Radiotherapy vs. Cystectomy for Treatment of Muscle Invasive Bladder Cancer in Very Elderly Patients

PURPOSE/OBJECTIVE(S)

Radical cystectomy (RC) has long remained the principal treatment of muscle invasive bladder cancer (MIBC). It is, however, associated with significant morbidity, long recovery, and reported worse overall and cancer specific survival, particularly for the very elderly (age > = 80). Bladder preservation with transurethral resection of bladder tumor (TURBT) followed by radiotherapy (RT) +/- concurrent chemotherapy (ChT) is regarded as a curative-intent alternative to RC in well-selected patients. The optimal treatment strategy remains unclear in very elderly patients. We hypothesize that outcomes following RT vs RC are clinically equivalent for treatment of MIBC in very elderly patients.

MATERIALS/METHODS

Patients > = 80 years old with T2-T4 N0-N1 bladder cancer treated definitively with RT versus RC were included. Exclusion criteria included history of pelvic RT, prior cystectomy, or palliative treatment intent. Clinicopathologic and treatment-related details, as well as clinical outcomes and toxicities were retrospectively abstracted. Kaplan-Meier analyses were performed.

RESULTS

At a median follow-up of 17 months (range 0.25-190), 47 patients received RT vs 83 patients who underwent RC with median age of 86 years (80-97) vs 83 years (range 80-91) (p<0.01), respectively. Median Charlson Comorbidity Index was similar between groups (p = 0.35) with median 7 for both cohorts, predicting 0% estimated 10y survival. Most patients had cT2 tumors (91% vs 99%, p = 0.06), cN0 nodal status (96% vs 100%, p = 0.06), and urothelial carcinoma histology (79% vs 90%, p = 0.22). Most RT patients received concurrent ChT (90%) and a minority of RC patients received neoadjuvant ChT (16%). 70% of RT pts had complete TURBTs prior to RT. Common RT regimens were 50-55 Gy in 20-25 fractions or 60-64.8 Gy in 30-36 fractions, using IMRT (89%) or 3D conformal (11%) technique. Overall survival for RT vs RC at 1- and 2- years was 79% vs 85% and 57% and 69%, respectively (p = 0.20). Locoregional control at 1- and 2-years was 73% vs 70% and 63% vs 66% (p = 0.59), respectively. Progression free survival at 1- and 2-years was 69% vs 66% and 52% vs 54% (p = 0.75), respectively. No RT patients went on to receive salvage cystectomy. Treatment complications are listed in Table 1; the Clavien Dindo classification system was used to describe acute surgical complications of RC and the Common Terminology Criteria for Adverse Events (CTCAE) Dictionary v5.0 was used for acute and late toxicity of RT.

CONCLUSION

In the very elderly, RT (with or without concurrent ChT) offers survival and locoregional control rates comparable to RC, with a favorable side effect profile. RT should be offered for definitive management of non-metastatic MIBC as an alternative to RC in selected, well- informed, and compliant very elderly patients.

A Pilot Study of an Interactive Virtual Tour Tool for Patient Education Prior to Undergoing High-Dose Rate Brachytherapy for Prostate Cancer

PURPOSE/OBJECTIVE(S)

High-dose rate (HDR) brachytherapy for treatment of prostate cancer is an invasive procedure that can be associated with patient anxiety. Patient education regarding the procedure can allow for better informed decision-making while also decreasing anxiety. We sought to develop and assess the utility of an interactive virtual tour tool that portrays a 360-degree view of the HDR brachytherapy patient experience, with the goals of providing patient education, decreasing patient anxiety, and assisting in wayfinding on the procedure day.

MATERIALS/METHODS

Using a 360-degree camera, we captured multiple photographs that depicted the various hospital locations that a patient would navigate through on the day of their HDR brachytherapy procedure, including the medical center lobby, pre-operative/post-operative units, and the brachytherapy suite. We then compiled these 360-degree photographs using virtual tour software, to allow users to navigate throughout the locations. We added informational text, spoken audio, and videos associated with key staff, objects, and the brachytherapy procedure that allow the users to interact with and learn about these various components within the virtual tour. This tool was accessible via a website link on a computer, tablet, or smartphone and was provided at the time of consult to patients who were planning to undergo HDR brachytherapy for prostate cancer. A questionnaire assessing the tool's ease of use, educational value, wayfinding utility, and ability to improve anxiety and treatment decision-making was conducted prior to and after their procedure.

RESULTS

Preliminary feedback from healthy volunteers is highly positive, with users finding that the tool is easily accessible, user-friendly, improves understanding of HDR brachytherapy, simulates the treatment experience accurately, helps with wayfinding, and has the potential to decrease patient anxiety and increase comfort with the treatment decision. Data from the patient questionnaires are being collected and will be analyzed.

CONCLUSION

A 360-degree virtual tour tool allows for an easily accessible, immersive, and interactive method of patient education on an invasive, anxiety-associated procedure. This has the potential to decrease patient anxiety and improve comfort regarding treatment decision-making. This tool may be applied toward other relatively involved radiotherapy modalities, including gynecologic HDR brachytherapy, respiratory-gated treatments, and CyberKnife stereotactic radiosurgery.

