Faculty Bibliography

BACKGROUND/OBJECTIVE/UNASSIGNED:The frequency of hematospermia in transgender women is unknown. This report aimed to describe the development of hematospermia in a transgender woman. CASE REPORT/UNASSIGNED:A 35-year-old transgender woman treated with estradiol valerate and leuprolide presented with painless rust-tinged ejaculate, urethral bleeding after ejaculation, and intermittent hematuria. Her medical history included gastroesophageal reflux disease, internal hemorrhoids, and attention deficit hyperactivity disorder with negative tobacco smoking and urologic history. Additional medications included emtricitabine-tenofovir disoproxil fumarate and fexofenadine. Physical examination did not reveal constitutional or genitourinary abnormalities. Urinalysis and culture disclosed rare white blood cells with gram-variable bacilli. The chlamydia, gonorrhea, and human immunodeficiency virus test results were negative. Abdominal computed tomography did not reveal bladder or prostate cancer, calcifications, inflammation, or cysts. She continued to have symptoms after this initial workup. One year after the initial symptom onset, transrectal ultrasound disclosed a 1.7-cm midline posterior prostatic cyst with hemorrhagic products, later revealed by magnetic resonance imaging as communicating with the left seminal vesicle. Two ultrasound-guided transperineal biopsy samples revealed benign prostatic tissue with a small focus of Müllerian or endometrial-type tissue, evidenced by immunopositivity for paired-box gene 8 and estrogen receptor in epithelium and cluster of differentiation 10 immunopositivity in stroma. After medical consultation, the patient underwent prostatic cyst aspiration, resection of the transurethral ejaculatory ducts, and orchiectomy. She did not experience any complications after these procedures. DISCUSSION/UNASSIGNED:The etiology of hematospermia may be idiopathic, iatrogenic, anatomic, or pathologic. CONCLUSION/UNASSIGNED:Occult endometriosis or ectopic Müllerian epithelial tissue growth may occur in transgender women taking feminizing gender-affirming hormone therapy.

PURPOSE/UNASSIGNED:Stimulated Raman histology is an innovative technology that generates real-time, high-resolution microscopic images of unprocessed tissue, significantly reducing prostate biopsy interpretation time. This study aims to evaluate the ability for an artificial intelligence convolutional neural network to interpretate prostate biopsy histologic images created with stimulated Raman histology. MATERIALS AND METHODS/UNASSIGNED:Unprocessed, unlabeled prostate biopsies were prospectively imaged using a stimulated Raman histology microscope. Following stimulated Raman histology creation, the cores underwent standard pathological processing and interpretation by at least 2 genitourinary pathologists to establish a ground truth assessment. A network, trained on 303 prostate biopsies from 100 participants, was used to measure the accuracy, sensitivity, and specificity of detecting prostate cancer on stimulated Raman histology relative to conventional pathology. The performance of the artificial intelligence was evaluated on an independent 113-biopsy test set. RESULTS/UNASSIGNED:Prostate biopsy images obtained through stimulated Raman histology can be generated within a time frame of 2 to 2.75 minutes. The artificial intelligence system achieved a rapid classification of prostate biopsies with cancer, with a potential identification time of approximately 1 minute. The artificial intelligence demonstrated an impressive accuracy of 96.5% in detecting prostate cancer. Moreover, the artificial intelligence exhibited a sensitivity of 96.3% and a specificity of 96.6%. CONCLUSIONS/UNASSIGNED:Stimulated Raman histology generates microscopic images capable of accurately identifying prostate cancer in real time, without the need for sectioning or tissue processing. These images can be interpreted by artificial intelligence, providing physicians with near-real-time pathological feedback during the diagnosis or treatment of prostate cancer.

INTRODUCTION/BACKGROUND:Delay between targeted prostate biopsy (PB) and pathologic diagnosis can lead to a concern of inadequate sampling and repeated biopsy. Stimulated Raman histology (SRH) is a novel microscopic technique allowing real-time, label-free, high-resolution microscopic images of unprocessed, unsectioned tissue. This technology holds potential to decrease the time for PB diagnosis from days to minutes. We evaluated the concordance of pathologist interpretation of PB SRH as compared with traditional hematoxylin and eosin (H&E) stained slides. METHODS:, to create SRH images. The cores were then processed as per normal pathologic protocols. Sixteen PB containing a mix of benign and malignant histology were used as an SRH training cohort for four genitourinary pathologists, who were then tested on a set of 32 PBs imaged by SRH and processed by traditional H&E. Sensitivity, specificity, accuracy, and concordance for prostate cancer (PCa) detection on SRH relative to H&E were assessed. RESULTS:The mean pathologist accuracy for the identification of any PCa on PB SRH was 95.7%. In identifying any PCa or ISUP grade group 2-5 PCa, a pathologist was independently able to achieve good and very good concordance (κ: 0.769 and 0.845, respectively; p < 0.001). After individual assessment was completed a pathology consensus conference was held for the interpretation of the PB SRH; after the consensus conference the pathologists' concordance in identifying any PCa was also very good (κ: 0.925, p < 0.001; sensitivity 95.6%; specificity 100%). CONCLUSION/CONCLUSIONS:SRH produces high-quality microscopic images that allow for accurate identification of PCa in real-time without need for sectioning or tissue processing. The pathologist performance improved through progressive training, showing that ultimately high accuracy can be obtained. Ongoing SRH evaluation in the diagnostic and treatment setting hold promise to reduce time to tissue diagnosis, while interpretation by convolutional neural network may further improve diagnostic characteristics and broaden use.

