Concurrent Radiation and Deep Hyperthermia Therapy for the Treatment of Recurrent Prostate Cancer

PURPOSE/OBJECTIVE(S)

Robustpreclinical and clinical data have established hyperthermia as an effective radiosensitizer which can be used in the setting of recurrent disease to enhance the therapeutic window. We present a single institution experience examining outcomes in recurrent prostate cancer (RPCA) patients treated with concurrent deep hyperthermia (DHT) and radiation (RT). We hypothesized that concurrent DHT and RT would be well tolerated and would provide durable local control without unexpected toxicity.

MATERIALS/METHODS

Consecutive RPCA patients treated with concurrent DHT and pelvic RT were retrospectively analyzed. Patients received twice weekly DHT treatments in addition to daily or twice daily (BID) RT. DHT was delivered using a concentric ring radiofrequency phased array system to a target temperature of 40-43°C. Acute and late treatment associated toxicities, graded per Common Terminology Criteria for Adverse Events (CTCAE) v5.0, were evaluated. Survival and control outcomes were evaluated using the Kaplan-Meier method.

RESULTS

Eighteen patients were included for analysis. Median patient age was 69 yrs (64-82 yrs). Fifteen (83%) patients had received prior RT and 12 (67%) patients had undergone radical prostatectomy. At time of treatment, two patients had RPCA which had dedifferentiated to a small cell phenotype. Eight (44%) patients had extra-pelvic disease at time of treatment. Seventeen (94%) patients received proton RT, while 1 (6%) received photon RT. Median RT dose was 49 Gy (range 30-73.8 Gy). Five (28%) patients received BID RT. Fifteen (83%) patients also received sequential or concurrent systemic therapy including androgen deprivation therapy or chemotherapy. A total of 142 DHT treatments were administered (median of 7.5 treatments). Fourteen (78%) patients completed ≥ 75% of planned DHT treatments. Reasons for inability to complete treatment included discomfort and abnormal vital signs during DHT. Only one patient reported Grade 2 pain and pruritus attributed to concurrent RT and DHT. One acute Grade 3 RT toxicity (diarrhea) was reported. No late Grade 3+ toxicities occurred. Of ten patients (56%) treated with curative intent, 8 (44%) had no reported failures at 2-year follow up while two had distant failure and biochemical failure respectively. Three (17%) patients were treated with palliative intent for disease related pain; two reported partial relief and one reported complete pain relief. With a median follow-up of 27 months (1-46 months), 2-year failure free survival was 41.4% (95% CI: 27.8-55%), local control was 76.5% (95% CI 66.2-86.8%) and overall survival was 70.9% (95% CI 58.4-83.3%).

CONCLUSION

Our results suggest that concurrent RT and DHT is well tolerated and allows for safe escalation of local therapy for RPCA, providing patients with durable local control and palliation with an acceptable toxicity profile. Prospective validation is warranted.

Pelvis Treatment Plan Dose Comparison for Proton Therapy Using Single Energy and Dual Energy Computed Tomography Simulation Methods

PURPOSE/OBJECTIVE(S)

In proton therapy, plan robustness is ameliorated by expanding the irradiation volume beyond the target, in order to mitigate setup and proton range uncertainties (RU). A byproduct of this expansion is elevated doses to surrounding organs at risk (OARs) which reduce some of the benefits associated with proton therapy. Dual-energy CT (DECT) has been shown in multiple phantom and animal tissue studies to reduce RU without compromising plan robustness. This study quantifies dosimetric differences between single-energy CT (SECT) and DECT for pelvis patients treated with intensity modulated proton therapy (IMPT).

MATERIALS/METHODS

Under IRB approval, SECT and DECT scans from 25 IMPT pelvis patients were acquired using a CT scanner. Clinical plans were generated on the SECT images using robust optimization settings of 3.5% RU and 5 mm setup uncertainty in a treatment planning system. Subsequently, the clinical plans were recomputed on the corresponding DECT generated SPR-map images. For each patient, target coverage, mean and maximum OAR doses were compared for both image sets.

RESULTS

Comparison of two plans showed systematic differences in target minimum dose (D99%) and V100%. Variations as high as 3.1% with DECT were observed in D99% indicating target under-dosage. On average, use of SECT overestimated V100% by 2.4% when compared to DECT. Since all clinical plans were optimized robustly to meet V95% coverage, higher agreement (<1%) was achieved for V95% (99.9±0.2%), and D95% (99.6±0.3%). DECT relative to SECT indicated slightly higher OAR maximum doses for femoral heads (2.3±2.78%), penile bulb/external genital (1.33±4.00%) and large bowel (0.5±1.25%). Similarly, higher mean dose was observed to rectum (2.08±4.88%), bladder (1.41±0.25%), femoral heads (1.18±6.61%) and penile bulb/external genital (1.78±5.74%) for DECT relative to SECT.

