Follicular nodules (Thy3) of the thyroid: is total thyroidectomy the best option?

BACKGROUND: Identification of the best management strategy for nodules with Thy3 cytology presents particular problems for clinicians. This study investigates the ability of clinical, cytological and sonographic data to predict malignancy in indeterminate nodules with the scope of determining the need for total thyroidectomy in these patients. METHODS: The study population consisted of 249 cases presenting indeterminate nodules (Thy3): 198 females (79.5%) and 51 males (20.5%) with a mean age of 52.43 ± 13.68 years. All patients underwent total thyroidectomy. RESULTS: Malignancy was diagnosed in 87/249 patients (34.9%); thyroiditis co-existed in 119/249 cases (47.79%) and was associated with cancer in 40 cases (40/87; 45.98%). Of the sonographic characteristics, only echogenicity and the presence of irregular margins were identified as being statistically significant predictors of malignancy. 52/162 benign lesions (32.1%) and 54/87 malignant were hypoechoic (62.07%); irregular margins were present in 13/162 benign lesions (8.02%), and in 60/87 malignant lesions (68.97%). None of the clinical or cytological features, on the other hand, including age, gender, nodule size, the presence of microcalcifications or type 3 vascularization, were significantly associated with malignancy. CONCLUSIONS: The rate of malignancy in cytologically indeterminate lesions was high in the present study sample compared to other reported rates, and in a significant number of cases Hashimoto’s thyroiditis was also detected. Thus, considering the fact that clinical and cytological features were found to be inaccurate predictors of malignancy, it is our opinion that surgery should always be recommended. Moreover, total thyroidectomy is advisable, being the most suitable procedure in cases of multiple lesions, hyperplastic nodular goiter, or thyroiditis; the high incidence of malignancy and the unreliability of intraoperative frozen section examination also support this preference for total over hemi-thyroidectomy

KLASIFIKASI MULTI-LABEL MENGGUNAKAN METODE MULTI-LABEL K-NEAREST NEIGHBOR (ML-KNN) PADA PENYAKIT KANKER SERVIKS

Berdasarkan data statistik GLOBOCAN 2020, kanker serviks menempati urutan ke-8 penyakit kanker yang banyak diderita perempuan di seluruh dunia dengan jumlah kasus sebanyak 604.127 kasus dengan angka kematian mencapai 341.831 jiwa. Sedangkan di Indonesia tercatat penderita penyakit kanker serviks berada di urutan ke-2 dengan jumlah kasus sebanyak 36.633 kasus dengan angka kematian mencapai 21.003 jiwa. Multi-Label K-Nearest Neighbor (ML-KNN) merupakan salah satu adaptive algorithm yang dapat digunakan untuk menyelesaikan kasus klasifikasi multi-label. Pada penelitain ini menggunakan dataset yang diperoleh dari website UCI Machine Learning. Pada dataset tersebut akan dilakukan pra-proses data dengan menghapus missing value, mengecek duplicate data, mengecek tipe data, dan melakukan resample data berupa oversampling pada label Biopsy karena data kelas 1 dan 0 yang tidak seimbang. Selanjutnya data dibagi menjadi data latih dan data uji dengan perbandingan 80:20. Pada data latih, dicari kedekatannya dengan nilai k yang sudah ditentukan yaitu K=1, K=3, K=5, K=7, dan K=9. Diperoleh hasil evaluasi performa terbaik yaitu saat nilai K=5 yang memperoleh nilai hamming loss sebesar 3,59%, akurasi sebesar 93%, precision weighted sebesar 93%, recall weighted sebesar 96%, dan f1-score weighted sebesar 94%

THE CLINICAL AND FORENSIC ROLE OF CITOLOGY IN PTA AND PT1 BLADDER CANCER MONITORING. CASE STUDY REVISION FOR THE PERIOD 2008 – 2017.

Introduction: The Authors describe the results of a retrospective study that analyzes importance of a proper bladder cancer monitoring, comparing the use of the different methods available, both in terms of diagnostic delay and in terms of legal medical repercussions. Materials and methods: Using the database of the Pathological Anatomy Department of the Modena Polyclinic, we have isolated a series of 238 patients with histological diagnosis of bladder urothelial carcinoma in pTa and pT1 stages with an observational minimum time interval after first diagnosis of at least 5 years. The observational statistical analysis of the data stored was made through a statistical software (SPSS report 11.00 USA). Results: The results of the present study show how cytological screening, performed constantly with urine tests during early-stage monitoring of bladder tumors, can be a valid tool for the timely diagnosis of tumor stage evolution. Indeed positivity of the cytological examination can direct to a rapid diagnostic and therapeutic re-planning. Conclusion: It would be desirable to standardize the best screening strategies about bladder cancer. With a correct standardization, a valid reference could be obtained both from a clinical point of view, and for a correct legal medical evaluation in term of diagnostic delay and, consequently, reduction in the chance of survival

