Linac- and CyberKnife-based MRI-only treatment planning of prostate SBRT using an optimized synthetic CT calibration curve

PURPOSE

CT Hounsfield Units (HUs) are converted to electron density using a calibration curve obtained from physical measurements of an electron density phantom. HU values assigned to an MRI-derived synthetic computed tomography (sCT) may present a different relationship with electron density compared to CT HU. Correct assignment of sCT HU values is critical for accurate dose calculation and delivery. The goals of this work were to develop a sCT calibration curve using patient data acquired on a clinically commissioned CT scanner and assess for CyberKnife- and volumetric modulated arc therapy (VMAT)-based MR-only treatment planning of prostate SBRT.

METHODS

Same-day CT and MRI simulation in the treatment position were performed on 10 patients treated with SBRT to the prostate. Dixon in-phase and out-of-phase MRIs were acquired on a 3T scanner using a 3D T1-weighted gradient-echo sequence to generate sCTs using a commercial sCT algorithm. CT and sCT datasets were co-registered and HU values compared using mean absolute error (MAE). An optimized HU-to-density calibration curve was created based on average HU values across an institutional patient database for each of the four sCT tissue types. Clinical CyberKnife and VMAT treatment plans were generated on each patient CT and recomputed onto corresponding sCTs. Dose distributions computed using CT and sCT were compared using gamma criteria and dose-volume-histograms.

RESULTS

For the optimized calibration curve, HU values were -96, 37, 204, and 1170 and relative electron densities were 0.95, 1.04, 1.1, and 1.7 for adipose, soft tissue, inner bone, and outer bone, respectively. The proposed sCT protocol produced total MAE of 94 ± 20HU. Gamma values mean ± std (min-max) were 98.9% ± 0.9% (97.1%-100%) and 97.7% ± 1.3% (95.3%-99.3%) for VMAT and CyberKnife plans, respectively.

CONCLUSION

MRI-derived sCT using the proposed approach shows excellent dosimetric agreement with conventional CT simulation, demonstrating the feasibility of MRI-derived sCT for prostate SBRT treatment planning.

Incidental findings and safety events from magnetic resonance imaging simulation for head and neck radiation treatment planning: A single institution experience

Purpose

Having dedicated MRI scanners within radiation oncology departments may present unexpected challenges since radiation oncologists and radiation therapists are generally not trained in this modality and there are potential patient safety concerns. This study retrospectively reviews the incidental findings and safety events that were observed at a single institution during introduction of MRI sim for head and neck radiotherapy planning.

Methods

Consecutive patients from March 1, 2020, to May 31, 2022, who were scheduled for MRI sim after having completed CT simulation for head and neck radiotherapy were included for analysis. Patients first underwent a CT simulation with a thermoplastic mask and in most cases with an intraoral stent. The same setup was then reproduced in the MRI simulator. Safety events were instances where scheduled MRI sims were not completed due to the MRI technologist identifying MRI-incompatible devices or objects at the time of sim. Incidental findings were identified during weekly quality assurance rounds as a joint enterprise of head and neck radiation oncology and neuroradiology. Categorical variables between completed and not completed MRI sims were compared using the Chi-Square test and continuous variables were compared using the Mann-Whitney U test with a p-value of < 0.05 considered to be statistically significant.

Results

148 of 169 MRI sims (88 %) were completed as scheduled and 21 (12 %) were not completed (Table 1). Among the 21 aborted MRI sims, the most common reason was due to safety events flagged by the MRI technologist (n = 8, 38 %) because of the presence of metal or a medical device that was not noted at the time of initial screening by the administrative coordinator. Patients who did not complete MRI sim were more likely to be treated for non-squamous head and neck primary tumor (p = 0.016) and were being treated post-operatively (p < 0.001). CT and MRI sim scans each had 17 incidental findings. CT simulation detected 3 cases of new metastases in lungs, which were outside the scan parameters of MRI sim. MRI sim detected one case of dural venous thrombosis and one case of cervical spine epidural abscess, which were not detected by CT simulation.

