Yu, Nathan Y.

Cisplatin is the standard for the chemoradiation of squamous cell carcinoma of the head and neck (HNSCC). Many patients cannot receive cisplatin due to impaired renal function. This study investigated carboplatin as an alternative option. In total, 131 patients assigned to two courses of cisplatin (20 mg/m2/d1-–5 or 25 mg/m2/d1–4) were matched to 45 patients not suitable for cisplatin and receiving carboplatin (AUC 1.0/d1–5 or AUC 1.5/d1–4). The endpoints included loco-regional control (LRC), metastases-free survival (MFS), overall survival (OS), toxicities, and the completion of chemotherapy. The patients in the carboplatin group were significantly older and had more G3 tumors. Otherwise, the baseline characteristics were balanced. The LRC rates at 2 and 3 years were 77% and 76% in the cisplatin group vs. 69% and 65% in the carboplatin group (p = 0.21). The MFS rates were 83% and 78% vs. 78% and 74% (p = 0.34) and the OS rates 83% and 79% vs. 83% and 75% (p = 0.64), respectively. The outcomes were not significantly different in the subgroups receiving definitive or adjuvant chemoradiation. No significant differences were found regarding toxicities. Non-significantly more patients in the carboplatin group completed their chemotherapy (78% vs. 66%, p = 0.15). Carboplatin was associated with similar outcomes and toxicities as cisplatin, although these patients had worse renal function, more aggressive tumors, and were older. Given the limitations of this study, carboplatin appears an option for patients not suitable for cisplatin.

Many patients with squamous cell carcinoma of the head and neck (SCCHN) receive cisplatin-based chemoradiation. Cisplatin 100 mg/m2 every three weeks is toxic and alternative cisplatin regimens are desired. Two courses of 20 mg/m2/day 1–5 (cumulative 200 mg/m2) were shown to be similarly effective and better tolerated than 100 mg/m2 every three weeks. Previous studies suggested that cumulative doses >200 mg/m2 may further improve outcomes. In this study, 10 patients (group A) receiving two courses of 25 mg/m2/day 1–5 (cumulative 250 mg/m2) in 2022 were retrospectively matched and compared to 98 patients (group B) receiving two courses of 20 mg/m2/day 1–5 or 25 mg/m2/day 1–4 (cumulative 200 mg/m2). Follow-up was limited to 12 months to avoid bias. Group A achieved non-significantly better 12-month loco-regional control (100% vs. 83%, p = 0.27) and metastases-free survival (100% vs. 88%, p = 0.38), and similar overall survival (89% vs. 88%, p = 0.90). No significant differences were found regarding toxicities, completion of chemotherapy, and interruption of radiotherapy. Given the limitations of this study, chemoradiation with two courses of 25 mg/m2/day 1–5 appears an option for carefully selected patients as a personalized treatment approach. Longer follow-up and a larger sample size are needed to properly define its role.

