scholarly journals Case Report: Role of an Iodinated Rectal Hydrogel Spacer, SpaceOAR Vue™, in the Context of Low-Dose-Rate Prostate Brachytherapy, for Enhanced Post-Operative Contouring to Aid in Accurate Implant Evaluation and Dosimetry

2021 ◽  
Vol 11 ◽  
Author(s):  
Andrew Gross ◽  
Jiankui Yuan ◽  
Daniel Spratt ◽  
Elisha Fredman

We present a case series of 13 consecutive patients with prostate cancer treated with low-dose-rate (LDR) brachytherapy, utilizing SpaceOAR Vue™, the recent iodinated iteration of the SpaceOAR™ hydrogel rectal spacer. Low- and favorable intermediate-risk patients receiving monotherapy and unfavorable intermediate- and high-risk patients undergoing a brachytherapy boost were included. Permanent brachytherapy can result in subacute and late rectal toxicity, and precise contouring of the anterior rectal wall and posterior aspect of the prostate is essential for accurate dosimetry to confirm a safe implant. Clearly visible on non-contrast CT imaging, SpaceOAR Vue™ can substantially aid in post-implant contouring and analysis. Not previously described in the literature in the context of LDR brachytherapy, we demonstrate the added clinical benefit of placing a well-visualized rectal spacer.

2021 ◽  
Author(s):  
Reyhaneh Nosrati

Permanent implantation of low-dose-rate (LDR) brachytherapy seeds is a well-established treatment modality for patients with localized prostate cancer. The quality of the implant is assessed within 30 days following implantation through post-implant dosimetry. The standard recommended procedure for post-implant dosimetry is based on computed tomography (CT). CT provides excellent seed visualization and localization; however, due to poor soft tissue contrast and challenging anatomical identificatio,n it leads to significant interobserver variabilities. The current MRI-CT fusion-based workflow for post-implant dosimetry LDR prostate brachytherapy takes advantage of the superior soft tissue contrast of MRI but still relies on CT for seed visualization and detection, and it suffers from image fusion uncertainties and extra cost and logistics. The lack of positive contrast from brachytherapy seeds in conventional MR images remains a major challenge towards an MRI-only workflow for post-implant dosimetry of Low- Dose-Rate (LDR) brachytherapy. In this thesis, a clinically feasible MRI-based workflow has been developed for brachytherapy seed visualization and localization. The seed visualization is based on a novel Quantitative Susceptibility Mapping (QSM) algorithm. The proposed seed localization on QSM utilizes machine learning algorithms. The reliability of the proposed workflow has been validated on 23 patients by comparing the seed positions and final dosimetric parameters between the proposed MRI-only workflow and the clinical CT-MRI fusion-based approach and there was excellent agreement between the two methods.


2021 ◽  
Author(s):  
Reyhaneh Nosrati

Permanent implantation of low-dose-rate (LDR) brachytherapy seeds is a well-established treatment modality for patients with localized prostate cancer. The quality of the implant is assessed within 30 days following implantation through post-implant dosimetry. The standard recommended procedure for post-implant dosimetry is based on computed tomography (CT). CT provides excellent seed visualization and localization; however, due to poor soft tissue contrast and challenging anatomical identificatio,n it leads to significant interobserver variabilities. The current MRI-CT fusion-based workflow for post-implant dosimetry LDR prostate brachytherapy takes advantage of the superior soft tissue contrast of MRI but still relies on CT for seed visualization and detection, and it suffers from image fusion uncertainties and extra cost and logistics. The lack of positive contrast from brachytherapy seeds in conventional MR images remains a major challenge towards an MRI-only workflow for post-implant dosimetry of Low- Dose-Rate (LDR) brachytherapy. In this thesis, a clinically feasible MRI-based workflow has been developed for brachytherapy seed visualization and localization. The seed visualization is based on a novel Quantitative Susceptibility Mapping (QSM) algorithm. The proposed seed localization on QSM utilizes machine learning algorithms. The reliability of the proposed workflow has been validated on 23 patients by comparing the seed positions and final dosimetric parameters between the proposed MRI-only workflow and the clinical CT-MRI fusion-based approach and there was excellent agreement between the two methods.


2016 ◽  
Vol 121 (2) ◽  
pp. 310-315 ◽  
Author(s):  
Robert Laing ◽  
Adrian Franklin ◽  
Jennifer Uribe ◽  
Alex Horton ◽  
Santiago Uribe-Lewis ◽  
...  

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