Conclusions

Radiation oncology departments with dedicated MRI simulation scanners would benefit from diagnostic radiology review for incidental findings and having therapists with MRI safety credentialing to catch near-miss events.

Adrenocortical hemorrhage following intravenous tetracosactide in a dog with hypercortisolism

OBJECTIVE

To summarize findings from a case of adrenocortical hemorrhage following tetracosactide injection during ACTH stimulation testing for monitoring of trilostane therapy in a dog.

ANIMAL

A 12-year old neutered male dog with adrenal-dependent hypercortisolism.

CLINICAL PRESENTATION, PROGRESSION, AND PROCEDURES

4 hours after ACTH stimulation testing, the patient developed vomiting, lethargy, and abdominal pain. Abdominal ultrasound was performed before and after an ACTH stimulation test. Following ACTH stimulation testing, there was progressive bilateral adrenal enlargement and free abdominal fluid had developed. This was considered to be caused by adrenocortical inflammation and hemorrhage secondary to the synthetic ACTH analog, tetracosactide, used during stimulation testing. A resting cortisol performed 5 hours after tetracosactide injection was not consistent with iatrogenic hypoadrenocorticism.

TREATMENT AND OUTCOME

The patient was managed with analgesia, IV fluids, and corticosteroids and made a full recovery.

CLINICAL RELEVANCE

To the authors' knowledge, this was the first reported case of adrenocortical hemorrhage following administration of a synthetic ACTH analog in a dog. This should be considered as a rare potential complication of ACTH stimulation testing.

Stereotactic Magnetic Resonance-guided Adaptive Radiation Therapy for Localized Kidney Cancer: Early Outcomes from a Prospective Phase 1 Trial and Supplemental Cohort

Stereotactic magnetic resonance (MR)-guided adaptive radiotherapy (SMART) for renal cell carcinoma may result in more precise treatment delivery through the capabilities for improved image quality, daily adaptive planning, and accounting for respiratory motion during treatment with real-time MR tracking. In this study, we aimed to characterize the safety and feasibility of SMART for localized kidney cancer. Twenty patients with localized kidney cancer (ten treated in a prospective phase 1 trial and ten in the supplemental cohort) were treated to 40 Gy in five fractions on a 0.35 T MR-guided linear accelerator with daily adaptive planning and a cine MR-guided inspiratory breath hold technique. The median follow-up time was 17 mo (interquartile range: 13-20 months). A single patient developed local failure at 30 mo. No grade ≥3 adverse events were reported. The mean decrease in estimated glomerular filtration rate was -1.8 ml/min/1.73 m2 (95% confidence interval or CI [-6.6 to 3.1 ml/min/1.73 m2]), and the mean decrease in tumor diameter was -0.20 cm (95% CI [-0.6 to 0.2 cm]) at the last follow-up. Anterior location and overlap of the 25 or 28 Gy isodose line with gastrointestinal organs at risk were predictive of the benefit from online adaptive planning. Kidney SMART is feasible and, at the early time point evaluated in this study, was well tolerated with minimal decline in renal function. More studies are warranted to further evaluate the safety and efficacy of this technique. PATIENT SUMMARY: For patients with localized renal cell carcinoma who are not surgical candidates, stereotactic magnetic resonance--guided adaptive radiotherapy is a feasible and safe noninvasive treatment option that results in minimal impact on kidney function.

Evaluating the Hounsfield unit assignment and dose differences between CT-based standard and deep learning-based synthetic CT images for MRI-only radiation therapy of the head and neck

BACKGROUND

Magnetic resonance image only (MRI-only) simulation for head and neck (H&N) radiotherapy (RT) could allow for single-image modality planning with excellent soft tissue contrast. In the MRI-only simulation workflow, synthetic computed tomography (sCT) is generated from MRI to provide electron density information for dose calculation. Bone/air regions produce little MRI signal which could lead to electron density misclassification in sCT. Establishing the dosimetric impact of this error could inform quality assurance (QA) procedures using MRI-only RT planning or compensatory methods for accurate dosimetric calculation.