Clinical Implementation of an Automated IMRT/VMAT Treatment Planning Tool

PURPOSE/OBJECTIVE(S)

To create an in-house automated treatment planning tool for IMRT/VMAT treatments and evaluate the dosimetric plan quality against manually generated plans.

MATERIALS/METHODS

A scripting application programming interface is employed to interact with a commercial treatment planning system (TPS) to implement automatic plan evaluation and update optimization parameters by mimicking the human planning process. The automated planning performs in an iterative fashion until reaching an acceptable tradeoff among target coverage/dose homogeneity and sparing of critical organs at risk. In each iteration, the dose constraints, priorities, and optimization structures for are automatically updated based on the results of the current iteration. Twenty previously treated plans (10 prostate and 10 head and neck), were preliminarily used to evaluate the performance of the automated planning tool. The differences in target and organ-at-risk metrics from the manually generated clinical plans were analyzed using paired t-test to evaluate clinical acceptability of tour automated planning tool. The current in-house-developed automated planning solution is able to create plans for different disease sites, including head & neck, prostate, pelvis, and lung. So far, the VMAT plans for more than 150 different cases have been generated with the tool. The results for these were also evaluated.

RESULTS

Compared to the manually generated clinical head and neck plans, all auto plans achieved PTV D95% coverage and critical organs at risk sparing without statistically significant change in average global Dmax (107.4% for manual vs 107.3% for automated plans). The auto-planning solution provided reduced maximum doses to brainstem and spinal cord (average reductions with standard deviations of 5.1 ± 2.6 Gy and 2.9 ± 1.4 Gy, respectively, all p <0.03), reduced average mean doses to contralateral parotid, ipsilateral parotid, contralateral submandibular gland, pharynx, esophagus, cochleae (reductions of 2.2 ± 2.9 Gy, 4.8 ± 4.7 Gy, 3.6 ± 5.2 Gy, 2.0 ± 7.1 Gy, 3.9 ± 2.6 Gy, 3.8 ± 5.0 Gy, respectively, all p < 0.045). Similar results were observed for the prostate plans. With the same PTV coverage and without statistically significant change in average global Dmax (106.5% for manual vs 106.8% for automated plans), the automated solution provided superior sparing for both bladder and rectum. Bladder V75, V70, V65 were reduced by 0.6% ± 2.1%, 0.8% ± 2.5%, and 0.9% ± 2.9% (all p <0.04), respectively. Rectum V75, V70, V65, V60 were reduced by 1.0% ± 2.3%, 1.2% ± 2.8%, 1.3% ± 3.2%, 1.6% ± 3.6% (all p < 0.01), respectively.

CONCLUSION

Our automated treatment planning solution is capable of efficiently generating VMAT plans for different disease sites with superior dosimetric indices compared to manually generated plans. Our tool is integrated within a commercial TPS platform, so it has the advantage of seamless adoption into the standard workflow to improve plan quality and treatment planning efficiency in our clinic.

Patient-Adaptive Automated Segmentation in Daily kVCT Images for Radiotherapy of Head and Neck and Prostate Cancer

PURPOSE/OBJECTIVE(S)

The purpose of this study was to examine the use of transfer learning in deep learning-based auto-segmentation of daily kilovoltage computed tomography (kVCT) images for patient-specific adaptive radiotherapy. Using data from the first cohort of patients treated with the innovative BgRT system, the objective of this study was to evaluate the potential benefits of this approach in facilitating efficient and effective adaptive radiotherapy.

MATERIALS/METHODS

For the head and neck (HaN) site and pelvic site, we first trained a deep convolutional segmentation network using a population dataset, consisting of 67 and 56 patient cases, respectively. This population network was then fine-tuned for a specific patient using a transfer learning approach, adapting the network weights. The auto-segmentation network utilized in this study was a 23-layer U-Net with batch normalization, a dropout rate of 0.5, and four skip connections between the encoder and decoder at different levels. We used initial planning CT and 5-26 sets of daily kVCT scans with a total of 8,039 images for patient-specific learning in the 6 HaN cases and 4 pelvic cases, particularly analyzing the relationship between the number of sequential patient-specific training data and the performance of the auto-segmentation. We compared the performance of the patient-specific network with the population network and the clinical rigid registration method, using the Dice similarity coefficient (DSC) as the evaluation metric. Additionally, we investigated the corresponding dosimetric impacts of the different auto-segmentation and registration methods.

RESULTS

The patient-specific network showed improved mean DSC scores of 0.88 and 0.90 for three HaN organs at risk (OARs) and eight pelvic targets and OARs, respectively, compared to the population network (0.70 and 0.63) and the registration method (0.72 and 0.72). The DSC of the patient-specific network steadily improved as the number of longitudinal training cases increased, reaching near saturation after 6 training cases. The use of the patient-specific auto-segmentation resulted in a reduction of the mean discrepancy in target and OAR doses between delivery and planning from 5.5% with the clinical rigid registration to 1.1%.

CONCLUSION

The use of patient-specific transfer learning in auto-segmenting kVCT images showed higher accuracy compared to a conventional population network and clinical registration-based method. This approach holds promise for enhancing dose evaluation accuracy in adaptive radiotherapy.