AbstractBackgroundDeformable Image Registration (DIR) is an essential technique required in many applications of radiation oncology. However, conventional DIR approaches typically take several minutes to register one pair of 3D CT images and the resulting deformable vector fields (DVFs) are only specific to the pair of images used, making it less appealing for clinical application.PurposeA deep‐learning‐based DIR method using CT images is proposed for lung cancer patients to address the common drawbacks of the conventional DIR approaches and in turn can accelerate the speed of related applications, such as contour propagation, dose deformation, adaptive radiotherapy (ART), etc.MethodsA deep neural network based on VoxelMorph was developed to generate DVFs using CT images collected from 114 lung cancer patients. Two models were trained with the weighted mean absolute error (wMAE) loss and structural similarity index matrix (SSIM) loss (optional) (i.e., the MAE model and the M+S model). In total, 192 pairs of initial CT (iCT) and verification CT (vCT) were included as a training dataset and the other independent 10 pairs of CTs were included as a testing dataset. The vCTs usually were taken 2 weeks after the iCTs. The synthetic CTs (sCTs) were generated by warping the vCTs according to the DVFs generated by the pre‐trained model. The image quality of the synthetic CTs was evaluated by measuring the similarity between the iCTs and the sCTs generated by the proposed methods and the conventional DIR approaches, respectively. Per‐voxel absolute CT‐number‐difference volume histogram (CDVH) and MAE were used as the evaluation metrics. The time to generate the sCTs was also recorded and compared quantitatively. Contours were propagated using the derived DVFs and evaluated with SSIM. Forward dose calculations were done on the sCTs and the corresponding iCTs. Dose volume histograms (DVHs) were generated based on dose distributions on both iCTs and sCTs generated by two models, respectively. The clinically relevant DVH indices were derived for comparison. The resulted dose distributions were also compared using 3D Gamma analysis with thresholds of 3 mm/3%/10% and 2 mm/2%/10%, respectively.ResultsThe two models (wMAE and M+S) achieved a speed of 263.7±163 / 265.8±190 ms and a MAE of 13.15±3.8 / 17.52±5.8 HU for the testing dataset, respectively. The average SSIM scores of 0.987±0.006 and 0.988±0.004 were achieved by the two proposed models, respectively. For both models, CDVH of a typical patient showed that less than 5% of the voxels had a per‐voxel absolute CT‐number‐difference larger than 55 HU. The dose distribution calculated based on a typical sCT showed differences of ≤2cGy[RBE] for clinical target volume (CTV) D95 and D5, within ±0.06% for total lung V5, ≤1.5cGy[RBE] for heart and esophagus Dmean, and ≤6cGy[RBE] for cord Dmax compared to the dose distribution calculated based on the iCT. The good average 3D Gamma passing rates (> 96% for 3 mm/3%/10% and > 94% for 2 mm/2%/10%, respectively) were also observed.ConclusionA deep neural network‐based DIR approach was proposed and has been shown to be reasonably accurate and efficient to register the initial CTs and verification CTs in lung cancer.

AbstractBackgroundDeep learning auto‐segmentation (DLAS) models have been adopted in the clinic; however, they suffer from performance deterioration owing to the clinical practice variability. Some commercial DLAS software provide an incremental retraining function that enables users to train a custom model using their institutional data to account for clinical practice variability.PurposeThis study was performed to evaluate and implement the commercial DLAS software with the incremental retraining function for definitive treatment of patients with prostate cancer in a multi‐user environment.MethodsCT‐based target organs and organs‐at‐risk (OAR) delineation of 215 prostate cancer patients were utilized. The performance of three commercial DLAS software built‐in models was validated with 20 patients. A retrained custom model was developed using 100 patients and evaluated on the remaining data (n = 115). Dice similarity coefficient (DSC), Hausdorff distance (HD), mean surface distance (MSD), and surface DSC (SDSC) were utilized for quantitative evaluation. A multi‐rater qualitative evaluation was blindly performed with a five‐level scale. Visual inspection was performed in consensus and non‐consensus unacceptable cases to identify the failure modes.ResultsThree commercial DLAS vendor built‐in models achieved sub‐optimal performance in 20 patients. The retrained custom model had a mean DSC of 0.82 for prostate, 0.48 for seminal vesicles (SV), and 0.92 for rectum, respectively. This represents a significant improvement over the built‐in model with DSC of 0.73, 0.37, and 0.81 for the corresponding structures. Compared to the acceptance rate of 96.5% and consensus unacceptable rate (i.e., both reviewers rated as unacceptable) of 3.5% achieved by manual contours, the custom model achieved a 91.3% acceptance rate and 8.7% consensus unacceptable rate. The failure modes of retrained custom model were attributed to the following: cystogram (n = 2), hip prosthesis (n = 2), low dose rate brachytherapy seeds (n = 2), air in endorectal balloon(n = 1), non‐iodinated spacer (n = 2), and giant bladder(n = 1).ConclusionThe commercial DLAS software with the incremental retraining function was validated and clinically adopted for prostate patients in a multi‐user environment. AI‐based auto‐delineation of the prostate and OARs is shown to achieve improved physician acceptance, overall clinical utility, and accuracy.