PURPOSE

The aim of this study was to investigate if Hounsfield unit (HU) voxel misassignments from sCT images result in dosimetric errors in clinical treatment plans.

METHODS

Fourteen H&N cancer patients undergoing same-day CT and 3T MRI simulation were retrospectively identified. MRI was deformed to the CT using multimodal deformable image registration. sCTs were generated from T1w DIXON MRIs using a commercially available deep learning-based generator (MRIplanner, Spectronic Medical AB, Helsingborg, Sweden). Tissue voxel assignment was quantified by creating a CT-derived HU threshold contour. CT/sCT HU differences for anatomical/target contours and tissue classification regions including air (<250 HU), adipose tissue (-250 HU to -51 HU), soft tissue (-50 HU to 199 HU), spongy (200 HU to 499 HU) and cortical bone (>500 HU) were quantified. t-test was used to determine if sCT/CT HU differences were significant. The frequency of structures that had a HU difference > 80 HU (the CT window-width setting for intra-cranial structures) was computed to establish structure classification accuracy. Clinical intensity modulated radiation therapy (IMRT) treatment plans created on CT were retrospectively recalculated on sCT images and compared using the gamma metric.

RESULTS

The mean ratio of sCT HUs relative to CT for air, adipose tissue, soft tissue, spongy and cortical bone were 1.7 ± 0.3, 1.1 ± 0.1, 1.0 ± 0.1, 0.9 ± 0.1 and 0.8 ± 0.1 (value of 1 indicates perfect agreement). T-tests (significance set at t = 0.05) identified differences in HU values for air, spongy and cortical bone in sCT images compared to CT. The structures with sCT/CT HU differences > 80 HU of note were the left and right (L/R) cochlea and mandible (>79% of the tested cohort), the oral cavity (for 57% of the tested cohort), the epiglottis (for 43% of the tested cohort) and the L/R TM joints (occurring > 29% of the cohort). In the case of the cochlea and TM joints, these structures contain dense bone/air interfaces. In the case of the oral cavity and mandible, these structures suffer the additional challenge of being positionally altered in CT versus MRI simulation (due to a non-MR safe immobilizing bite block requiring absence of bite block in MR). Finally, the epiglottis HU assignment suffers from its small size and unstable positionality. Plans recalculated on sCT yielded global/local gamma pass rates of 95.5% ± 2% (3 mm, 3%) and 92.7% ± 2.1% (2 mm, 2%). The largest mean differences in D95, Dmean , D50 dose volume histogram (DVH) metrics for organ-at-risk (OAR) and planning tumor volumes (PTVs) were 2.3% ± 3.0% and 0.7% ± 1.9% respectively.

CONCLUSIONS

In this cohort, HU differences of CT and sCT were observed but did not translate into a reduction in gamma pass rates or differences in average PTV/OAR dose metrics greater than 3%. For sites such as the H&N where there are many tissue interfaces we did not observe large scale dose deviations but further studies using larger retrospective cohorts are merited to establish the variation in sCT dosimetric accuracy which could help to inform QA limits on clinical sCT usage.

Widening the therapeutic window for central and ultra-central thoracic oligometastatic disease with stereotactic MR-guided adaptive radiation therapy (SMART)

BACKGROUND/PURPOSE

Central/ultra-central thoracic tumors are challenging to treat with stereotactic radiotherapy due potential high-grade toxicity. Stereotactic MR-guided adaptive radiation therapy (SMART) may improve the therapeutic window through motion control with breath-hold gating and real-time MR-imaging as well as the option for daily online adaptive replanning to account for changes in target and/or organ-at-risk (OAR) location.

MATERIALS/METHODS

26 central (19 ultra-central) thoracic oligoprogressive/oligometastatic tumors treated with isotoxic (OAR constraints-driven) 5-fraction SMART (median 50 Gy, range 35-60) between 10/2019-10/2022 were reviewed. Central tumor was defined as tumor within or touching 2 cm around proximal tracheobronchial tree (PBT) or adjacent to mediastinal/pericardial pleura. Ultra-central was defined as tumor abutting the PBT, esophagus, or great vessel. Hard OAR constraints observed were ≤ 0.03 cc for PBT V40, great vessel V52.5, and esophagus V35. Local failure was defined as tumor progression/recurrence within the planning target volume.

