The Role of Ultrasound Guided Sampling Procedures in the Diagnosis of Pelvic Masses: A Narrative Review of the Literature

Tru-Cut Biopsy in Gynecological Cancer: Adequacy, Accuracy, Safety and Clinical Applicability

Purpose

Tru-cut biopsy is a minimally invasive technique used to obtain tissue samples for the diagnosis of tumors, especially in patients where primary surgery is not indicated. The aim of this study was to assess the adequacy, accuracy and safety of the tru-cut biopsy for diagnosis in gynecological cancer.

Methods

A retrospective population-based review of 328 biopsies was conducted. The indications for tru-cut biopsies were diagnosis of primary tumors, metastases of gynecological and non-gynecological tumors, and suspected recurrences. A tissue sample was considered adequate when the quality/quality was sufficient to identify the subtype/origin of the tumor. Potential factors affecting adequacy were analyzed using logistic regressions analyses. Accuracy was defined as agreement between the diagnosis of the tru-cut biopsy and the postoperative histology. The therapy plan was registered, and the clinical applicability of the tru-cut biopsy was investigated. Complications within 30 days after the biopsy procedure were registered.

Results

In total, 300 biopsies were identified as tru-cut biopsies. The overall adequacy was 86.3%, varying between 80.8% and 93.5%, respectively, when performed by a gynecological oncologist or a gynecologist with a subspecialty in ultrasound diagnosis. Sampling of a pelvic mass had a lower adequacy (81.6%) compared with sampling of the omentum (93.9%) or carcinomatosis (91.5%). The accuracy was 97.5%, and the complication rate was 1.3%.

Conclusion

The tru-cut biopsy is a safe and reliable diagnostic method with a high accuracy and a good adequacy, depending on the site of the tissue sample, indications for the biopsy and the experience of the operator.

Contribution of Outpatient Ultrasound Transvaginal Biopsy and Puncture in the Diagnosis and Treatment of Pelvic Lesions: A Bicenter Study

BACKGROUND

The use of transvaginal ultrasound guided biopsy and puncture of pelvic lesions is a minimally invasive technique that allows for accurate diagnosis. It has many advantages compared to other more invasive (lower complication rate) or non-invasive techniques (accurate diagnosis). Furthermore, it offers greater availability, it does not radiate, enables the study of pelvic masses accessible vaginally with ultrasound control in real time, and it is possible to use the colour Doppler avoiding puncturing large vessels among others. The main aim of the work is to describe a standardized ambulatory technique and to determine its usefulness.

METHODS

This is a retrospective study of ultrasound transvaginal punctures (core needle biopsies and cytologies) and drainages of pelvic lesions performed on an outpatient basis during the last two years. The punctures were made with local anesthesia, under transvaginal ultrasound guidance with an automatic or semi-automatic 18G biopsy needle with a length of 20-25 cm and a penetration depth of 12 or 22 mm. The material obtained was sent for anatomopathological, cytological and/or microbiological study if necessary.

RESULTS

A total of 42 women were recruited in two centers. Fifty procedures (nine punctures, seven drains, and 34 biopsies) were performed. In five cases the punction and drain provided clinical relief in benign pelvic masses. Regarding material of the biopsies performed, 15 were vaginal in women previously histerectomized, finding 10 carcinomas, eight were ovarian tumours in advanced stages or peritoneal carcinomatosis obtaining the appropriate histology in each case, seven were suspicious cervical biopsies finding carcinomas in five of them, three were myometrial biopsies including one breast carcinoma metastasis in the miometrium and a benign placental nodule, and a periurethral biopsy was performed on a woman with a history of endometrial cancer confirming recurrence. The pathological diagnosis was satisfactory in all cases, confirming the nature of the lesion (25 malignant-ten vaginal recurrences of previous gynaecological cancers, eight cases of primary ovarian/peritoneal carcinoma, four new diagnosis of cervical malignant masses, one cervical metastasis of lymphoma, one periurethral recurrence of endometrial carcinoma and one recurrence of breast cancer in the myometrium-and 23 benign). The tolerance was excellent and no complications were detected.