12051 Background: The combination of ipilimumab and nivolumab (Ipi-Nivo) is a standard of care regimen in many malignancies. However, immune-related adverse events (irAE) are common and are of great concern, especially when treating the elderly population. This subgroup of patients may be at greater risk for serious irAEs and be less able to tolerate the potential treatment side effects. We sought to retrospectively evaluate our experience treating elderly patients ≥ 80 years with Ipi-Nivo to characterize adverse events. Methods: A retrospective chart review of the electronic medical records of all patients treated with Ipi-Nivo at the Mayo Clinic Health System was performed. Patients with any solid tumor who received their first dose of Ipi-Nivo at the age of ≥ 80 were included. Records were analyzed for baseline characteristics, cancer type, toxicity, and response to therapy. Differences between continuous and categorical variables were assessed using the students’ t-test and the chi-squared test, respectively. Overall survival (OS) was estimated using the Kaplan-Meier method. Cox proportional hazard models assessed the relative contribution of factors to survival after treatment. P values < 0.05 were considered statistically significant. All analyses were performed using SAS V.9.4. Results: Forty-six patients met inclusion criteria, 13 females and 33 males. Median age of first dose was 83 (Range: 80 - 94). Sixty-seven percent had an ECOG performance status (PS) 0-1 and 33% had an ECOG PS 2-3. Thirteen (28.3%) patients received 4 cycles of Ipi-Nivo. Cancers included: 18 (40%) melanomas, 10 (21%) mesothelioma, 9 (19.5%) lung cancers, and 9 (19.5%) other types. Thirty-one patients (67%) developed at least one irAE. Of the irAEs, 8 (17.4%) were grade 1, 20 (43.5%) were grade 2, 14 (30.4%) were grade 3, and 3 (6.5%) were grade 4. Systemic steroids were used in 29 (63%) patients. Twenty-six (56.5%) patients were hospitalized for any cause, and 12 (26.1%) were hospitalized due to an irAE. Of the 26 patients hospitalized during treatment, 19 (73%) died within 1 year of discharge; 11 (42%) died within < 1 month of discharge and 3 (12%) died within 1-3 months of discharge. Median OS from the date of first Ipi-Nivo dose was 14.6 months in the ECOG PS 0-1 and 6.5 months in the ECOG PS 2-3. ECOG PS of 0-1 was associated with a significantly decreased risk of mortality (HR [hazard ratio] 0.33, 95 % CI [confidence interval]: 0.15-0.70; p=0.0025) compared to ECOG PS of 2-3. Conclusions: This is the first analysis to evaluate the outcomes of Ipi-Nivo in patients ≥ 80 years. Approximately 60% of the patients required systemic steroids and a quarter were hospitalized with grade 3-4 irAEs. As expected, patients with ECOG PS 2-3 did significantly worse than ECOG PS 0-1. Ipi-Nivo should be used with caution in patients ≥ 80 years.

