Fine needle aspiration cytology of epididymal nodules and its corroboration with ultrasonographic‐histological findings

Mondal, Krishnendu; Mandal, Rajesh Kumar; Saha, A.; Shahabuddin,; Sarkar, R.

doi:10.1002/dc.24336

Cited by 5 publications

(2 citation statements)

References 21 publications

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“…In such cases of genital tuberculosis with isolated epididymo-testicular lesions and high suspicion of malignancy, diagnosis is generally made on histopathology after inguinal exploration, FNAC being contraindicated [13,39]. Nonetheless, when there is low suspicion of testicular tumor, in comparison to open surgical surgery, FNAC showed a higher sensitivity (87%) and specificity (93%) [40]. Furthermore, it has displaced investigations leading to unnecessary epididymectomy or orchiectomy in some cases [12,41].…”

Section: Histological/cytological Examinationmentioning

confidence: 99%

Why do we miss isolated male genital tuberculosis diagnosis?

Retal

Kharbach²,

Khallouk³

2022

infez med

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cause confusion as the infection does not always occur simultaneously. There are currently quite a lot of difficulties that clinicians encounter when facing a possible case of isolated MGTB because of its varied presentations and unavailability of sensitive and specific investigations. Thus, TB of male genital tract still presents a diagnostic dilemma. The aim of this review is to highlight the pathophysiology, clinical features, diagnostic challenges of tuberculosis affecting only the male genital tract and to improve awareness of MGTB in the differential diagnosis. This review also shows the variability and nonexistence of uniform consensus for this presentation. n MATERIALS AND METHODSAn electronic search was carried out at PubMed, MEDLINE, Scopus, Embase, and Google scholar to realize this narrative review. The search was

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Section: Histological/cytological Examinationmentioning

confidence: 99%

Why do we miss isolated male genital tuberculosis diagnosis?

Retal

Kharbach²,

Khallouk³

2022

infez med

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“…Therefore, CT has become an indispensable imaging method for patients with testicular masses. In addition, testicular biopsy is used in few centers and has not gained widespread acceptance because of narrow indication and possible increased local recurrence rate, with which it is difficult to assess intratumoral heterogeneity for its limitation ( 7 , 11 ). In recent years, CT texture analysis (CTTA) has become a promising technique for evaluating tumor heterogeneity in a quantitative manner.…”

Section: Introductionmentioning

confidence: 99%

Machine learning-based CT texture analysis in the differentiation of testicular masses

Hu,

Qiao,

et al. 2024

Front. Oncol.

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PurposeTo evaluate the ability of texture features for distinguishing between benign and malignant testicular masses, and furthermore, for identifying primary testicular lymphoma in malignant tumors and identifying seminoma in testicular germ cell tumors, respectively.MethodsWe retrospectively collected 77 patients with an abdominal and pelvic enhanced computed tomography (CT) examination and a histopathologically confirmed testicular mass from a single center. The ROI of each mass was split into two parts by the largest cross-sectional slice and deemed to be two samples. After all processing steps, three-dimensional texture features were extracted from unenhanced and contrast-enhanced CT images. Excellent reproducibility of texture features was defined as intra-class correlation coefficient ≥0.8 (ICC ≥0.8). All the groups were balanced via the synthetic minority over-sampling technique (SMOTE) method. Dimension reduction was based on pearson correlation coefficient (PCC). Before model building, minimum-redundancy maximum-relevance (mRMR) selection and recursive feature elimination (RFE) were used for further feature selection. At last, three ML classifiers with the highest cross validation with 5-fold were selected: autoencoder (AE), support vector machine(SVM), linear discriminant analysis (LAD). Logistics regression (LR) and LR-LASSO were also constructed to compare with the ML classifiers.Results985 texture features with ICC ≥0.8 were extracted for further feature selection process. With the highest AUC of 0.946 (P <0.01), logistics regression was proved to be the best model for the identification of benign or malignant testicular masses. Besides, LR also had the best performance in identifying primary testicular lymphoma in malignant testicular tumors and in identifying seminoma in testicular germ cell tumors, with the AUC of 0.982 (P <0.01) and 0.928 (P <0.01), respectively.ConclusionUntil now, this is the first study that applied CT texture analysis (CTTA) to assess the heterogeneity of testicular tumors. LR model based on CTTA might be a promising non-invasive tool for the diagnosis and differentiation of testicular masses. The accurate diagnosis of testicular masses would assist urologists in correct preoperative and perioperative decision making.

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Fine Needle Aspiration Cytology of the Gonads

Dey

2020

Color Atlas of Fine Needle Aspiration Cytology

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Fine needle aspiration cytology of epididymal nodules and its corroboration with ultrasonographic‐histological findings

Cited by 5 publications

References 21 publications

Why do we miss isolated male genital tuberculosis diagnosis?

Why do we miss isolated male genital tuberculosis diagnosis?

Machine learning-based CT texture analysis in the differentiation of testicular masses

Fine Needle Aspiration Cytology of the Gonads

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