Savi Scout Localization for Extrapelvic Endometriosis Resection.

BACKGROUND Endometriosis is a common cause of chronic pelvic pain among women globally. Pharmacological therapy for endometriosis includes non-steroidal anti-inflammatory drugs (NSAIDs) and hormonal contraceptives, while surgical therapy often involves either laparoscopic excision and ablation of endometriosis implants or open surgery. Surgical therapy is one of the mainstays of treatment especially for extrapelvic endometriomas. However, little guidance exists for the treatment of non-palpable or intermittently palpable lesions of this nature. CASE REPORT A 33-year-old woman with a previous cesarean section presented with complaints of intermittent discomfort in the area between her umbilicus and the surgical incision, for the previous 7 years, that worsened during her menstrual cycle. A 3×3-cm area of fullness was only intermittently palpable during various clinic visits, but was visualizable on computed tomography and magnetic resonance imaging. Given the lesion's varying palpability, a Savi Scout radar localization device was placed into the lesion pre-operatively to aid with surgical resection. The mass was excised, pathologic examination revealed endometrial tissue, and the patient had an uncomplicated postoperative course with resolution of her symptoms. CONCLUSIONS Surgical removal of extrapelvic endometrioma lesions can be made difficult by varying levels of palpability or localizability due to a patient's menstrual cycle. The Savi Scout, most commonly used in breast mass localization, is a useful tool in guiding surgical excision of non-palpable or intermittently palpable extrapelvic endometrioma lesions.

Intravenous Steroids for Refractory Chemotherapy-Related Diarrhea: A Case Report.

The clinical course of a patient with chemotherapy-related diarrhea (CRD) refractory to standard therapy was monitored over the course of 21 days. The patient was minimally responsive to traditional treatment options, including bismuth subsalicylate, diphenoxylate-atropine, loperamide, octreotide, and oral (PO) steroids, and exhibited reportable improvements with the addition of intravenous (IV) methylprednisolone to other antidiarrheal agents. We present a case of CRD in an 82-year-old female. She was initiated on chemotherapy three weeks prior and has experienced severe diarrhea since her initiation. Despite the use of first-line antidiarrheal therapies, including loperamide, diphenoxylate-atropine, and octreotide, both subcutaneously and via continuous infusion drip, no infectious cause was found. She also received the non-absorbing corticosteroid budesonide, but her diarrhea persisted. After experiencing severe hypotension and hypovolemia secondary to profuse diarrhea, she was placed on IV steroids, which quickly reduced her symptoms. The patient was then transitioned to oral steroids and discharged on a tapering regimen. We recommend using IV steroids to treat CRD if first-line therapies fail. Utilizing IV steroids efficiently and effectively can decrease the symptoms of persistent diarrhea and lead to rapid recovery.

A Rare Case of Ruptured Appendicitis Secondary to Metastatic Ovarian Cancer.

BACKGROUND Patients with advanced stage ovarian cancer typically have vague non-specific abdominal symptoms related to pelvic tumor, metastasis, and ascites. When these patients present with more acute abdominal pain, appendicitis is rarely considered. Acute appendicitis due to metastatic ovarian cancer has been sparsely documented in the medical literature; only twice, to our knowledge. CASE REPORT A 61-year-old woman with a 3-week history of abdominal pain, shortness of breath, and bloating was diagnosed with ovarian cancer after computed tomography (CT) demonstrated a large pelvic cystic and solid mass. Five weeks later she underwent an omental biopsy to determine cell type and potential upstaging of the ovarian cancer to stage IV, as other aggressive cancers such as breast cancer can also involve the pelvis/omentum. Seven hours after her biopsy, she presented with increasing abdominal pain. Post-biopsy complications such as hemorrhage or bowel perforation were initially suspected to be the cause of her abdominal pain. However, CT demonstrated ruptured appendicitis. The patient underwent an appendectomy and histopathologic examination of the specimen revealed infiltration by low-grade ovarian serous carcinoma. CONCLUSIONS Given the low incidence of spontaneous acute appendicitis in this patient's age group, and the lack of any other clinical, surgical, or histopathological evidence to suggest another cause, metastatic disease was ruled to be the likely source of her acute appendicitis. Providers should be aware of appendicitis in a broad differential diagnosis and have a low threshold for ordering abdominal pelvis CT when advanced stage ovarian cancer patients present with acute abdominal pain.

Augmenting Career Longevity: An Analysis of Ergonomics Training Among 134 Neurological Surgeons.

BACKGROUND: Work-related pain among neurosurgeons remains understudied, yet can have long-term consequences which affect operative efficiency and efficacy, career longevity, and life outside of work. OBJECTIVE: This study provides insight into the extent of pain experienced by neurosurgeons and the effect of ergonomics training on pain. METHODS: An online survey pertaining to ergonomics and pain was sent to all neurosurgeons on the Council of State Neurosurgical Societies (CSNS) email distribution list. Statistical comparisons of age groups against pain levels and ergonomics training against pain levels, as well as multivariate linear regression of demographics, training, and operating factors against pain levels were performed. RESULTS: One hundred and thirty-four neurosurgeons responded to the survey. The mean average severity of pain across respondents was 3.3/10 and the mean peak severity of pain was 5.1/10. Among the reported peak pain severity scores, neurosurgeons with 21-30 years of operating experience had significantly higher pain scores than those with 11-20 years of experience (mean 6.2 vs. 4.2; P < 0.05), while neurosurgeons with more than 30 years of experience had significantly less pain than those with 21-30 years of experience (mean 4.4 vs. 6.2, P = 0.005). Training in ergonomics did not significantly improve respondents' reported peak or mean pain severities (17.9% reported having ergonomics training). CONCLUSIONS: Ergonomics training did not appear to make a difference in neurosurgeons' pain severities. This may signify a need to optimize ergonomics pedagogy to achieve observable benefits.