RESULTS

Tumor abutted the PBT in 31 %, esophagus in 31 %, great vessel in 65 %, and heart in 42 % of cases. 96 % of fractions were treated with reoptimized plan, necessary to meet OAR constraints (80 %) and/or target coverage (20 %). Median follow-up was 19 months (27 months among surviving patients). Local control (LC) was 96 % at 1-year and 90 % at 2-years (total 2/26 local failure). 23 % had G2 acute toxicities (esophagitis, dysphagia, anorexia, nausea) and one (4 %) had G3 acute radiation dermatitis. There were no G4-5 acute toxicities. There was no symptomatic pneumonitis and no G2 + late toxicities.

CONCLUSION

Isotoxic 5-fraction SMART resulted in high rates of LC and minimal toxicity. This approach may widen the therapeutic window for high-risk oligoprogressive/oligometastatic thoracic tumors.

Association of Parental Status and Gender With Burden of Multidisciplinary Tumor Boards Among Oncology Physicians

Importance

Tumor boards are integral to the care of patients with cancer. However, data investigating the burden of tumor boards on physicians are limited.

Objective

To investigate what physician-related and tumor board-related factors are associated with higher tumor board burden among oncology physicians.

Design, Setting, and Participants

Tumor board burden was assessed by a cross-sectional convenience survey posted on social media and by email to Cedars-Sinai Medical Center cancer physicians between March 3 and April 3, 2022. Tumor board start times were independently collected by email from 22 top cancer centers.

Main Outcomes and Measures

Tumor board burden was measured on a 4-point scale (1, not at all burdensome; 2, slightly burdensome; 3, moderately burdensome; and 4, very burdensome). Univariable and multivariable probabilistic index (PI) models were performed.

Results

Surveys were completed by 111 physicians (median age, 42 years [IQR, 36-50 years]; 58 women [52.3%]; 60 non-Hispanic White [54.1%]). On multivariable analysis, factors associated with higher probability of tumor board burden included radiology or pathology specialty (PI, 0.68; 95% CI, 0.54-0.79; P = .02), attending 3 or more hours per week of tumor boards (PI, 0.68; 95% CI, 0.58-0.76; P < .001), and having 2 or more children (PI, 0.65; 95% CI, 0.52-0.77; P = .03). Early or late tumor boards (before 8 am or at 5 pm or after) were considered very burdensome by 33 respondents (29.7%). Parents frequently reported a negative burden on childcare (43 of 77 [55.8%]) and family dynamics (49 of 77 [63.6%]). On multivariable analysis, a higher level of burden from early or late tumor boards was independently associated with identifying as a woman (PI, 0.69; 95% CI, 0.57-0.78; P = .003) and having children (PI, 0.75; 95% CI, 0.62-0.84; P < .001). Independent assessment of 358 tumor boards from 22 institutions revealed the most common start time was before 8 am (88 [24.6%]).

Conclusions and Relevance

This survey study of tumor board burden suggests that identifying as a woman or parent was independently associated with a higher level of burden from early or late tumor boards. The burden of early or late tumor boards on childcare and family dynamics was commonly reported by parents. Having 2 or more children, attending 3 or more hours per week of tumor boards, and radiology or pathology specialty were associated with a significantly higher tumor board burden overall. Future strategies should aim to decrease the disparate burden on parents and women.

Quantifying the Dosimetric Impact of Tissue Hounsfield Unit Assignment in Deep Learning-based Synthetic CT Images For MRI-Only Radiation Therapy of The Head and Neck

PURPOSE/OBJECTIVE(S)

MRI-only simulation for head and neck (HN) radiotherapy (RT) could allow for single-image modality planning with excellent soft tissue contrast. In the MRI-only simulation workflow, synthetic CTs (sCTs) are generated from MRI to provide electron density information for dose calculation. Bone/air regions produce little MRI signal which could lead to electron density misclassification in sCTs. Establishing the dosimetric impact of this error could inform quality assurance (QA) procedures using MRI-only RT planning. In this study we quantify differences in Hounsfield Unit (HU) values between paired CT/ sCTs of HN cancer patients and investigate the dosimetric impact on clinical treatment plans.