In Radiation Therapy Oncology Group 90-05, the maximum tolerated dose of single-fraction radiosurgery (SRS) for brain metastases of 21–30 mm was 18 Gy (biologically effective dose (BED) 45 Gy12). Since the patients in this study received prior brain irradiation, tolerable BED may be >45 Gy12 for de novo lesions. We investigated SRS and fractionated stereotactic radiotherapy (FSRT) with a higher BED for radiotherapy-naive lesions. Patients receiving SRS (19–20 Gy) and patients treated with FSRT (30–48 Gy in 3–12 fractions) with BED > 49 Gy12 for up to 4 brain metastases were compared for grade ≥ 2 radiation necrosis (RN). In the entire cohort (169 patients with 218 lesions), 1-year and 2-year RN rates were 8% after SRS vs. 2% and 13% after FSRT (p = 0.73) in per-patient analyses, and 7% after SRS vs. 7% and 10% after FSRT (p = 0.59) in per-lesion analyses. For lesions ≤ 20 mm (137 patients with 185 lesions), the RN rates were 4% (SRS) vs. 0% and 15%, respectively, (FSRT) (p = 0.60) in per-patient analyses, and 3% (SRS) vs. 0% and 11%, respectively, (FSRT) (p = 0.80) in per-lesion analyses. For lesions > 20 mm (32 patients with 33 lesions), the RN rates were 50% (SRS) vs. 9% (FSRT) (p = 0.012) in both per-patient and per-lesion analyses. In the SRS group, a lesion size > 20 mm was significantly associated with RN; in the FSRT group, lesion size had no impact on RN. Given the limitations of this study, FSRT with BED > 49 Gy12 was associated with low RN risk and may be safer than SRS for brain metastases > 20 mm.

A modern approach for brain metastases includes whole-brain radiotherapy plus simultaneous boost (WBRT+SIB). We developed a survival score in 128 patients treated with WBRT+SIB. Three models, each including three prognostic groups, were created. Positive predictive values (PPVs) for death ≤6 and survival ≥6 months were calculated. On multivariate analyses, performance score (KPS) and the number of brain metastases were significantly associated with survival. On univariate analyses, age showed a strong trend, and extra-cerebral cranial metastases a trend. In Model 1 (KPS, number of lesions), compared groups had 6-month survival rates of 15%, 38% and 57%. In Model 2 (KPS, lesions, age), rates were 17%, 33% and 75%, and in Model 3 (KPS, lesions, age, extra-cerebral metastases), 14%, 34% and 78%. PPVs for death ≤6 and survival ≥6 months were 85% and 57% (Model 1), 83% and 75% (Model 2), and 86% and 78% (Model 3). Thus, all models were accurate in predicting death ≤ 6 months; poor-prognosis patients may not benefit from SIB. Models 2 and 3 were superior in predicting survival ≥ 6 months. Given that Model 3 requires more data (including extensive staging), Model 2 is considered favorable for many patients. If extra-cerebral metastases are already known or extensive staging has been performed, Model 3 can also be used.

AbstractBackgroundThere is a knowledge gap regarding lobar versus sublobar resection for atypical carcinoid (AC) of the lung. As such, the authors sought to understand and analyze the outcomes of sublobar resection versus lobectomy in this patient population.MethodsA retrospective analysis using the National Cancer Database was performed to compare overall survival (OS) between patients treated with lobectomy and patients treated with sublobar resection for AC of the lung between the years 2004 and 2016. Patient characteristics were compared with χ2 tests. The Kaplan–Meier method was used to estimate OS distributions, and the log‐rank test was used to compare distributions by treatment strategy. A multivariable Cox regression model was used to assess associations between the treatment strategy and OS. A propensity score matching method was also implemented to further eliminate treatment selection bias in the study sample.ResultsThe database identified 669 patients with T1–T4 and N0–N3 lung ACs that were surgically resected. Unadjusted Kaplan–Meier survival curves did not demonstrate an OS difference between lobectomy and sublobar resection (p = .094). After propensity score matching, curves demonstrated a numerical improvement in OS with lobectomy; however, it was not statistically significant (p = .5). In a subgroup analysis, lobectomy and node‐negative disease were associated with the best OS, whereas sublobar resection and node‐positive disease were associated with the worst OS (p < .0001). Nodal involvement was associated with worse survival, regardless of surgical treatment (p < .0001).ConclusionsIn patients with T1–T4 and N0–N3 ACs of the lung, lobectomy was not associated with an improvement in OS in comparison with sublobar resection.

