Demonstrating the benefits of corrective intraoperative feedback in improving the quality of duodenal hydrogel spacer placement

Inter-Breath-Hold Geometric and Dosimetric Variations in Organs at Risk during Pancreatic Stereotactic Body Radiotherapy: Implications for Adaptive Radiation Therapy

Pancreatic cancer is the fourth leading cause of cancer-related death, with nearly 60,000 cases each year and less than a 10% 5-year overall survival rate. Radiation therapy (RT) is highly beneficial as a local-regional anticancer treatment. As anatomical variation is of great concern, motion management techniques, such as DIBH, are commonly used to minimize OARs toxicities; however, the variability between DIBHs has not been well studied. Here, we present an unprecedented systematic analysis of patients' anatomical reproducibility over multiple DIBH motion-management technique uses for pancreatic cancer RT. We used data from 20 patients; four DIBH scans were available for each patient to design 80 SBRT plans. Our results demonstrated that (i) there is considerable variation in OAR geometry and dose between same-subject DIBH scans; (ii) the RT plan designed for one scan may not be directly applicable to another scan; (iii) the RT treatment designed using a DIBH simulation CT results in different dosimetry in the DIBH treatment delivery; and (iv) this confirms the importance of adaptive radiation therapy (ART), such as MR-Linacs, for pancreatic RT delivery. The ART treatment delivery technique can account for anatomical variation between referenced and scheduled plans, and thus avoid toxicities of OARs because of anatomical variations between DIBH patient setups.

DAART: a deep learning platform for deeply accelerated adaptive radiation therapy for lung cancer

Purpose

The study aimed to implement a novel, deeply accelerated adaptive radiation therapy (DAART) approach for lung cancer radiotherapy (RT). Lung cancer is the most common cause of cancer-related death, and RT is the preferred medically inoperable treatment for early stage non-small cell lung cancer (NSCLC). In the current lengthy workflow, it takes a median of four weeks from diagnosis to RT treatment, which can result in complete restaging and loss of local control with delay. We implemented the DAART approach, featuring a novel deepPERFECT system, to address unwanted delays between diagnosis and treatment initiation.

Materials and methods

We developed a deepPERFECT to adapt the initial diagnostic imaging to the treatment setup to allow initial RT planning and verification. We used data from 15 patients with NSCLC treated with RT to train the model and test its performance. We conducted a virtual clinical trial to evaluate the treatment quality of the proposed DAART for lung cancer radiotherapy.

Results

We found that deepPERFECT predicts planning CT with a mean high-intensity fidelity of 83 and 14 HU for the body and lungs, respectively. The shape of the body and lungs on the synthesized CT was highly conformal, with a dice similarity coefficient (DSC) of 0.91, 0.97, and Hausdorff distance (HD) of 7.9 mm, and 4.9 mm, respectively, compared with the planning CT scan. The tumor showed less conformality, which warrants acquisition of treatment Day1 CT and online adaptive RT. An initial plan was designed on synthesized CT and then adapted to treatment Day1 CT using the adapt to position (ATP) and adapt to shape (ATS) method. Non-inferior plan quality was achieved by the ATP scenario, while all ATS-adapted plans showed good plan quality.

Conclusion

DAART reduces the common online ART (ART) treatment course by at least two weeks, resulting in a 50% shorter time to treatment to lower the chance of restaging and loss of local control.

Ultrasound Imaging with Flexible Array Transducer for Pancreatic Cancer Radiation Therapy

Pancreatic cancer with less than 10% 3-year survival rate is one of deadliest cancer types and greatly benefits from enhanced radiotherapy. Organ motion monitoring helps spare the normal tissue from high radiation and, in turn, enables the dose escalation to the target that has been shown to improve the effectiveness of RT by doubling and tripling post-RT survival rate. The flexible array transducer is a novel and promising solution to address the limitation of conventional US probes. We proposed a novel shape estimation for flexible array transducer using two sequential algorithms: (i) an optical tracking-based system that uses the optical markers coordinates attached to the probe at specific positions to estimate the array shape in real-time and (ii) a fully automatic shape optimization algorithm that automatically searches for the optimal array shape that results in the highest quality reconstructed image. We conducted phantom and in vivo experiments to evaluate the estimated array shapes and the accuracy of reconstructed US images. The proposed method reconstructed US images with low full-width-at-half-maximum (FWHM) of the point scatters, correct aspect ratio of the cyst, and high-matching score with the ground truth. Our results demonstrated that the proposed methods reconstruct high-quality ultrasound images with significantly less defocusing and distortion compared with those without any correction. Specifically, the automatic optimization method reduced the array shape estimation error to less than half-wavelength of transmitted wave, resulting in a high-quality reconstructed image.

deepPERFECT: Novel Deep Learning CT Synthesis Method for Expeditious Pancreatic Cancer Radiotherapy

Major sources of delay in the standard of care RT workflow are the need for multiple appointments and separate image acquisition. In this work, we addressed the question of how we can expedite the workflow by synthesizing planning CT from diagnostic CT. This idea is based on the theory that diagnostic CT can be used for RT planning, but in practice, due to the differences in patient setup and acquisition techniques, separate planning CT is required. We developed a generative deep learning model, deepPERFECT, that is trained to capture these differences and generate deformation vector fields to transform diagnostic CT into preliminary planning CT. We performed detailed analysis both from an image quality and a dosimetric point of view, and showed that deepPERFECT enabled the preliminary RT planning to be used for preliminary and early plan dosimetric assessment and evaluation.

Systematic study of the iodinated rectal hydrogel spacer material discrepancy on accuracy of proton dosimetry

Purpose

Iodination of rectal hydrogel spacer increases the computed tomography (CT) visibility. The effect of iodinated hydrogel spacer material on the accuracy of proton dosimetry has not been fully studied yet. We presented a systematic study to determine the effect of iodination on proton dosimetry accuracy during proton therapy (PT).

Methods

PT plans were designed for 20 prostate cancer patients with rectal hydrogel spacer. Three variations of hydrogel density were considered. First, as the ground truth, the true elemental composition of hydrogel true material (TM), verified by our measurement of spacer stopping power ratio, was used for plan optimization and Monte Carlo dose calculation. The dose distribution was recalculated with (1) no material (NM) override based on the CT intensity of the iodinated spacer, and (2) the water material (WM) override, where spacer material was replaced by water. The plans were compared with the ground truth using the metrics of gamma index (GI) and dosimetric indices.

Results

The iodination of hydrogel spacer affected the proton dose distribution with the NM scenario showing the most deviation from the ground truth. The iodination of spacer resulted in a notable increase in CT intensity and led to the treatment planning systems mistreating the iodinated spacer as a high‐density material. Among the structures adjacent to the target, neurovascular bundles showed the largest dose difference, up to 350 cGy or about 5% of the prescribed dose with NM. Compared to the WM scenario, dose distribution similarity and GI passing ratios were lower in the NM scenario.

Conclusion

The inaccurate CT intensity‐based material for iodinated spacer resulted in errors in PT dose calculation. We found that the error was negligible if the iodinated spacer was replaced with water. Water density can be used as a clinically accessible and convenient alternative material override to true spacer material.