Are there features that can predict the unresectability of pleural mesothelioma?

INTRODUCTION: The current clinical staging of pleural mesothelioma (PM) is often discordant with the pathologic staging. This study aimed to identify clinical and radiological features that could help predict unresectability in PM. METHODS: Twenty-two descriptive radiologic features were retrospectively evaluated on preoperative computed tomography (CT) and/or positron emission tomography/CT (PET/CT) performed in patients with presumably resectable PM who underwent surgery. Measurements of maximum and sum pleural thickness at three levels of the thorax (upper, middle, and lower) were taken and stratified based on the cutpoints provided by the International Association for the Study of Lung Cancer (IASLC). Clinical and radiological features, including clinical-stage, were compared between resectable and unresectable tumors by univariate analysis and logistic regression modeling. RESULTS: Of 133 patients, 69/133 (52%) had resectable and 64/133 (48%) had unresectable PM. Asbestos exposure (p = 0.005), neoadjuvant treatment (p = 0.001), clinical T-stage (p < 0.0001), all pleural thickness measurements (p < 0.05), pleural thickness pattern (p < 0.0001) and degree (p = 0.033), lung invasion (p = 0.004), extrapleural space obliteration (p < 0.0001), extension to subphrenic space (p = 0.0004), and two combination variables representing extensive diaphragmatic contact and/or chest wall involvement (p = 0.002) and mediastinal invasion (p < 0.0001) were significant predictors at univariate analysis. At multivariable analysis, all models achieved a strong diagnostic performance (area under the curve (AUC) > 0.8). The two best-performing models were one that included the upper-level maximum pleural thickness, extrapleural space obliteration, and mediastinal infiltration (AUC = 0.876), and another that integrated clinical variables and radiological assessment through the clinical T-stage (AUC = 0.879). CONCLUSION: Selected clinical and radiologic features, including pleural thickness measurements, appear to be strong predictors of unresectability in PM. CLINICAL RELEVANCE STATEMENT: A more accurate prediction of unresectability in the preoperative assessment of patients with pleural mesothelioma may avoid unnecessary surgery and prompt initiation of nonsurgical treatments. KEY POINTS: About half of pleural mesothelioma patients are reported to receive an incorrect disease stage preoperatively. Eleven features identified as predictors of unresectability were included in strongly performing predictive models. More accurate preoperative staging will help clinicians and patients choose the most appropriate treatments.

A phase I/II study of valemetostat (DS-3201b), an EZH1/2 inhibitor, in combination with irinotecan in patients with recurrent small cell lung cancer.

PURPOSE: Recurrent small cell lung cancer (SCLC) has few effective treatments. The EZH2-SLFN11 pathway is a driver of acquired chemoresistance that may be targeted. PATIENTS AND METHODS: This phase I/II trial investigated valemetostat, an EZH1/2 inhibitor, with fixed-dose irinotecan in patients with recurrent SCLC. Phase I primary objectives were to assess safety and a recommended phase II dose (RP2D). The phase II primary objective was to determine overall response rate (ORR), with secondary objectives of duration of response (DoR), progression-free survival (PFS) and overall survival (OS). Immunohistochemistry of pre- and on-treatment tumor biopsies and pharmacokinetics analysis were performed. RESULTS: Twenty-two patients enrolled (phase I, n=12; phase II n=10); one withdrew consent prior to treatment. Three dose-limiting toxicities (DLTs) in dose-escalation resulted in valemetostat 100 mg orally daily selected as RP2D. Among 21 toxicity-evaluable patients, the most frequent (≥20%) treatment-related adverse events were diarrhea, fatigue, nausea, and rash; 3 patients discontinued treatment for toxicity. In phase II, 3/10 patients experienced DLTs triggering a stopping rule. The ORR was 4/19 (21%, 95% CI 6 to 46%). The median DoR, PFS and OS were 4.6 mo, 2.2 mo (95% CI 1.3 to 7.6 mo) and 6.6 mo (95% CI 4.3 to not reached). SLFN11, EZH2 and SCLC subtyping markers did not correlate with response. MHC-I protein expression increased in 4/4 patients with paired biopsies, including 3/3 responders; two responders demonstrated subtype switching on treatment. CONCLUSIONS: Valemetostat and irinotecan was not tolerated but demonstrated efficacy in recurrent SCLC. Valemetostat may warrant further investigation in SCLC.

A Real-World Assessment of Stage I Lung Cancer Through Electronic Nose Technology.

INTRODUCTION: Electronic nose (E-nose) technology has reported excellent sensitivity and specificity in the setting of lung cancer screening. However, the performance of E-nose specifically for early-stage tumors remains unclear. Therefore, the aim of our study was to assess the diagnostic performance of E-nose technology in clinical stage I lung cancer. METHODS: This phase IIc trial (NCT04734145) included patients diagnosed with a single greater than or equal to 50% solid stage I nodule. Exhalates were prospectively collected from January 2020 to August 2023. Blinded bioengineers analyzed the exhalates, using E-nose technology to determine the probability of malignancy. Patients were stratified into three risk groups (low-risk, [<0.2]; moderate-risk, [≥0.2-0.7]; high-risk, [≥0.7]). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models. RESULTS: Based on the predefined cutoff (<0.20), E-nose agreed with histopathologic results in 86% of cases, achieving an F1 score of 92.5%, based on 86 true positives, two false negatives, and 12 false positives (n = 100). E-nose would refer fewer patients with malignant nodules to observation (low-risk: 2 versus 9 and 11, respectively; p = 0.028 and p = 0.011) than would the Swensen and Brock models and more patients with malignant nodules to treatment without biopsy (high-risk: 27 versus 19 and 6, respectively; p = 0.057 and p < 0.001). CONCLUSIONS: In the setting of clinical stage I lung cancer, E-nose agrees well with histopathology. Accordingly, E-nose technology can be used in addition to imaging or as part of a "multiomics" platform.

