Purpose The purposes of this work are to (a) investigate whether the use of auto‐planning and multiple iterations improves quality of head and neck (HN) radiotherapy plans; (b) determine whether delivery methods such as step‐and‐shoot (SS) and volumetric modulated arc therapy (VMAT) impact plan quality; (c) report on the observations of plan quality predictions of a commercial feasibility tool. Materials and methods Twenty HN cases were retrospectively selected from our clinical database for this study. The first ten plans were used to test setting up planning goals and other optimization parameters in the auto‐planning module. Subsequently, the other ten plans were replanned with auto‐planning using step‐and‐shoot (AP‐SS) and VMAT (AP‐VMAT) delivery methods. Dosimetric endpoints were compared between the clinical plans and the corresponding AP‐SS and AP‐VMAT plans. Finally, predicted dosimetric endpoints from a commercial program were assessed. Results All AP‐SS and AP‐VMAT plans met the clinical dose constraints. With auto‐planning, the dose coverage of the low dose planning target volume (PTV) was improved while the dose coverage of the high dose PTV was maintained. Compared to the clinical plans, the doses to critical organs, such as the brainstem, parotid, larynx, esophagus, and oral cavity were significantly reduced in the AP‐VMAT (P < 0.05); the AP‐SS plans had similar homogeneity indices (HI) and conformality indices (CI) and the AP‐VMAT plans had comparable HI and improved CI. Good agreement in dosimetric endpoints between predictions and AP‐VMAT plans were observed in five of seven critical organs. Conclusion With improved planning quality and efficiency, auto‐planning module is an effective tool to enable planners to generate HN IMRT plans that are meeting institution specific planning protocols. DVH prediction is feasible in improving workflow and plan quality.

Injuries to the brachial plexus and subclavian artery are serious complications of shoulder girdle trauma. Due to the close anatomical relationship between the brachial plexus and the subclavian artery in the thoracic outlet, both structures are often simultaneously involved in shoulder girdle injuries. Isolated lesions of the subclavian artery or the brachial plexus can also occur, especially with clavicular fractures. When a false subclavian aneurysm leads to a gradually increasing compression of the brachial plexus, the neurological signs and symptoms develop insidiously after the traumatic event.

Purpose To conduct a prospective observational study across 12 U.S. hospitals to evaluate real-time performance of an interpretable artificial intelligence (AI) model to detect COVID-19 on chest radiographs. Materials and Methods A total of 95 363 chest radiographs were included in model training, external validation, and real-time validation. The model was deployed as a clinical decision support system, and performance was prospectively evaluated. There were 5335 total real-time predictions and a COVID-19 prevalence of 4.8% (258 of 5335). Model performance was assessed with use of receiver operating characteristic analysis, precision-recall curves, and F1 score. Logistic regression was used to evaluate the association of race and sex with AI model diagnostic accuracy. To compare model accuracy with the performance of board-certified radiologists, a third dataset of 1638 images was read independently by two radiologists. Results Participants positive for COVID-19 had higher COVID-19 diagnostic scores than participants negative for COVID-19 (median, 0.1 [IQR, 0.0–0.8] vs 0.0 [IQR, 0.0–0.1], respectively; P < .001). Real-time model performance was unchanged over 19 weeks of implementation (area under the receiver operating characteristic curve, 0.70; 95% CI: 0.66, 0.73). Model sensitivity was higher in men than women ( P = .01), whereas model specificity was higher in women ( P = .001). Sensitivity was higher for Asian ( P = .002) and Black ( P = .046) participants compared with White participants. The COVID-19 AI diagnostic system had worse accuracy (63.5% correct) compared with radiologist predictions (radiologist 1 = 67.8% correct, radiologist 2 = 68.6% correct; McNemar P < .001 for both). Conclusion AI-based tools have not yet reached full diagnostic potential for COVID-19 and underperform compared with radiologist prediction. Keywords: Diagnosis, Classification, Application Domain, Infection, Lung Supplemental material is available for this article. . © RSNA, 2022