MATERIALS/METHODS

Fourteen patients with head and neck cancer undergoing same-day CT and 3T MRI simulation were retrospectively identified. MRIs were deformed to the CT using multimodal deformable image registration. SCTs were generated from T1w DIXON MRI using a commercially available deep learning-based generator (MRIplanner, Spectronics). Tissue voxel assignment was quantified by creating a CT-derived HU threshold contour. CT/sCT HU differences for anatomical/target contours and tissue classification regions including air (<-250HU), adipose tissue (-250HU to -51HU), soft tissue (-50HU to 199HU), spongy (200HU to 499HU) and cortical bone (> 500HU) were quantified. T-test was used to determine if sCT/CT HU differences were significant. The frequency of structures that had a HU difference >70HU (the CT window-width setting for intra-cranial structures) was computed to establish structure classification accuracy. Clinical IMRT treatment plans created on CTs were retrospectively recalculated on sCT images using compared using the gamma metric.

RESULTS

The mean ratio of sCT HUs relative to CT for air, adipose tissue, soft tissue, spongy and cortical bone were 1.7±0.3, 1.1±0.1, 1.0±0.1, 0.9±0.1 and 0.8±0.1 (value of 1 indicates perfect agreement). T-tests (significance set at t = 0.05) identified differences in HU values for air, spongy and cortical bone in sCT images compared to CT. The structures with sCT/CT HU differences > 70HU were the L/R cochlea and mandible, occurring in >78% of the tested cohort. These structures contain dense bone/air interfaces. Plans recalculated on sCTs yielded global/local gamma pass rates of 98.7%±1.2% (3mm,3%) and 95.5%±2.5% (1mm,1%). Mean differences in D95, D50, D10 and D2 dose volume histogram (DVH) metrics for organ-at-risk (OAR) and planning tumor volumes (PTV) were 0.8%±1.5% and 2.1% ± 1.2% respectively.

CONCLUSION

In this cohort, HU differences in sCTs were observed but did not translate into a reduction in gamma pass rates and OAR/PTV DVH metrics. The acquisition of additional training data such as ultrashort echo time MRI could improve bone/air contrast and reduce bone/air sCT misclassifications. Further studies will establish the variation in sCT dosimetric accuracy using a larger retrospective cohort to inform QA limits on clinical sCT usage.

Association of Parental Status and Gender with Burden of Multidisciplinary Tumor Boards

PURPOSE/OBJECTIVE(S)

Tumor boards are an integral part of the management of patients with cancer. However, there is limited data investigating the burden of tumor boards on physicians. Our objective was to determine what physician-related, and tumor board-related factors associate with higher burden.

MATERIALS/METHODS

Tumor board start times were collected by email from 22 National Cancer Institute-designated cancer centers and/or U.S. World and News Report Top 40 hospitals for cancer. Tumor board burden was assessed by a cross-sectional convenience survey posted on social media and by email to Cedars-Sinai Medical Center cancer physicians between March 3, 2022, and April 3, 2022. Tumor board burden was measured on a 4-point scale (1, not at all; 2, slightly; 3, moderately; 4, very burdensome). Univariable and multivariable analyses were performed using a probabilistic index model.

