High-resolution Diffusion-weighted Imaging to Detect Changes in Tumor Size and ADC, and Predict Adverse Biopsy Histology during Prostate Cancer Active Surveillance.

PURPOSE: Majority of men with low-risk prostate cancer can be managed with active surveillance (AS). This study evaluates a high-resolution diffusion-weighted imaging (HR-DWI) technique to predict adverse biopsy histology (AH), defined as Gleason score ≥7 on any biopsy or ≥3 increase in number of positive biopsy cores on systematic biopsies. We test the hypothesis that high-grade disease and progressing disease undergo subtle changes during even short intervals that can be detected by HR-DWI. EXPERIMENTAL DESIGN: In a prospective clinical trial, serial multiparametric MRIs, incorporating HR-DWI and standard DWI (S-DWI) were performed approximately 12 months apart prior to prostate biopsy (n = 59). HR-DWI, which uses reduced field-of-view and motion compensation techniques, was compared with S-DWI. RESULTS: HR-DWI had a 3-fold improvement in spacial resolution compared with S-DWI as confirmed using imaging phantoms. For detecting AH, multiparametric MRI using HR-DWI had a sensitivity of 75% and specificity of 83.9%, and MRI using S-DWI had a sensitivity of 71.4% and specificity of 54.8%. The AUC for HR-DWI was significantly higher (0.794 vs. 0.631, P = 0.014). Secondary analyses of univariable predictors of AH showed tumor size increase [OR 16.8; 95% confidence interval (CI): 4.06-69.48; P < 0.001] and apparent diffusion coefficient (ADC) decrease (OR 5.06; 95% CI: 1.39-18.38; P = 0.014) on HR-DWI were significant predictors of AH. CONCLUSION: HR-DWI outperforms S-DWI in predicting AH. Patient with AH have tumors that change in size and ADC that could be detected using HR-DWI. Future studies with longer follow-up should assess HR-DWI for predicting disease progression during AS. SIGNIFICANCE: We report on a prospective clinical trial using a MRI that has three times the resolution of standard MRI. During AS for prostate cancer, two high-resolution MRIs performed approximately a year apart can detect tumor changes that predict the presence of aggressive cancers that should be considered for curative therapy such as prostatectomy or radiation.

E. faecalis Sepsis and Asherman's Syndrome as Complications of Sonata System Transcervical Fibroid Ablation.

The Sonata System is a minimally invasive, ultrasound-guided transcervical fibroid ablation procedure for the management of symptomatic uterine fibroids. Since its approval by the US Food and Drug Administration in 2018, this procedure has demonstrated an excellent safety profile and postprocedure satisfaction rate. We present the case of a patient treated with Sonata, who subsequently developed bacterial sepsis and Asherman's syndrome-serious complications with long-term sequelae and implications for fertility. A nulligravid woman in her 40s presented in the outpatient setting with dysmenorrhea and bulk symptoms, with imaging showing an enlarged myomatous uterus compressing the urinary bladder. She desired minimally invasive, fertility-preserving management and underwent the Sonata procedure at an outside hospital. On postoperative day 3, she was admitted to our institution with abdominal pain, fever, tachycardia, and Enterococcus faecalis bacteremia. Despite 6 days of culture-directed antibiotic therapy, the patient remained septic with worsening symptoms and imaging findings and with persistent bacteremia. On hospital day 7, the patient underwent laparoscopic myomectomy and excision of hemorrhagic, infected myometrium. She recovered appropriately after surgery and was discharged home on hospital day 11 to continue 2 weeks of intravenous antibiotics. Nine months after myomectomy, the patient was diagnosed as having Asherman's syndrome. She subsequently had an early pregnancy loss with retained products of conception, requiring hysteroscopic lysis of adhesions and dilation and curettage. Ultimately, careful patient selection is critical for the optimal application of the Sonata procedure. Limiting the extent of fibroid necrosis after treatment is a reasonable goal to minimize the risk of secondary bacterial infection and adhesiogenesis as procedural sequelae.

Segmentation of Pancreatic Subregions in Computed Tomography Images.