CONCLUSION

Our results show a disparity between evaluated SECT and DECT target and OAR dosimetric parameters. Given the higher accuracies in proton range estimation associated with the use of DECT, its use can imply a potential for more conformal proton plans as well as higher TPS computed target coverage and OAR dose accuracy, both of which enhance overall treatment quality.

Validation of a CT-based motion model with in-situ fluoroscopy for lung surface deformation estimation

Many surrogate-based motion models (SMMs), proposed to guide motion management in radiotherapy, are constructed by correlating motion of an external surrogate and internal anatomy during CT-simulation. Changes in this correlation define model break down. We validate a methodology that incorporates fluoroscopic images (FL) acquired during treatment for SMM construction and update. Under a prospective IRB, 4DCT scans, VisionRT surfaces, and orthogonal FLs were collected from five lung cancer patients. VisionRT surfaces and two FL time-series were acquired pre- and post-treatment. A simulated annealing optimization scheme was used to estimate optimal lung deformations by maximizing the mutual information between digitally reconstructed radiographs (DRRs) of the SMM-estimated 3D images and FLs. Our SMM used partial-least-regression and was trained using the optimal deformations and VisionRT surfaces from the first breathing-cycle. SMM performance was evaluated using the mutual information score between reference FLs and the corresponding SMM or phase-assigned 4DCT DRRs. The Hausdorff distance for contoured landmarks was used to evaluate target position estimation error. For four out of five patients, two principal components approximated lung surface deformations with submillimeter accuracy. Analysis of the mutual information score between more than 4,000 pairs of FL and DRR demonstrated that our model led to more similarity between the FL and DRR images compared to 4DCT and DRR images from a model based on an a priori correlation model. Our SMM consistently displayed lower mean and 95^th percentile Hausdorff distances. For one patient, 95^th percentile Hausdorff distance was reduced by 11mm. Patient-averaged reductions in mean and 95^th percentile Hausdorff distances were 3.6mm and 7mm for right-lung, and 3.1mm and 4mm for left-lung targets. FL data were used to evaluate model performance and investigate the feasibility of model update. Despite variability in breathing, use of post-treatment FL preserved model fidelity and consistently outperformed 4DCT for position estimation.

Development and prospective in-patient proof-of-concept validation of a surface photogrammetry + CT-based volumetric motion model for lung radiotherapy

PURPOSE

We develop and validate a motion model that uses real-time surface photogrammetry acquired concurrently with four-dimensional computed tomography (4DCT) to estimate respiration-induced changes within the entire irradiated volume, over arbitrarily many respiratory cycles.

METHODS

A research, couch-mounted, VisionRT (VRT) system was used to acquire optical surface data (15 Hz, ROI = 15 × 20 cm² ) from the thoraco-abdominal surface of a consented lung SBRT patient, concurrently with their standard-of-care 4DCT. The end-exhalation phase from the 4DCT was regarded as reference and for each remaining phase, deformation vector fields (DVFs) with respect to the reference phase were computed. To reduce dimensionality, the first two principal components (PCs) of the matrix of nine DVFs were calculated. In parallel, ten phase-averaged VRT surfaces were created. Surface DVFs and corresponding PCs were computed. A principal least squares regression was used to relate the PCs of surface DVF to those of volume DVFs, establishing a relationship between time-varying surface and the underlying time-varying volume. Proof-of-concept validation was performed during each treatment fraction by concurrently acquiring 30 s time series of real-time surface data and "ground truth" kV fluoroscopic data (FL). A ray-tracing algorithm was used to create a digitally reconstructed fluorograph (DRF), and motion trajectories of high-contrast, soft-tissue, anatomical features in the DRF were compared with those from kV FL.

RESULTS

For five of the six fluoroscopic acquisition sessions, the model out-performed 4DCT in predicting contour Dice coefficient with respect to fluoroscopy-derived contours. Similarly, the model exhibited a marked improvement over 4DCT for patch positions on the diaphragm. Model patch position errors varied from 5 to -15 mm while 4DCT errors ranged between 5 and -22.4 mm. For one fluoroscopic acquisition, a marked change in the a priori internal-external correlation resulted in model errors comparable to those of 4DCT.

CONCLUSIONS

We described the development and a proof-of-concept validation for a volumetric motion model that uses surface photogrammetry to correlate the time-varying thoraco-abdominal surface to the time-varying internal thoraco-abdominal volume. These early results indicate that the proposed approach can result in a marked improvement over 4DCT. While limited by the duration of the fluoroscopic acquisitions as well as the resolution of the acquired images, the DRF-based proof-of-concept technique developed here is model-agnostic, and therefore, has the potential to be used as an in-patient validation tool for other volumetric motion models.