RESULTS

The timing of 392 tumor boards was collected from 22 institutions. The most common tumor board start time was at or before 0730 (24.6%). Surveys were completed by 111 physicians, of which 52.3% identified as women and 42.3% as men. Reported specialties were radiation oncology (39.6%), medical oncology (18.0%), surgery (15.3%), radiology (12.6%), and pathology (9.9%). On average, 41.4% attended ≥3 hours/week total of tumor boards and 1-2 hours/week of early/late tumor boards (defined as starting before 0800 or 1700 or after). Overall, 37.8% reported tumor boards were at least moderately burdensome. On multivariable analysis, radiology/pathology specialty (probability 0.68; 95% confidence interval [CI], 0.54-0.79; p = 0.015), attending ≥3 hours/week of tumor boards (probability 0.68; 95% CI, 0.58-0.76; p<.001), and having ≥2 children (probability 0.65; 95% CI, 0.52-0.77; p = 0.029), were associated with higher burden. Early/late tumor boards were frequently considered burdensome (20.7% moderately, 29.7% very burdensome). On multivariable analysis, identifying as a woman (probability 0.69; 95% CI, 0.57-0.78; p = 0.003) and having children (probability 0.75; 95% CI, 0.62-0.84; p<.001) remained associated with a higher level of burden from early/late tumor boards. Further, parents frequently reported that early/late tumor boards negatively affected childcare (55.8%), feeding and/or sleep logistics (33.8%), and overall family dynamics (63.7%).

CONCLUSION

Identifying as a woman and having children were associated with a higher level of burden from early/late tumor boards. The negative impact of early/late tumor boards on overall family dynamics, including children feeding, sleeping, and childcare logistics, was commonly reported by parents. Having ≥2 children, attending ≥3 hours/week of tumor boards, and radiology/pathology specialty were associated with a higher level of burden overall. Future strategies should aim to decrease burden, particularly the disparate impact on parents and women.

Impact of Workflow and Educational Interventions on MR Safety in Radiation Oncology

PURPOSE/OBJECTIVE(S)

Magnetic resonance imaging (MRI) is becoming increasingly integrated into radiation oncology (RO) departments with the use of MRI-Linacs and MRI simulation. Due to the number of implants in patients with cancer, adoption of comprehensive patient screening and MR safety workflows in RO is critical. Identifying MR unsafe implants only at the time of MRI simulation leads to same-day cancellations, potentially delaying treatment, and can risk MR safety events (SEs). This quality improvement study evaluated the impact of workflow and educational interventions on MR safety in RO at a single institution.

MATERIALS/METHODS

In an effort to decrease same-day cancellations and improve safety surrounding use of a 3 Tesla MRI simulator at an academic center, three plan-see-do-act (PDSA) cycles were implemented from 4/18/22 - 1/19/23. MR safety oversight for the simulator was provided by a multidisciplinary team, with input from both radiology and RO. PDSA cycle 1 implemented a two-screen functional workflow, adapted from radiology at the same institution. The first screen is completed by the practice coordinator (PC) at the time of scheduling to triage high-risk patients into a work queue (WQ) for further evaluation by the MR safety team. The second screen is performed by the MR technologist (MRT) at the point of care. PDSA cycle 2 involved education for PCs. PDSA cycle 3 was a second PC educational intervention including a visual aide to assist with WQ use. Efficacy was determined by the number of same-day cancellations, patients in the WQ (a measure of the number of patients identified at the initial screen as having an implant), and SEs in each PDSA cycle.

RESULTS

PDSA cycle 1 spanned 56 workdays during which 91 MR simulations were scheduled with 6 cancellations (6.5%). PDSA cycle 2 spanned 84 days during which 173 MR simulations were scheduled with 18 cancellations (10.4%). PDSA cycle 3 spanned 39 workdays and had 94 MR simulations, with 7 cancellations (7.4%). The cancellation rate during each PDSA cycle was 0.11, 0.21, and 0.17 cancellations/day, respectively. The number of patients in the WQ during each PDSA cycle, representing successfully screened high-risk patients, was 0, 0, and 3, respectively. There were no SEs during the study.

CONCLUSION

In this study, an MR safety workflow from radiology was successfully implemented in RO. There were no SEs during the study, but the number of patients successfully screened as high-risk and placed in the WQ increased after repeat PC education. Further increases in WQ use would decrease the demand for implant assessment at point of care, which could decrease burden on the MRT, same day cancellations, and potentially SEs. This will be especially important if case load increases. Future work could expand educational efforts to additional staff.

