Fractal Analysis of Cervical Intraepithelial Neoplasia (original) (raw)
Related papers
Journal of Biosciences and Medicines, 2018
Background: The concomitant use of fractal and Euclidian measurements has led to the development of new methodologies of cell evaluation, including a diagnosis of cervical cells that set up differences between normality and various degrees of lesion, to carcinoma. Aim: To confirm the diagnostic capacity of the methodology based on fractal and Euclidian geometry for the mathematical diagnosis through a blind study of normal cells and with different types of lesion, as atypia of undetermined significance (ASCUS), low grade squamous intra-epithelial lesion (LGSIL) and high grade squamous intra-epithelial lesion (HGSIL). Methods: 100 cells of Papanicolaou tests were analyzed and divided into 4 groups according to conventional parameters: 25 normal, 25 ASCUS, 25 LGSIL and 25 HGSIL. By means of the Box-counting Fractal Space, we calculated the fractal dimension and occupying spaces of the border and surface in pixels of the cell nucleus and cytoplasm. The diagnostic parameters of the previously developed methodology were applied and compared with the conventional diagnosis, setting up sensibility, specificity, negative likelihood ratio and Kappa coefficient. Results: The values of the occupation of the border and surface of the cell nucleus and cytoplasm were consistent with the values found by the diagnostic methodology previously found. The subtraction of the nucleus and cytoplasm frontiers presented values between: 189 and 482 for normality; 159
Fractal and Euclidean Geometrical Diagnosis of Cervix Cytology
Journal of Cancer Science & Therapy, 2014
Background: Conventional methods for evaluation of cervix cytology show reproducibility problems. To solve this, there was developed a diagnostic methodology based on fractal and euclidean geometry, mathematically differentiating normality, L SIL and H SIL. Objective: The aim of the present work is to confirm the clinical applicability of such diagnostic in a blind study. Methods: The clinic diagnosis of 15 normal cells, 15 ASCUS, 15 L SIL and 15 H SIL was masked. Cellular nucleus and cytoplasm were evaluated calculating fractal dimension, number of spaces occupied by the frontier and number of pixels occupied by the surface of each object. The mathematical diagnosis was established and compared with the conventional diagnosis, calculating specificity, sensibility, negative likelihood ratio and Kappa coefficient. Results: It was found that simultaneous measures of the nuclear surface and the subtraction between the frontiers of cytoplasm and nucleus, lead to differentiate normality, L SIL and H SIL. Both sensibility and specificity values were of 100 percent. Kappa coefficient was 1 and negative likelihood ratio was zero. 4 ASCUS showed mathematical measures of normality, while the remaining 11 showed values of L-SIL cells. Conclusion: The mathematical diagnostic prove to be useful for clinical evaluation of cervix cytology, differentiating normality, L SIL and H SIL, quantifying how close it is the cell to a higher severity stage, and clearing up the undetermination of the ASCUS cells.
BMC Medical Physics, 2014
Background: Fractal geometry has been the basis for the development of a diagnosis of preneoplastic and neoplastic cells that clears up the undetermination of the atypical squamous cells of undetermined significance (ASCUS). Methods: Pictures of 40 cervix cytology samples diagnosed with conventional parameters were taken. A blind study was developed in which the clinic diagnosis of 10 normal cells, 10 ASCUS, 10 L-SIL and 10 H-SIL was masked. Cellular nucleus and cytoplasm were evaluated in the generalized Box-Counting space, calculating the fractal dimension and number of spaces occupied by the frontier of each object. Further, number of pixels occupied by surface of each object was calculated. Later, the mathematical features of the measures were studied to establish differences or equalities useful for diagnostic application. Finally, the sensibility, specificity, negative likelihood ratio and diagnostic concordance with Kappa coefficient were calculated. Results: Simultaneous measures of the nuclear surface and the subtraction between the boundaries of cytoplasm and nucleus, lead to differentiate normality, L-SIL and H-SIL. Normality shows values less than or equal to 735 in nucleus surface and values greater or equal to 161 in cytoplasm-nucleus subtraction. L-SIL cells exhibit a nucleus surface with values greater than or equal to 972 and a subtraction between nucleus-cytoplasm higher to 130. L-SIL cells show cytoplasm-nucleus values less than 120. The rank between 120-130 in cytoplasm-nucleus subtraction corresponds to evolution between L-SIL and H-SIL. Sensibility and specificity values were 100%, the negative likelihood ratio was zero and Kappa coefficient was equal to 1. Conclusions: A new diagnostic methodology of clinic applicability was developed based on fractal and euclidean geometry, which is useful for evaluation of cervix cytology.