Cervical Cancer Prediction using NGBFA Feature Selection Algorithm and Hybrid Ensemble Classifier

Cervical Cancer (CC) is a substantial reason of death midst middle-aged women throughout the world, specifically in developing countries, with approximately 85% of deaths. CC patients can be healed if spotted in the early stages. As no symptoms appear in the initial stages, it has become a challenge for investigators to predict the disease in the early stages. Several machine learning algorithms have been used to predict CC since the last decade. Instead of using a single classifier for the prediction, ensemble methods give accurate results, creating and combining multiple models to produce improved results. In this study, we built a hybrid ensemble classifier, 'A Robust Model Stacking: A Hybrid Ensemble,' in which a homogenous ensemble will be performed on a pool of classifiers in the base level followed by a heterogenous ensemble using the majority voting (soft) algorithm to get the final prediction of the new data. The dataset used in this study contains 858 instances with 32 features built from the risk factors and four targets made from the CC diagnosis tests. We have solved the data imbalance problem using an oversampling technique called SMOTE. The model's efficiency was evaluated based on the accuracy, recall, f1-score, precision, and AUC-ROC curve metrics for all four target variables in the dataset. The proposed Biopsy method's accuracy is 98%, Hinselmann is 97%, Schiller is 96.09%, and Citology is 93%. We implement ensemble learning in this study to increase prediction accuracy and decrease bias and variance. We carried the experiments out using the Python language in Google Colab and Jupyter notebooks. The experimental results revealed that our proposed hybrid ensemble learning records a remarkable accuracy for all four target variables

How to Win Cites and Influence People

By now, Fred Shapiro can lay claim to be the founding father of a new and peculiar discipline: legal citology. Citology, the study of citations, should not be confused with cytology, which is the biological study of cells. Legal citology is the systematic study of the citation practices of those professors, research assistants, and law review editors who produce articles in journals widely circulated in the legal academy. Of course other people-judges, politicians, journalists, and even ordinary citizens writing letters to the editor-may occasionally cite law journal articles. Yet, unsurprisingly, academics are most interested in citations by people like themselves, who publish primarily in academic journals. So we\u27re confident that Shapiro\u27s new article will, like its predecessor, be avidly read (and gossiped about) by members of the legal academy. More than a few of us will be eager to discover who ranks where and to speculate, with mixed tones of admiration, envy, and outright rancor, about the justice of whatever kudos are signified by high citation counts

Aplicaciones de la citologia oral por raspado (exfoliativa) en el cáncer y precáncer oral

La citología por raspado es un procedimiento simple e incruento que ha sido objeto de controversia sobre su validez real en patología oral. En los últimos tiempos ha resurgido en base a su aplicación en el precáncer y el cáncer oral, tanto como metodología diagnóstica como predictiva y para la monitorización de los pacientes. Se han desarrollado nuevas técnicas sobre aspectos diagnósticos, como la aplicación 'brush biopsy', y múltiples estudios moleculares sobre las células recogidas. En esta revisión analizamos los aspectos más novedosos en relación con las aplicaciones de la citología por raspado o exfoliativa en la patología oral cancerosa y precancerosa, dirigida de un modo especial a los estudios moleculares y sus implicaciones diagnósticas y pronósticas.Scraped (exfoliative) cytology is a simple and harmless procedure, which has been a controversial technique according to its real validity in oral pathology. Lately it has re-emerged due to its application in oral precancer and cancer as a diagnostic and predictive method as well as for monitoring patients. New diagnostic techniques have been developed, such as 'brush biopsy' and multiple molecular studies using the cells collected. In this review we are going to analyse the more novel aspects related with the applications of the scraped or exfoliative cytology in oral precancerous and cancerous pathology, specially focusing on molecular studies and their diagnostic and prognostic implications

A case of primary Hodgkin's lymphoma of the parotid gland. Case report and differentian diagnosis from Kuttner's Syndrom

Abstract We report a rare case of primary Hodgkin’s lymphoma (HL) of the submandibular gland, with initially diagnosis of Kuttner’s Syndrom. A 48 years old man was referred to our hospital foe evaluation of a submandibular mass. Although the initial Fine Needle Aspiration and subsequent cytology was highly suggestive for a cronic sialadenitis with lymphoid cells. After surgical gland removal we obtained a definitive diagnosis of Hodgkin’s lymphoma in submandibular gland a seat where the most common lymphoma tipe is B