Nuclear morphometric features in benign breast tissue and risk of subsequent breast cancer

Morphometric study in thyroid tumors

Various morphonuclear studies using digital image analysis have been taken into account in order to establish the malignancy of thyroid lesions based on their size and on the chromatographic characteristics of tumor cell nuclei. Nuclear morphometry involves the measurement of nuclear parameters to obtain diagnostically important information in an objective and reproducible manner. The aim of the present study was to evaluate the detailed morphometric analysis of histopathological preparations with lesions of the thyroid gland and to investigate its role in differentiating between benign and malignant thyroid lesions. The present study included 10 benign and 26 malignant thyroid cases with different selected thyroid lesions. Using a microscope connected to a computerized video system, nuclear morphometric parameters including the nuclear area, perimeter, average intensity, red average, width and roundness, were measured and analyzed. The main parameters used in the statistical calculation were significant in distinguishing between benign and malignant thyroid lesions. The association of morphometry in cytological smears for suspected malignant follicular lesions led to increased accuracy in establishing a suspicious malignant diagnosis for follicular lesions. Nuclear morphometry provides an unbiased point of view that increases diagnosis accuracy. Computerized morphometry can positively influence diagnostic accuracy, allowing for a better correlation with clinical and imaging data.

Nuclear Morphological Characteristics in Breast Cancer: Correlation with Hormone Receptor and Human Epidermal Growth Factor Receptor 2

Background

Hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) are the common diagnostic/prognostic markers in breast cancer. Few articles have recently reported the correlation between cytology and molecular subtypes. We combined nuclear morphological characteristics with HR and HER2 status to observe the relationship and provide ideas for machine learning.

Methods

We reanalyzed fine-needle aspiration cytology samples and core-needle puncture histological specimens from 142 patients with invasive breast cancer between March 2019 and December 2019, and the findings were compared with the two groups (HR+/HER2- and HR-/HER2+) following nuclear cytomorphological features: nuclear/cytoplasmic ratio, difference of nuclear size, nuclear pleomorphism, chromatin feature, nuclear membrane and nucleoli, and Nottingham grading.

Results

Two groups were significantly associated with the difference of nuclear size, nuclear pleomorphism, and nucleoli (P < 0.001) and consistent with histological grading (P < 0.001). Moreover, nucleolar characteristics of size and number had obviously statistical significance (P < 0.001). Multiple micro-nucleoli were frequently seen in the HR+/HER2- group compared with the HR-/HER2+ group which mostly were observed centered medium-large nucleoli. We described four interesting nuclear morphologies in the experiment.

Conclusions

There were significant differences in nuclear characteristics between two groups. HR and HER2 status not only might be predicted in cytological samples, but some specific nuclear morphological features might have potential value to help us understand molecular function and predict more information.

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.

Cytological Evaluation of Thyroid Lesions by Nuclear Morphology and Nuclear Morphometry

Introduction:

Fine needle aspiration (FNA) of the thyroid gland is an effective diagnostic method. The Bethesda system for reporting thyroid cytopathology classifies them into six categories and gives implied risk for malignancy and management protocol in each category. Though the system gives specific criteria, diagnostic dilemma still exists. Using nuclear morphometry, we can quantify the number of parameters, such as those related to nuclear size and shape. The evaluation of nuclear morphometry is not well established in thyroid cytology.

Objective:

To classify thyroid lesions on fine needle aspiration cytology (FNAC) using Bethesda system and to evaluate the significance of nuclear parameters in improving the prediction of thyroid malignancy.

Materials and Methods:

In the present study, 120 FNAC cases of thyroid lesions with histological diagnosis were included. Computerized nuclear morphometry was done on 81 cases which had confirmed cytohistological correlation, using Aperio computer software. One hundred nuclei from each case were outlined and eight nuclear parameters were analyzed.

Results:

In the present study, thyroid lesions were common in female with M: F ratio of 1:5 and most commonly in 40–60 yrs. Under Bethesda system, 73 (60.83%) were category II; 14 (11.6%) were category III, 3 (2.5%) were category IV, 8 (6.6%) were category V, and 22 (18.3%) were category VI, which were malignant on histopathological correlation. Sensitivity, specificity, and diagnostic accuracy of Bethesda reporting system are 62.5, 84.38, and 74.16%, respectively. Minimal nuclear diameter, maximal nuclear diameter, nuclear perimeter, and nuclear area were higher in malignant group compared to nonneoplastic and benign group.