Purpose: Planning target volume (PTV) expansion for post-prostatectomy radiotherapy is typically ≥5 mm. Recent clinical trials have proved the feasibility of a reduced margin of 2–3 mm for treatments on MRI-linac. We aim to study the minimum PTV margin needed using iterative cone-beam CT (iCBCT) as image guidance on conventional linacs. Materials/Methods: Fourteen patients who received post-prostatectomy irradiation (8 with an endorectal balloon and 6 without a balloon) were included in this study. Treatment was delivered with volumetric modulated radiation therapy (VMAT). Fractional dose delivery was evaluated in 165 treatment fractions. The bladder, rectal wall, femoral heads, and prostate bed clinical tumor volume (CTV) were contoured and verified on daily iCBCT. PTV margins (0 mm, 2 mm, and 4 mm) were evaluated on daily iCBCT. CTV coverage and OAR dose parameters were assessed with each PTV margin. Results: CTV D100% was underdosed with a 0 mm margin in 32% of fractions in comparison with 2 mm (6%) and 4 mm (6%) PTV margin (p ≤ 0.001). CTV D95% > 95% was met in 93–94% fractions for all PTV expansions. CTV D95% > 95% was achieved in more patients with an endorectal balloon than those without: 0 mm—90/91 (99%) vs. 63/74 (85%); 2 mm—90/91 (99%) vs. 65/75 (87%); 4 mm—90/90 (100%) vs. 63/73 (86%). There was no difference in absolute median change in CTV D95% (0.32%) for 0-, 2-, and 4 mm margins. The maximum dose remained under 108% for 100% (0 mm), 97% (2 mm), and 98% (4 mm) of images. Rectal wall maximum dose remained under 108% for 100% (0 mm), 100% (2 mm), and 98% (4 mm) of images. Conclusions: With high-quality iCBCT image guidance, PTV margin accounting for inter-fractional uncertainties can be safely reduced for post-prostatectomy radiotherapy. For fractionated radiotherapy, an isotropic expansion of 2 mm and 4 mm may be considered for margin expansion with and without the endorectal balloon. Future application for margin reduction needs to be further evaluated and considered with the advent of shorter post-prostatectomy radiation courses.

Purpose: Post-operative prostate cancer patients are treated with full bladder instruction and the use of an endorectal balloon (ERB). We reassessed the efficacy of this practice based on daily image guidance and dose delivery using high-quality iterative reconstructed cone-beam CT (iCBCT). Methods: Fractional dose delivery was calculated on daily iCBCT for 314 fractions from 14 post-operative prostate patients (8 with and 6 without ERB) treated with volumetric modulated radiotherapy (VMAT). All patients were positioned using novel iCBCT during image guidance. The bladder, rectal wall, femoral heads, and prostate bed clinical tumor volume (CTV) were contoured and verified on daily iCBCT. The dose-volume parameters of the contoured organs at risk (OAR) and CTV coverage were assessed for the clinical impact of daily bladder volume variations and the use of ERB. Minimum bladder volume was studied, and a straightforward bladder instruction was explored for easy clinical adoption. Results: A “minimum bladder” contour, the overlap between the original bladder contour and a 15 mm anterior and superior expansion from prostate bed PTV, was confirmed to be effective in identifying cases that might fail a bladder constraint of V65% <60%. The average difference between the maximum and minimum bladder volumes for each patient was 277.1 mL. The daily bladder volumes varied from 62.4 to 590.7 mL and ranged from 29 to 286% of the corresponding planning bladder volume. The bladder constraint of V65% <60% was met in almost all fractions (98%). CTVs (D90%, D95%, and D98%) remained well-covered regardless of the absolute bladder volume daily variation or the presence of the endorectal balloon. Patients with an endorectal balloon showed smaller variation but a higher average maximum rectal wall dose (D0.03mL: 104.3% of the prescription) compared to patients without (103.3%). Conclusions: A “minimum bladder” contour was determined that can be easily generated and followed to ensure sufficient bladder sparing. Further analysis and validation are needed to confirm the utility of the minimal bladder contour. Accurate dose delivery can be achieved for prostate bed target coverage and OAR sparing with or without the use of ERB.