Machine Learning for Hepatocellular Carcinoma Segmentation at MRI: Radiology In Training.

A 68-year-old woman with a history of hepatocellular carcinoma underwent conventional transarterial chemoembolization. Manual tumor segmentation on images, which can be used to assess disease progression, is time consuming and may suffer from interobserver reliability issues. The authors present a how-to guide to develop machine learning algorithms for fully automatic segmentation of hepatocellular carcinoma and other tumors for lesion tracking over time.

Harnessing clinical annotations to improve deep learning performance in prostate segmentation.

PURPOSE: Developing large-scale datasets with research-quality annotations is challenging due to the high cost of refining clinically generated markup into high precision annotations. We evaluated the direct use of a large dataset with only clinically generated annotations in development of high-performance segmentation models for small research-quality challenge datasets. MATERIALS AND METHODS: We used a large retrospective dataset from our institution comprised of 1,620 clinically generated segmentations, and two challenge datasets (PROMISE12: 50 patients, ProstateX-2: 99 patients). We trained a 3D U-Net convolutional neural network (CNN) segmentation model using our entire dataset, and used that model as a template to train models on the challenge datasets. We also trained versions of the template model using ablated proportions of our dataset, and evaluated the relative benefit of those templates for the final models. Finally, we trained a version of the template model using an out-of-domain brain cancer dataset, and evaluated the relevant benefit of that template for the final models. We used five-fold cross-validation (CV) for all training and evaluation across our entire dataset. RESULTS: Our model achieves state-of-the-art performance on our large dataset (mean overall Dice 0.916, average Hausdorff distance 0.135 across CV folds). Using this model as a pre-trained template for refining on two external datasets significantly enhanced performance (30% and 49% enhancement in Dice scores respectively). Mean overall Dice and mean average Hausdorff distance were 0.912 and 0.15 for the ProstateX-2 dataset, and 0.852 and 0.581 for the PROMISE12 dataset. Using even small quantities of data to train the template enhanced performance, with significant improvements using 5% or more of the data. CONCLUSION: We trained a state-of-the-art model using unrefined clinical prostate annotations and found that its use as a template model significantly improved performance in other prostate segmentation tasks, even when trained with only 5% of the original dataset.

Optimizing Spatial Biopsy Sampling for the Detection of Prostate Cancer.

PURPOSE: The appropriate number of systematic biopsy cores to retrieve during magnetic resonance imaging (MRI)-targeted prostate biopsy is not well defined. We aimed to demonstrate a biopsy sampling approach that reduces required core count while maintaining diagnostic performance. MATERIALS AND METHODS: We collected data from a cohort of 971 men who underwent MRI-ultrasound fusion targeted biopsy for suspected prostate cancer. A regional targeted biopsy (RTB) was evaluated retrospectively; only cores within 2 cm of the margin of a radiologist-defined region of interest were considered part of the RTB. We compared detection rates for clinically significant prostate cancer (csPCa) and cancer upgrading rate on final whole mount pathology after prostatectomy between RTB, combined, MRI-targeted, and systematic biopsy. RESULTS: A total of 16,459 total cores from 971 men were included in the study data sets, of which 1,535 (9%) contained csPCa. The csPCa detection rates for systematic, MRI-targeted, combined, and RTB were 27.0% (262/971), 38.3% (372/971), 44.8% (435/971), and 44.0% (427/971), respectively. Combined biopsy detected significantly more csPCa than systematic and MRI-targeted biopsy (p <0.001 and p=0.004, respectively) but was similar to RTB (p=0.71), which used on average 3.8 (22%) fewer cores per patient. In 102 patients who underwent prostatectomy, there was no significant difference in upgrading rates between RTB and combined biopsy (p=0.84). CONCLUSIONS: A RTB approach can maintain state-of-the-art detection rates while requiring fewer retrieved cores. This result informs decision making about biopsy site selection and total retrieved core count.

Federated learning improves site performance in multicenter deep learning without data sharing.

OBJECTIVE: To demonstrate enabling multi-institutional training without centralizing or sharing the underlying physical data via federated learning (FL). MATERIALS AND METHODS: Deep learning models were trained at each participating institution using local clinical data, and an additional model was trained using FL across all of the institutions. RESULTS: We found that the FL model exhibited superior performance and generalizability to the models trained at single institutions, with an overall performance level that was significantly better than that of any of the institutional models alone when evaluated on held-out test sets from each institution and an outside challenge dataset. DISCUSSION: The power of FL was successfully demonstrated across 3 academic institutions while avoiding the privacy risk associated with the transfer and pooling of patient data. CONCLUSION: Federated learning is an effective methodology that merits further study to enable accelerated development of models across institutions, enabling greater generalizability in clinical use.