Conclusion:

The Bethesda system is a useful standardized system of reporting thyroid cytopathology. It gives implied risk of malignancy. Nuclear morphometry by computerized image analysis can be utilized as an additional diagnostic tool.

Morphometric Analysis of Thyroid Follicular Cells with Atypia of Undetermined Significance

BACKGROUND

Atypia of undetermined significance (AUS) is a category that encompasses a heterogeneous group of thyroid aspiration cytology. It has been reclassified into two subgroups based on the cytomorphologic features: AUS with cytologic atypia and AUS with architectural atypia. The nuclear characteristics of AUS with cytologic atypia need to be clarified by comparing to those observed in Hashimoto thyroiditis and benign follicular lesions.

METHODS

We selected 84 cases of AUS with histologic follow-up, 24 cases of Hashimoto thyroiditis, and 26 cases of benign follicular lesions. We also subcategorized the AUS group according to the follow-up biopsy results into a papillary carcinoma group and a nodular hyperplasia group. The differences in morphometric parameters, including the nuclear areas and perimeters, were compared between these groups.

RESULTS

The AUS group had significantly smaller nuclear areas than the Hashimoto thyroiditis group, but the nuclear perimeters were not statistically different. The AUS group also had significantly smaller nuclear areas than the benign follicular lesion group; however, the AUS group had significantly longer nuclear perimeters. The nuclear areas in the papillary carcinoma group were significantly smaller than those in the nodular hyperplasia group; however, the nuclear perimeters were not statistically different.

CONCLUSIONS

We found the AUS group to be a heterogeneous entity, including histologic follow-up diagnoses of papillary carcinoma and nodular hyperplasia. The AUS group showed significantly greater nuclear irregularities than the other two groups. Utilizing these features, nuclear morphometry could lead to improvements in the accuracy of the subjective diagnoses made with thyroid aspiration cytology.

Evaluation of Pre-Malignant and Malignant Lesions in Cervico Vaginal (PAP) Smears by Nuclear Morphometry

BACKGROUND

Cervical cancer is the second most common cancer occurring among women worldwide, with almost half a million new cases each year. Normal cells gradually transform to form cancer cells through several stages. So, the changes occurring during the transformational stages need to be assessed.

AIM

Our aim was to study various nuclear parameters useful in evaluating pre-malignant and malignant cervico-vaginal pap smears.

MATERIALS AND METHODS

Bethesda System was used to categorize cervical pap smears into premalignant and malignant lesions. Nuclear parameters were calculated using J 1.44C morphometric software. Several nuclear size parameters were analysed.

RESULTS

The nuclear area, perimeter, diameter were found to be statistically significant (p<0.05) parameters in differentiating premalignant from malignant cervical smears.

CONCLUSION

Nuclear morphometry was thus a useful objective tool in differentiating premalignant from malignant cervical smears.

Computational pathology to discriminate benign from malignant intraductal proliferations of the breast

The categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools to aid pathologists in the characterization of these lesions would have great diagnostic and clinical value. As a first step to address this issue, we evaluated the ability of computational image analysis to accurately classify DCIS and UDH and to stratify nuclear grade within DCIS. Using 116 breast biopsies diagnosed as DCIS or UDH from the Massachusetts General Hospital (MGH), we developed a computational method to extract 392 features corresponding to the mean and standard deviation in nuclear size and shape, intensity, and texture across 8 color channels. We used L1-regularized logistic regression to build classification models to discriminate DCIS from UDH. The top-performing model contained 22 active features and achieved an AUC of 0.95 in cross-validation on the MGH data-set. We applied this model to an external validation set of 51 breast biopsies diagnosed as DCIS or UDH from the Beth Israel Deaconess Medical Center, and the model achieved an AUC of 0.86. The top-performing model contained active features from all color-spaces and from the three classes of features (morphology, intensity, and texture), suggesting the value of each for prediction. We built models to stratify grade within DCIS and obtained strong performance for stratifying low nuclear grade vs. high nuclear grade DCIS (AUC = 0.98 in cross-validation) with only moderate performance for discriminating low nuclear grade vs. intermediate nuclear grade and intermediate nuclear grade vs. high nuclear grade DCIS (AUC = 0.83 and 0.69, respectively). These data show that computational pathology models can robustly discriminate benign from malignant intraductal proliferative lesions of the breast and may aid pathologists in the diagnosis and classification of these lesions.