CONCLUSION

The ambulatory ultrasound transvaginal puncture and drainage technique is useful for obtaining a sample for pathological and microbiological diagnosis with excellent tolerance that can be used to rule out the recurrence of malignant lesions or progression of the disease, diagnose masses not accessible to gynecological exploration (vaginal vault, myometrium or cervix) and for early histologic diagnosis in cases of advanced peritoneal carcinomatosis or ovarian carcinoma as well as drainage and cytological study of cystic pelvic masses.

Primary retroperitoneal nodal endometrioid carcinoma associated with Lynch syndrome: A case report

We report a rare case of primary nodal, poorly differentiated endometrioid carcinoma associated with Lynch syndrome. A 29-year-old female patient was referred by her general gynecologist for further imaging with suspected right-sided ovarian endometrioid cyst. Ultrasound examination by an expert gynecological sonographer at tertiary center revealed unremarkable findings in the abdomen and pelvis apart from three iliac lymph nodes showing signs of malignant infiltration in the right obturator fossa and two lesions in the 4b segment of the liver. During the same appointment ultrasound guided tru-cut biopsy was performed to differentiate hematological malignancy from carcinomatous lymph node infiltration. Based on the histological findings of endometrioid carcinoma from lymph node biopsy, primary debulking surgery including hysterectomy and salpingo-oophorectomy was performed. Endometrioid carcinoma was confirmed only in the three lymph nodes suspected on the expert scan and primary nodal origin of endometroid carcinoma developed from ectopic Müllerian tissue was considered. As a part of the pathological examination immunohistochemistry analysis for mismatch repair protein (MMR) expression was done. The findings of deficient mismatch repair proteins (dMMR) led to additional genetic testing, which revealed deletion of the entire EPCAM gene up to exon 1-8 of the MSH2 gene. This was unexpected considering her insignificant family history of cancer. We discuss the diagnostic work-up for patients presenting with metastatic lymph node infiltration by cancer of unknown primary and possible reasons for malignant lymph node transformation associated with Lynch syndrome.

A machine learning approach applied to gynecological ultrasound to predict progression-free survival in ovarian cancer patients

In a growing number of social and clinical scenarios, machine learning (ML) is emerging as a promising tool for implementing complex multi-parametric decision-making algorithms. Regarding ovarian cancer (OC), despite the standardization of features that can support the discrimination of ovarian masses into benign and malignant, there is a lack of accurate predictive modeling based on ultrasound (US) examination for progression-free survival (PFS). This retrospective observational study analyzed patients with epithelial ovarian cancer (EOC) who were followed in a tertiary center from 2018 to 2019. Demographic features, clinical characteristics, information about the surgery and post-surgery histopathology were collected. Additionally, we recorded data about US examinations according to the International Ovarian Tumor Analysis (IOTA) classification. Our study aimed to realize a tool to predict 12 month PFS in patients with OC based on a ML algorithm applied to gynecological ultrasound assessment. Proper feature selection was used to determine an attribute core set. Three different machine learning algorithms, namely Logistic Regression (LR), Random Forest (RFF), and K-nearest neighbors (KNN), were then trained and validated with five-fold cross-validation to predict 12 month PFS. Our analysis included n. 64 patients and 12 month PFS was achieved by 46/64 patients (71.9%). The attribute core set used to train machine learning algorithms included age, menopause, CA-125 value, histotype, FIGO stage and US characteristics, such as major lesion diameter, side, echogenicity, color score, major solid component diameter, presence of carcinosis. RFF showed the best performance (accuracy 93.7%, precision 90%, recall 90%, area under receiver operating characteristic curve (AUROC) 0.92). We developed an accurate ML model to predict 12 month PFS.