Statistical modeling of outcomes based on a patient's presenting symptoms (symptomatology) can help deliver high quality care and allocate essential resources, which is especially important during the COVID-19 pandemic. Patient symptoms are typically found in unstructured notes, and thus not readily available for clinical decision making. In an attempt to fill this gap, this study compared two methods for symptom extraction from Emergency Department (ED) admission notes. Both methods utilized a lexicon derived by expanding The Center for Disease Control and Prevention's (CDC) Symptoms of Coronavirus list. The first method utilized a word2vec model to expand the lexicon using a dictionary mapping to the Uni ed Medical Language System (UMLS). The second method utilized the expanded lexicon as a rule-based gazetteer and the UMLS. These methods were evaluated against a manually annotated reference (f1-score of 0.87 for UMLS-based ensemble; and 0.85 for rule-based gazetteer with UMLS). Through analyses of associations of extracted symptoms used as features against various outcomes, salient risks among the population of COVID-19 patients, including increased risk of in-hospital mortality (OR 1.85, p-value < 0.001), were identified for patients presenting with dyspnea. Disparities between English and non-English speaking patients were also identified, the most salient being a concerning finding of opposing risk signals between fatigue and in-hospital mortality (non-English: OR 1.95, p-value = 0.02; English: OR 0.63, p-value = 0.01). While use of symptomatology for modeling of outcomes is not unique, unlike previous studies this study showed that models built using symptoms with the outcome of in-hospital mortality were not significantly different from models using data collected during an in-patient encounter (AUC of 0.9 with 95% CI of [0.88, 0.91] using only vital signs; AUC of 0.87 with 95% CI of [0.85, 0.88] using only symptoms). These findings indicate that prognostic models based on symptomatology could aid in extending COVID-19 patient care through telemedicine, replacing the need for in-person options. The methods presented in this study have potential for use in development of symptomatology-based models for other diseases, including for the study of Post-Acute Sequelae of COVID-19 (PASC).

The purpose of this study was to compare the single‐isocenter, four‐field hybrid IMRT with the two‐isocenter techniques to treat the whole breast and supraclavicular fields and to investigate the intrafraction motions in both techniques in the superior direction. Fifteen breast cancer patients who underwent lumpectomy and adjuvant radiation to the whole breast and supraclavicular (SCV) fossa at our institution were selected for this study. Two planning techniques were compared for the treatment of the breast and SCV lymph nodes. The patients were divided into three subgroups according to the whole breast volume. For the two‐isocenter technique, conventional wedged or field‐within‐a‐field tangents (FIF) were used to match with the same anterior field for the SCV region. For the single‐isocenter technique, four‐field hybrid IMRT was used for the tangent fields matched with a half blocked anterior field for the SCV region. To simulate the intrafraction uncertainties in the longitudinal direction for both techniques, the treatment isocenters were shifted by 1 mm and 2 mm in the superior direction. The average breast clinical tumor volume (CTV) receiving 100% (V100%) of the prescription dose (50 Gy) was 99.3%±0.5% and 96.4%±1.2% for the for two‐isocenter and single‐isocenter plans (p<0.05), respectively. The breast CTV receiving 95% of the prescription dose (V95%) was close to 100% in both techniques. The average breast CTV receiving 105% (V105%) of the prescription dose was 32.4%±19.3% and 23.8%±13.3% (p=0.08). The percentage volume of the breast CTV receiving 110% of the dose was 0.4%±1.2% in the two‐isocentric technique vs. 0.1%±0.2% in the single‐isocentric technique. The average uniformity index was 0.91±0.02 vs. 0.91±0.01 in both techniques (p=0.04), but had no clinical impact. The percentage volume of the contralateral breast receiving a dose of 1 Gy was less than 2.3% in small breast patients and insignificant for medium and large breast sizes. The percentage of the total lung volume receiving g>20 Gy (normalV20Gy) and the heart receiving >30 Gy (normalV30Gy) were 13.6% vs. 14.3% (p=0.03) and 1.25% vs. 1.2% (p=0.62), respectively. Shifting the treatment isocenter by 1 mm and 2 mm superiorly showed that the average maximum dose to 1 cc of the breast volume was 55.5±1.8 Gy and 58.6±4.3 Gy in the two‐isocentric technique vs. 56.4±2.1 Gy and 59.1±5.1 Gy in the single‐isocentric technique (p=0.46, 0.87), respectively. The single‐isocenter technique using four‐field hybrid IMRT approach resulted in comparable plan quality as the two‐isocentric technique. The single‐isocenter technique is more sensitive to intrafraction motion in the superior direction compared to the two‐isocentric technique. The advantages of the single‐isocenter include elimination of isocentric errors due to couch and collimator rotations and reduction in treatment time. This study supports consideration of a single‐isocenter four‐field hybrid IMRT technique for patients undergoing breast and supraclavicular nodal irradiation.PACS number: 87.55.D...