Lymphoma of the urinary tract is relatively rare and comprises of < 5% of all primary extra nodal lymphoma. Diagnoses of these lesions at anearly stage is important as they can disseminate or transform into high grade lesion if there is a delay in the diagnoses. There are only few case series and case reports on the malignant lymphoma of the urinary tract. The aim of this study was to characterize lymphoma involving the urinary bladder and prostate. We retrospectively reviewed the clinical data and histologic findings of the malignant lymphoma involving urinary bladder and prostate at our institution. Lymphoma involving the lower urinary tract clinically presented with lower urinary tract symptoms and usually with concurrent associated urinary bladder cancer or prostatic cancer in our series. Lymphoma should be included in the differential diagnoses especially in patients with prior history of lymphoid disorders. There should be a high index of suspicion when there is any atypical lymphoid infiltrate in routine urinary bladder and prostate surgical specimens.

Introduction & Objectives: Delay between prostate biopsy (PB) and pathologic diagnosis leads to a concern of inadequate sampling and repeated biopsy. Stimulated Raman Histology (SRH) is a novel microscopic technique allowing real time, label-free, high-resolution microscopic images of unprocessed, un-sectioned tissue. We evaluated the accuracy of pathologist interpretation of PB SRH as compared to traditional hematoxylin and eosin (H&E) stained slides.
Material(s) and Method(s): Men undergoing prostatectomy were included in an IRB approved prospective study. 18-gauge PB cores, taken ex vivo from prostatectomy specimen, were scanned in a SRH microscope at 20 microns depth over 10-14 minutes using two Raman shifts: 2845cm-1 and 2930cm-1, to create SRH images. The cores were then processed as per normal pathologic protocols. 16 PB containing benign/prostate cancer histology were used as a SRH training cohort for 4 GU pathologists (1, 3, 2x >15 yrs experience), who were then tested on a set of 32 PB imaged by SRH and processed by traditional H&E. Sensitivity, specificity, and concordance for PCa detection on SRH relative to a consensus H&E were assessed. With a two-sided alpha level of 5%, it was calculated 32 SRH imaged biopsies would provide 90% power to detect concordance (k).
Result(s): PB cores were imaged in 2-3 separate strips (11-21 minutes) shown in Figure 1. In identifying any cancer, pathologists achieved moderate concordance (k=0.570; p<0.001) which improved when identifying GGG 2-5 PCa only (k=0.640, p<0001; sensitivity 96.4%; specificity 58.3%). In predicting Gleason score, the concordance for each pathologist varied from poor to moderate (k range -0.163 to 0.457). After individual assessment was completed a pathology consensus conference was held for the interpretation of the SRH PB. In identifying any prostate cancer, pathologists achieved near perfect concordance (k=0.925; p<0.001; sensitivity 95.6%; specificity 100%). When evaluating SRH in a consensus conference, the group prediction of Gleason score improved to moderate concordance (k=0.470; p<0.001). (Figure Presented) (Figure Presented)
Conclusion(s): SRH produces high quality microscopic images that allow for accurate identification of PCa in real-time without need for sectioning or tissue-processing. Individual pathologist performance varied highly suggesting potential for improvement with further training. Future SRH interpretation by convolutional neural network may further enhance GGG prediction
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When multiple cores are biopsied from a single magnetic resonance imaging (MRI)-targeted lesion, Gleason grade may be assigned for each core separately or for all cores of the lesion in aggregate. Because of the potential for disparate grades, an optimal method for pathology reporting MRI lesion grade awaits validation. We examined our institutional experience on the concordance of biopsy grade with subsequent radical prostatectomy (RP) grade of targeted lesions when grade is determined on individual versus aggregate core basis. For 317 patients (with 367 lesions) who underwent MRI-targeted biopsy followed by RP, targeted lesion grade was assigned as (1) global Grade Group (GG), aggregated positive cores; (2) highest GG (highest grade in single biopsy core); and (3) largest volume GG (grade in the core with longest cancer linear length). The 3 biopsy grades were compared (equivalence, upgrade, or downgrade) with the final grade of the lesion in the RP, using κ and weighted κ coefficients. The biopsy global, highest, and largest GGs were the same as the final RP GG in 73%, 68%, 62% cases, respectively (weighted κ: 0.77, 0.79, and 0.71). For cases where the targeted lesion biopsy grade scores differed from each other when assigned by global, highest, and largest GG, the concordance with the targeted lesion RP GG was 69%, 52%, 31% for biopsy global, highest, and largest GGs tumors (weighted κ: 0.65, 0.68, 0.59). Overall, global, highest, and largest GG of the targeted biopsy show substantial agreement with RP-targeted lesion GG, however targeted global GG yields slightly better agreement than either targeted highest or largest GG. This becomes more apparent in nearly one third of cases when each of the 3 targeted lesion level biopsy scores differ. These results support the use of global (aggregate) GG for reporting of MRI lesion-targeted biopsies, while further validations are awaited.