The Development of an Autonomous Robotic Surgical Framework for Breast Brachytherapy
Creators: Afshar, Mehrnoosh
Publisher: name: University of Alberta Library
Year: 2023

<p>Low-dose-rate-permanent-seed (LDR-PS) brachytherapy is a minimally inva-<br>
sive radiotherapy technique used after breast lumpectomy to prevent the re-<br>
growth of cancerous cells around the margins of a hollowed-out tumor (seroma).<br>
This approach involves implanting multiple radioactive seeds (each measuring<br>
2-3mm in length) in and around the seroma, gradually irradiating and elimi-<br>
nating any remaining cancerous cells. LDR-PS brachytherapy has had signif-<br>
icant success in treating prostate cancer and is now being explored for breast<br>
cancer treatment. However, it has a more established history in the former.<br>
During LDR-PS, the seeds are implanted into the breast using 6-20 fine<br>
flexible needles under ultrasound (US) imaging, following a pre-operative plan<br>
derived from dosimetry calculations based on the patient’s medical images<br>
(usually Computed Tomography or CT). Besides its clinical benefits over other<br>
radiotherapy methods like external beam radiation, LDR-PS promotes health-<br>
care equity and inclusion by reducing frequent hospital visits, benefiting both<br>
rural and urban patients.<br>
However, the adoption of LDR-PS brachytherapy has encountered chal-<br>
lenges. One significant limitation is the requirement for surgeons to undergo<br>
substantial training for accurate seed implantation, particularly in breast can-<br>
cer cases. Inaccurate placement of seeds during breast brachytherapy is pri-<br>
marily due to two factors: (1) the discrepancy between the intraoperative<br>
ultrasound images and the pre-operative CT/MRI images caused by breast<br>
tissue deformation, and (2) the utilization of non-specialized surgical tools<br>
and techniques designed for prostate surgery. Incorrect seed implantation can<br>
lead to inadequate radiotherapy and increased cancer recurrence risk. Ad-<br>
ditionally, using instruments intended for prostate surgery is inappropriate<br>
due to the breast’s mobility and compliance, as well as the needle’s limited<br>
maneuverability due to its shorter insertion length.<br>
This study explores the potential benefits of incorporating an Assistive<br>
Robotic Surgical System (ARSS) in the context of LDR-PS brachytherapy<br>
surgery. The research focuses on addressing the complexities of the surgical<br>
environment, which undergoes deformation due to surgical interactions and<br>
necessitates patient-specific tuning. The study presents a comprehensive ap-<br>
proach to developing a simulation environment suitable for ARSS, beginning<br>
with pre-operative design and demonstrating its effectiveness in active defor-<br>
mation control during LDR-PS brachytherapy surgery. Moreover, the study<br>
investigates methods for updating the pre-operative model intra-operatively<br>
and explores the use of a robotic arm for US-probe manipulation. The re-<br>
search provides valuable insights into the potential applications of ARSS in<br>
enhancing the performance of LDR-PS brachytherapy surgery. The main con-<br>
tributions of this thesis are as follows:<br>
Active tissue deformation for target manipulation: This research tackles<br>
the lack of real-time nonlinear tissue modeling integrated into a control frame-<br>
work for tissue manipulation. The study demonstrates the integration of a<br>
real-time deformable tissue solver into the control loop, enabling effective tar-<br>
get manipulation.<br>
Intra-operative model updates for target tracking: Two methods are de-<br>
veloped to improve the accuracy of target tracking based on patient-specific<br>
biomechanical models. The first method, KF-ADMM, incorporates data into<br>
an ADMM-based Finite Element Method (FEM) solver through Kalman Fil-<br>
tering. The second method utilizes a generative variational autoencoder struc-<br>
ture based on graph neural networks (GNN-VAE) to reduce the dimensionality<br>
of the input mesh. The Ensemble Smoother with Multiple Data Assimilation<br>
(ES-MDA) is employed for simultaneous updates, enhancing the corrective ca-<br>
pability of the KF-ADMM method. Robot-assisted US probe manipulation:<br>
The study utilizes a Panda dexterous robotic arm to control the US probe,<br>
accurately following the needle tip.<br>
Overall, this research advances the field of ARSS in LDR-PS brachytherapy<br>
surgery by addressing tissue manipulation, target tracking, sim-to-real regis-<br>
tration, and robot-assisted US probe manipulation. The findings highlight the<br>
potential to improve the performance and precision of LDR-PS brachytherapy<br>
procedures, particularly in complex surgical environments.</p>