Altered nuclear structure in myotonic dystrophy type 1-derived fibroblasts

Myotonic dystrophy type 1 (DM1) is a multisystem genetic disorder caused by a triplet nucleotide repeat expansion in the 3' untranslated region of the Dystrophia Myotonica-Protein Kinase (DMPK) gene. DMPK gene transcripts containing CUG expanded repeats accumulate in nuclear foci and ultimately cause altered splicing/gene expression of numerous secondary genes. The study of primary cell cultures derived from patients with DM1 has allowed the identification and further characterization of molecular mechanisms underlying the pathology in the natural context of the disease. In this study we show for the first time impaired nuclear structure in fibroblasts of DM1 patients. DM1-derived fibroblasts exhibited altered localization of the nuclear envelope (NE) proteins emerin and lamins A/C and B1 with concomitant increased size and altered shape of nuclei. Abnormal NE organization is more common in DM1 fibroblasts containing abundant nuclear foci, implying expression of the expanded RNA as determinant of nuclear defects. That transient expression of the DMPK 3' UTR containing 960 CTG but not with the 3' UTR lacking CTG repeats is sufficient to generate NE disruption in normal fibroblasts confirms the direct impact of mutant RNA on NE architecture. We also evidence nucleoli distortion in DM1 fibroblasts by immunostaining of the nucleolar protein fibrillarin, implying a broader effect of the mutant RNA on nuclear structure. In summary, these findings reveal that NE disruption, a hallmark of laminopathy disorders, is a novel characteristic of DM1.

Do lamins influence disease progression in cancer?

For nearly 60 years, diagnosis of cancer has been based on pathological tests that look for enlargement and distortion of nuclear shape. Because of their involvement in supporting nuclear architecture, it has been postulated that the basis for nuclear shape changes during cancer progression is altered expression of nuclear lamins and in particular lamins A and C. However, studies on lamin expression patterns in a range of different cancers have generated equivocal and apparently contradictory results. This might have been anticipated since cancers are diverse and complex diseases. Moreover, whilst altered epigenetic control over gene expression is a feature of many cancers, this level of control cannot be considered in isolation. Here I have reviewed those studies relating to altered expression of lamins in cancers and argue that consideration of changes in the expression of individual lamins cannot be considered in isolation but only in the context of an understanding of their functions in transformed cells.

Needle-based fluorescence endomicroscopy via structured illumination with a plastic, achromatic objective

In order to diagnose cancer, a sample must be removed, prepared, and examined under a microscope, which is expensive, invasive, and time consuming. Fiber optic fluorescence endomicroscopy, where an image guide is used to obtain high-resolution images of tissue in vivo, has shown promise as an alternative to conventional biopsies. However, the resolution of standard endomicroscopy is limited by the fiber bundle sampling frequency and out-of-focus light. A system is presented which incorporates a plastic, achromatic objective to increase the sampling and which provides optical sectioning via structured illumination to reject background light. An image is relayed from the sample by a fiber bundle with the custom 2.1-mm outer diameter objective lens integrated to the distal tip. The objective is corrected for the excitation and the emission wavelengths of proflavine (452 and 515 nm). It magnifies the object onto the fiber bundle to improve the system's lateral resolution by increasing the sampling. The plastic lenses were fabricated via single-point diamond turning and assembled using a zero alignment technique. Ex vivo images of normal and neoplastic murine mammary tissues stained with proflavine are captured. The system achieves higher contrast and resolves smaller features than standard fluorescence endomicroscopy.

Significance of nuclear morphometry in benign and malignant breast aspirates

Background:

Breast carcinoma is one of the most common cancers occurring in the female population world-wide. Normal cells gradually transform to form the cancer cells through several stages. Nuclear changes occurring during these transformational steps need to be assessed objectively. Hence nuclear morphometry can be used as a diagnostic tool.

Aim:

To compare the nuclear morphometric parameters of benign and malignant breast aspirates.

Study Design:

Cytology was used to categorize aspirates from the breast lumps in to malignant (30 cases), and benign (30 cases). Nuclear parameters were calculated using the Image J 1.44C morphometric software. Several nuclear size parameters were analyzed.