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Background To evaluate plan quality using volumetric‐modulated arc therapy (VMAT) and step‐and‐shoot intensity‐modulated radiation therapy (SS‐IMRT) techniques and for patients treated for oropharyngeal squamous cell carcinoma (OPSCC). Methods Treatment plans for patients treated definitively for stages I‐IVb, OPSCC between December 2009 and August 2015 were retrospectively reviewed. Dosimetric endpoints of involved organs‐at‐risk (OARs) were retrieved from clinical plans. Common Terminology Criteria for Adverse Events scores of acute toxicities were compared. Results Two‐hundred twenty‐two patients were identified with 134 and 88 receiving SS‐IMRT and VMAT with median follow‐up time of 23.0 and 7.9 months, respectively. The dosimetric endpoints of the OARs were significantly improved in VMAT cohort, which translated into significantly lower rates of grade 2 or higher acute dysphagia and xerostomia. Conclusion Improvements in stages I‐IVb, oropharyngeal cancer plan quality are associated with reduced grade ≥ 2 acute dysphagia and xerostomia.

Objective To investigate the association between tumor volume and locoregional failure (LRF) after concurrent chemoradiation (CCRT) for locally advanced larynx cancer (LC). Methods This is a retrospective cohort study from 2009 to 2014 identified from an institutional review board–approved registry. Fifty‐nine of 68 patients with locally advanced larynx cancer treated with definitive CCRT who had available imaging for review were identified. The main endpoint to be assessed was the association between gross tumor volumes (GTV; T = total, P = primary, N = nodal) and LRF. Receiver operative characteristic (ROC) curves were used to investigate diagnostic accuracy. Results Twenty LRFs were observed, resulting in a 2‐year LRF rate of 39% (95% CI, 23–52%). On UVA, the GTV‐T (P = .01), GTV‐P (P = .05), and GTV‐N (P = .04) were statistically significant predictors of LRF. Furthermore, age, smoking status, N‐stage, larynx subsite, and tracheostomy/feeding tube dependence were potentially associated with LRF (P < .3), whereas T‐stage (T3–4 vs. T2) was not (HR 1.05, 95% CI, 0.38–2.91, P = .92). In the multivariable model, GTV‐P (HR 1.022, 95% CI, 0.999–1.046, P = .07) and GTV‐N (HR 1.053, 95% CI, 1.0004–1.108, P = .05) were the two most impactful covariates on the model's R2. ROC analysis suggested an optimal cut point of 12 cc in the GTV‐T. The 2‐year LRF for GTV‐T > 12 cc was 64.2% and ≤ 12 cc was 16.4%, P = .006. Conclusion GTV is associated with LRF after definitive CCRT for LC. Patients with bulky primary and/or nodal tumors may be better served with upfront surgical resection regardless of T‐stage. Further investigation into the safety of larynx preservation for low‐volume T4 tumors can be considered. Level of Evidence 4 Laryngoscope, 130:2372–2377, 2020