-embedded material taken from the primary tumor before endocrine ablation. Four different textural features were selected from the training data set to calculate the discriminating function. This function separated the therapy-sensitive and the therapy-resistant patients with 87% accuracy in the independent data set. This study demonstrates that it is possible to predict tumor progression and survival for endocrine-ablated metastatic prostate carcinomas using computerized nuclear texture analysis on light microscopy images from prostate biopsies taken at the time of diagnosis.