Results:

The nuclear area, perimeter, diameter, compactness, and concave points were found to be statistically significant (P < 0.05) parameters in differentiating benign, and malignant aspirates.

Conclusion:

Nuclear morphometry was thus, a useful objective tool in the differentiating benign, and malignant breast lesions.

Achromatized endomicroscope objective for optical biopsy

Currently, researchers and clinicians lack achromatized endomicroscope objectives that are as narrow as biopsy needles. We present a proof-of-concept prototype that validates the optical design of an NA0.4 objective. The objective, built with plastic lenses, has a 0.9 mm clear aperture and is achromatized from 452 nm to 623 nm. The objective's measured Strehl ratio is 0.74 ± 0.05 across a 250 μm FOV. We perform optical sectioning via structured illumination through the objective while capturing fluorescence images of breast carcinoma cells stained with proflavine and cresyl violet. This technology has the potential to improve optical biopsies and provide the next step forward in cancer diagnostics.

Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer

Numerous studies have shown the prognostic significance of nuclear morphometry in breast cancer patients. Wide acceptance of morphometric methods has, however, been hampered by the tedious and time consuming nature of the manual segmentation of nuclei and the lack of equipment for high throughput digitization of slides. Recently, whole slide imaging became more affordable and widely available, making fully digital pathology archives feasible. In this study, we employ an automatic nuclei segmentation algorithm to extract nuclear morphometry features related to size and we analyze their prognostic value in male breast cancer. The study population comprised 101 male breast cancer patients for whom survival data was available (median follow-up of 5.7 years). Automatic segmentation was performed on digitized tissue microarray slides, and for each patient, the mean nuclear area and the standard deviation of the nuclear area were calculated. In univariate survival analysis, a significant difference was found between patients with low and high mean nuclear area (P=0.022), while nuclear atypia score did not provide prognostic value. In Cox regression, mean nuclear area had independent additional prognostic value (P=0.032) to tumor size and tubule formation. In conclusion, we present an automatic method for nuclear morphometry and its application in male breast cancer prognosis. The automatically extracted mean nuclear area proved to be a significant prognostic indicator. With the increasing availability of slide scanning equipment in pathology labs, these kinds of quantitative approaches can be easily integrated in the workflow of routine pathology practice.

Isotropic 3D nuclear morphometry of normal, fibrocystic and malignant breast epithelial cells reveals new structural alterations

Background

Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.

Methodology

We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.

Principal Findings

We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.

Conclusions

Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.

Computerized nuclear morphometry in the diagnosis of thyroid lesions with predominant follicular pattern

Background:

Differential diagnosis of thyroid lesions with predominantly follicular pattern is one of the most common problems in thyroid pathology. Development of more objective and reproducible tools for diagnosis is needed. This work is aimed at studying the role of nuclear morphometry in differential diagnosis of different thyroid lesions having predominant follicular pattern.

Material and methods:

Semiautomatic image analysis system was used to measure a total of 8 nuclear parameters in 48 thyroid lesions including seven nodular goiter (NG), 14 follicular adenoma (FA), 14 follicular carcinoma (FC) and 13 follicular variant papillary carcinoma (FVPC).

Results:

The parameters related to nuclear size (area, perimeter, MaxD, MinD, nuclear size) and shape (L/S ratio, Form_AR) were significantly higher in neoplastic group (FA, FC, FVPC) when compared to non-neoplastic group (NG) P<0.05. The perimeter was the most reliable parameter (area under the cure (AUC)=97%) followed by area, MaxD, and size (all have AUC= 96%) then form-AR (90%), LS ratio (86%) and the least reliable was Min D (79%). Within the neoplastic group, most parameters related to size and shape of the nuclei was significantly higher in FVPC than in FA and FC (p ≤ 0.05). Nuclear area and size (AUC 77%) were the most reliable parameters for differentiation between FVPC and FA. The best cut off values for diagnosing FVPC are nuclear area ≥39.9μm² and nuclear size ≥27.7μm². However, there was no quantitative difference between FC and FA.

Conclusion:

Nuclear morphometric parameters may help in the differentiation between neoplastic and non-neoplastic thyroid lesions and between FVPC and follicular neoplasms (FC and FA) but they have no value in the differentiation between FC and FA.