Identifying Common Topics in Patient Portal Messages with Unsupervised Natural Language Processing

PURPOSE/OBJECTIVE(S)

Patient portal messaging is an increasingly important form of communication between patients and medical providers. This has become particularly relevant in oncology, where patients undergo intense longitudinal treatments that require frequent communication regarding symptoms, appointments, and diagnostic results. The rise in the volume of these messages has significantly increased the workload of medical providers and consequent physician burn-out. Natural language processing (NLP), particularly transformer-based models, may offer an automated approach to characterize the content of patient messages and improve message triage and routing. In this study, we employed a state-of-the-art language model (Bidirectional Encoder Representations from Transformers; BERT) to identify data-derived categories of representative topics from real-world data thereby providing basic information to build an appropriate routing system.

MATERIALS/METHODS

Patient-generated portal messages sent to a messaging pool for a single institution radiation oncology department from 2014 to 2023 were extracted. BERTopic, an NLP-based topic modeling technique based on BERT was optimized for topic modeling of patient messages. Uniform Manifold Approximation and Projection (UMAP) was used to reduce dimensionality and visualize topic relationships across messages. The BERTopic-identified topic categories were subsequently labeled manually by one of the physician investigators. Differences of number of messages over time were assessed using t-tests.

RESULTS

A total of 47,492 messages were retrieved. The average number of messages per month from a single patient ranged from 1 to 18 (median 1.67, interquartile range 1.0-2.4). The total volume of patient messages showed a ten-fold increase over the study period, with 101 messages per month sent in 2014 and 999 messages per month in 2022 (p<0.001). BERTopic initially identified 35 topics whose relationships and degrees of overlap were visualized by UMAP. Due to physician-identified similarities, these topics were reduced into 13 categories. The most frequent topic category was messages about laboratory tests or imaging studies: 24.3%, followed by messages expressing appreciation: 18.9%, scheduling discussions: 15.6%, symptom-related messages: 11%, and treatment-related messages: 10.7%.

CONCLUSION

Patient portal messages sent to a single institution radiation oncology department have increased dramatically in volume since implementation, corresponding to a broader national trend. NLP successfully identified common subject themes across patient messages, many of which are related to scheduling. This presents potential opportunities to apply NLP to automate message routing in the future.

Pneumonitis in Patients Receiving Thoracic Radiotherapy and Osimertinib: A Multi-Institutional Study

Introduction

Thoracic radiotherapy (TRT) is increasingly used in patients receiving osimertinib for advanced NSCLC, and the risk of pneumonitis is not established. We investigated the risk of pneumonitis and potential risk factors in this population.

Methods

We performed a multi-institutional retrospective analysis of patients under active treatment with osimertinib who received TRT between April 2016 and July 2022 at two institutions. Clinical characteristics, including whether osimertinib was held during TRT and pneumonitis incidence and grade (Common Terminology Criteria for Adverse Events version 5.0) were documented. Logistic regression analysis was performed to identify risk factors associated with grade 2 or higher (2+) pneumonitis.

Results

The median follow-up was 10.2 months (range: 1.9-53.2). Of 102 patients, 14 (13.7%) developed grade 2+ pneumonitis, with a median time to pneumonitis of 3.2 months (range: 1.5-6.3). Pneumonitis risk was not significantly increased in patients who continued osimertinib during TRT compared with patients who held osimertinib during TRT (9.1% versus 15.0%, p = 0.729). Three patients (2.9%) had grade 3 pneumonitis, none had grade 4, and two patients had grade 5 events (2.0%, diagnosed 3.2 mo and 4.4 mo post-TRT). Mean lung dose was associated with the development of grade 2+ pneumonitis in multivariate analysis (OR = 1.19, p = 0.021).

Conclusions

Although the overall rate of pneumonitis in patients receiving TRT and osimertinib was relatively low, there was a small risk of severe toxicity. The mean lung dose was associated with an increased risk of developing pneumonitis. These findings inform decision-making for patients and providers.