The accurate segmentation of pancreatic subregions (head, body, and tail) in CT images provides an opportunity to examine the local morphological and textural changes in the pancreas. Quantifying such changes aids in understanding the spatial heterogeneity of the pancreas and assists in the diagnosis and treatment planning of pancreatic cancer. Manual outlining of pancreatic subregions is tedious, time-consuming, and prone to subjective inconsistency. This paper presents a multistage anatomy-guided framework for accurate and automatic 3D segmentation of pancreatic subregions in CT images. Using the delineated pancreas, two soft-label maps were estimated for subregional segmentation-one by training a fully supervised naïve Bayes model that considers the length and volumetric proportions of each subregional structure based on their anatomical arrangement, and the other by using the conventional deep learning U-Net architecture for 3D segmentation. The U-Net model then estimates the joint probability of the two maps and performs optimal segmentation of subregions. Model performance was assessed using three datasets of contrast-enhanced abdominal CT scans: one public NIH dataset of the healthy pancreas, and two datasets D1 and D2 (one for each of pre-cancerous and cancerous pancreas). The model demonstrated excellent performance during the multifold cross-validation using the NIH dataset, and external validation using D1 and D2. To the best of our knowledge, this is the first automated model for the segmentation of pancreatic subregions in CT images. A dataset consisting of reference anatomical labels for subregions in all images of the NIH dataset is also established.

Ovarian Transposition Before Pelvic Radiation Therapy: Spatial Distribution and Dose Volume Analysis.

PURPOSE: There is a paucity of data analyzing the anatomic locations and dose volume metrics achieved for surgically transposed ovaries in patients desiring fertility or hormonal preservation receiving pelvic radiation therapy (RT), which were examined herein. METHODS AND MATERIALS: This is a retrospective study including women who underwent ovarian transposition before pelvic RT between 2010 to 2020. The craniocaudal (CC) distance of the ovary centroid to the (1) plane of the sacral promontory, (2) iliac crest, and (3) the nearest distance between the ovary edge and RT planning target volume (PTV) were measured (cm). The area under the receiver operating characteristic curve and cut-point analysis estimating ovary location outside the PTV was performed. RESULTS: Thirty-one ovaries were analyzed from 18 patients. Thirteen (72.2%) were treated with intensity modulated RT, and 5 (27.8%) were treated with 3-dimensional conformal radiation therapy. Most ovaries were located above the sacral promontory (64.5%, n = 20), below the iliac crest (96.8%, n = 30), and outside the PTV (64.5%, n = 20). The median distance from the ovaries to the sacral promontory, iliac crest, and PTV was 0.8 cm (interquartile range [IQR], -0.83 to 1.59 cm), -3.22 cm (IQR, -5.12 to -1.84 cm), and 0.9 cm (IQR, -1.0 to 1.9 cm), respectively. The area under the receiver operating characteristic curve and cut-point analysis demonstrated that distance from the iliac crest predicted an ovary to be outside the PTV with an optimal cut-point of -3.0 cm (C-index = 0.82). The median mean and maximum (Dmax) ovary doses were 15.5 Gy (IQR, 9.6-20.2 Gy) and 32.2 Gy (IQR 24.8-46.5 Gy), respectively. CONCLUSIONS: Despite most transposed ovaries being located outside the PTV, nearly all remained below the iliac crest and received RT doses associated with a high risk of ovarian failure. These findings deepen our understanding of the spatial relationship between transposed ovaries and dose to inform surgical and pre-RT planning and suggest that more aggressive ovary-sparing strategies are warranted.

Novel Diagnosis of Lyme Disease: Potential for CAM Intervention.

Lyme disease (LD) is the most common tick-borne disease in the northern hemisphere, producing a wide range of disabling effects on multiple human targets, including the skin, the nervous system, the joints and the heart. Insufficient clinical diagnostic methods, the necessity for prompt antibiotic treatment along with the pervasive nature of infection impel the development and establishment of new clinical diagnostic tools with increased accuracy, sensitivity and specificity. The goal of this article is 4-fold: (i) to detail LD infection and pathology, (ii) to review prevalent diagnostic methods, emphasizing inherent problems, (iii) to introduce the usage of in vivo induced antigen technology (IVIAT) in clinical diagnostics and (iv) to underscore the relevance of a novel comprehensive LD diagnostic approach to practitioners of Complementary and Alternative Medicine (CAM). Utilization of this analytical method will increase the accuracy of the diagnostic process and abridge the time to treatment, with antibiotics, herbal medicines and nutritional supplements, resulting in improved quality of care and disease prognosis.