A 3D-Printable, Low-Cost Obturator for Less Invasive Gynecologic Brachytherapy.

The purpose of this report is to design, develop, and evaluate a cost-effective applicator for interstitial brachytherapy (ISBT) to minimize patient morbidity and facilitate access to curative radiation treatment for gynecologic cancers, especially in low-resource settings. A computer-aided design and prototype were developed of a proposed applicator that incorporates 44 slotted channels to gently guide needles, with or without a tandem, through the vaginal canal, effectively eliminating the need for transcutaneous needle insertions typically employed during ISBT of advanced gynecologic cancer and thus reducing the risk of vaginal laceration and bladder or rectal injury. The tested prototype was developed using AutoCAD software (Autodesk, San Francisco, CA) and 3D printed in Accura Xtreme Gray material using stereolithography. Small-scale iterative tests using a gelatin phantom were conducted on this prototype to confirm the efficacy of the applicator through inter-operator usability, needle stability, and needle arrangement. A promising prototype was developed aimed at addressing key issues with traditional perineum-based templates to facilitate ISBT, including being able to cover bulky tumors with parametrial extension reliably, decrease the risk of tissue or organ injury, and treat women with a prior hysterectomy. Results of preclinical testing demonstrated that the applicator met its purpose, suggesting that it may facilitate ISBT without the morbidity typically associated with the procedure, especially by addressing concerns associated with implementing the procedure in low-resource settings. The applicator shows substantial promise in the treatment of advanced gynecologic cancer. While further testing remains necessary to confirm its translatability to the clinical setting, the applicator appears capable of meeting its design objectives, representing its potential for improving upon current methods.

3D multimodal spatial fuzzy segmentation of intramuscular connective and adipose tissue from ultrashort TE MR images of calf muscle.

PURPOSE: To develop and evaluate an automated algorithm to segment intramuscular adipose (IMAT) and connective (IMCT) tissue from musculoskeletal MRI images acquired with a dual echo Ultrashort TE (UTE) sequence. THEORY AND METHODS: The dual echo images and calculated structure tensor images are the inputs to the multichannel fuzzy cluster mean (MCFCM) algorithm. Modifications to the basic multichannel fuzzy cluster mean include an adaptive spatial term and bias shading correction. The algorithm was tested on digital phantoms simulating IMAT/IMCT tissue under varying conditions of image noise and bias and on ten subjects with varying amounts of IMAT/IMCT. RESULTS: The MCFCM including the adaptive spatial term and bias shading correction performed better than the original MCFCM and adaptive spatial MCFCM algorithms. IMAT/IMCT was segmented from the unsmoothed simulated phantom data with a mean Dice coefficient of 0.933 ±0.001 when contrast-to-noise (CNR) was 140 and bias was varied between 30% and 65%. The algorithm yielded accurate in vivo segmentations of IMAT/IMCT with a mean Dice coefficient of 0.977 ±0.066. CONCLUSION: The proposed algorithm is completely automated and yielded accurate segmentation of intramuscular adipose and connective tissue in the digital phantom and in human calf data. Magn Reson Med 77:870-883, 2017. © 2016 International Society for Magnetic Resonance in Medicine.