Gynecologic Oncology, 1999
Objectives. Fractal geometry is a tool used to characterize irregularly shaped and complex figures. It can be used not only to generate biological structures (e.g., the human renal artery tree), but also to derive parameters such as the fractal dimension in order to quantify the shapes of structures. As such, it allows user-independent evaluation and does not rely on the experience level of the examiner. Methods. We applied a box-counting algorithm to determine the fractal dimension of atypical nuclei in dysplastic cervical epithelium. An automatic algorithm was used to determine the fractal dimension of nuclei in order to prevent errors from manual segmentation. Four groups of patients (CIN 1-3 and control) with 10 subjects each were examined. In total, the fractal dimensions of 1200 nuclei were calculated. Results. We found that the fractal dimensions of the nuclei increased as the degree of dysplasia increased. There were significant differences between control and atypical nuclei found by an analysis of variance. Atypical nuclei associated with CIN 1, CIN 2, and CIN 3 also differed significantly among these groups. Conclusion. We conclude that the fractal dimension is a valuable tool for detecting irregularities in atypical nuclei of the cervix uteri and thus allows objective nuclear grading.
Fractal dimension and image statistics of anal intraepithelial neoplasia
Chaos, Solitons & Fractals, 2011
It is well known that human papillomaviruses (HPV) induce a variety of tumorous lesions of the skin. HPV-subtypes also cause premalignant lesions which are termed anal intraepithelial neoplasia (AIN). The clinical classification of AIN is of growing interest in clinical practice, due to increasing HPV infection rates throughout human population. The common classification approach is based on subjective inspections of histological slices of anal tissues with all the drawbacks of depending on the status and individual variances of the trained pathologists.
The aplication of the fractal analysis in oncopathology
Medicus
Fractal analysis is an objective approach that in oncopathology is one of the important fields of application. In this study is present fractal methodologies at histological level that have been successfully applied to characterize pathological features and able to perform differential diagnosis and prognosis in oncopathology. The basic principles and prospects of fractal geometry in pathology are promising. In particular, fractal analysis is emerging as a powerful tool to perform differential diagnosis and prognosis of the patients in cancer and other malignancies as well to improve the effectiveness and safety of patient care. All fractal objects have Fractal Dimension FDs, commonly calculated with box counting. Morphometry, the measure of shapes of the structures, can be added to every imaging technique in order to obtain objective indexes. In this field, fractal analysis has been applied to histopathology, cytopathology, and electron microscopy with great success. Performing fra...
Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
Applied Radiation and Isotopes, 2019
Tumor growth in the cervix is a complex process. Understanding this phenomena is quite relevant in order to establish proper diagnosis and therapy strategies and a possible startpoint is to evaluate its complexity through the scaling analysis, which define the tumor growth geometry. In this work, tumor interface from primary tumors of squamous cells and adenocarcinomas for cervical cancer were extracted. Fractal dimension and local roughness exponent (Barabási and Stanley (1996)), α loc , were calculated to characterize the in vivo 3-D tumor growth. Image acquisition was carried out according to the standard protocol used for cervical cancer radiotherapy, i.e., axial, magnetic resonance T1-weighted contrast enhanced images comprising the cervix volume for image registration. Image processing was carried out by a classification scheme based on quantum clustering algorithm (Mussa, Mitchell and Afzal (2015)) combined with the application of the K-means procedure upon contrasted images (Demirkaya, Asyali, and Sahoo (2008)). The results show significant variations of the parameters depending on the tumor stage and its histological origin.
Fractal Study on Nuclear Boundary of Cancer Cells in Urinary Smears
2011
Background & Objectives: Cancer is a serious problem for human being and is becoming a serious problem day-by-day .A prerequisite for any therapeutic modality is early diagnosis. Automated cancer diagnosis by automatic image feature extraction procedures can be used as a feature extraction in the field of fractal dimension. The aim of this survey was to introduce a quantitative and objective mathematical method for pinpointing the differences between malignant and non-malignant epithelial cells in urine cytology by the use of software analysis. Materials & Methods: Forty-one positive urine cytology and 33 negative subjects from Pathology Department of Imam Khomeini Hospital, Urmia, Iran (2003-2007) were selected at random. Digitalized images were prepared by the use of objective 100X (a digital video head) which subsequently were processed by the Beonit TM software version 1.3 (Tru Soft International inc. USA) to measure fractal dimension of nuclear boundaries. Results: Findings revealed statistically significant differences between fractal dimensions of nuclear boundaries of cancerous and non-cancerous smears (P=0.001). Study had selected a cutoff point to (1.732 ± 0.006) to discriminate malignant and non-malignant epithelial cells in urinary smears. Conclusion: Based on diagnostic accuracy measures (sensitivity and specificity), probability of disease measures (predictive value of a positive and negative test results), and likelihood ratio of positive and negative tests, it seems fractal dimension of nuclear cell boundaries for urinary smears can be used as a feature extraction in the field of automated cancer diagnosis.