Clinical outcomes of stereotactic body radiation therapy for malignant pleural mesothelioma.

BACKGROUND: The objective of this study is to determine the outcomes and toxicities of patients with malignant pleural mesothelioma (MPM) treated with stereotactic body radiotherapy (SBRT). MATERIALS AND METHODS: Data were extracted from an institutional tumor registry for patients diagnosed with mesothelioma and treated with SBRT. Kaplan-Meier and Cox regression analyses were employed to determine local control (LC) and overall survival (OS). RESULTS: Forty-four patients with 59 total treated tumors from December 2006 to April 2022 were identified. Fifty-one (86.4 %) cases had oligoprogressive disease (five sites or less). The median prescription dose delivered was 3000 cGy in 5 fractions (range: 2700-6000 cGy in 3-8 fractions). Fifty-one (86.4 %) tumors were in the pleura, 4 (6.8 %) spine, 2 (3.4 %) bone, 1 (1.7 %) brain, and 1 (1.7 %) pancreas. The median follow-up from SBRT completion for those alive at last follow-up was 28 months (range: 14-52 months). The most common toxicities were fatigue (50.8 %), nausea (22.0 %), pain flare (15.3 %), esophagitis (6.8 %), dermatitis (6.8 %), and pneumonitis (5.1 %). There were no grade ≥ 3 acute or late toxicities. There were 2 (3.4 %) local failures, one of the pleura and another of the spine. One-year LC was 92.9 % (95 % CI: 74.6-98.2 %) for all lesions and 96.3 % (95 % CI: 76.5-99.5 %) for pleural tumors. One-year LC was 90.9 % (95 % CI: 68.1-97.6 %) for epithelioid tumors and 92.1 % (95 % CI: 72.1-98.0 %) for oligoprogressive tumors. One-year OS from time of SBRT completion was 36.4 % (95 % CI: 22.6-50.3 %). On multivariable analysis, KPS was the lone significant predictor for OS (p = 0.029). CONCLUSIONS: Our single-institutional experience on patients with MPM suggests that SBRT is safe with a low toxicity profile and potentially achieve good local control.

The GENIE BPC NSCLC Cohort: A Real-World Repository Integrating Standardized Clinical and Genomic Data for 1,846 Patients with Non-Small Cell Lung Cancer.

PURPOSE: We describe the clinical and genomic landscape of the non-small cell lung cancer (NSCLC) cohort of the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) Biopharma Collaborative (BPC). EXPERIMENTAL DESIGN: A total of 1,846 patients with NSCLC whose tumors were sequenced from 2014 to 2018 at four institutions participating in AACR GENIE were randomly chosen for curation using the PRISSMM data model. Progression-free survival (PFS) and overall survival (OS) were estimated for patients treated with standard therapies. RESULTS: In this cohort, 44% of tumors harbored a targetable oncogenic alteration, with EGFR (20%), KRAS G12C (13%), and oncogenic fusions (ALK, RET, and ROS1; 5%) as the most frequent. Median OS (mOS) on first-line platinum-based therapy without immunotherapy was 17.4 months [95% confidence interval (CI), 14.9-19.5 months]. For second-line therapies, mOS was 9.2 months (95% CI, 7.5-11.3 months) for immune checkpoint inhibitors (ICI) and 6.4 months (95% CI, 5.1-8.1 months) for docetaxel ± ramucirumab. In a subset of patients treated with ICI in the second-line or later setting, median RECIST PFS (2.5 months; 95% CI, 2.2-2.8) and median real-world PFS based on imaging reports (2.2 months; 95% CI, 1.7-2.6) were similar. In exploratory analysis of the impact of tumor mutational burden (TMB) on survival on ICI treatment in the second-line or higher setting, TMB z-score harmonized across gene panels was associated with improved OS (univariable HR, 0.85; P = 0.03; n = 247 patients). CONCLUSIONS: The GENIE BPC cohort provides comprehensive clinicogenomic data for patients with NSCLC, which can improve understanding of real-world patient outcomes.

Imaging Follow-Up of Nonsurgical Therapies for Lung Cancer: AJR Expert Panel Narrative Review.

Lung cancer continues to be the most common cause of cancer-related death worldwide. In the past decade, with the implementation of lung cancer screening programs and advances in surgical and nonsurgical therapies, the survival of patients with lung cancer has increased, as has the number of imaging studies that these patients undergo. However, most patients with lung cancer do not undergo surgical re-section, because they have comorbid disease or lung cancer in an advanced stage at diagnosis. Nonsurgical therapies have continued to evolve with a growing range of systemic and targeted therapies, and there has been an associated evolution in the imaging findings encountered at follow-up examinations after such therapies (e.g., with respect to posttreatment changes, treatment complications, and recurrent tumor). This AJR Expert Panel Narrative Review describes the current status of nonsurgical therapies for lung cancer and their expected and unexpected imaging manifestations. The goal is to provide guidance to radiologists regarding imaging assessment after such therapies, focusing mainly on non-small cell lung cancer. Covered therapies include systemic therapy (conventional chemotherapy, targeted therapy, and immunotherapy), radiotherapy, and thermal ablation.

Clinical Outcomes Associated With Pembrolizumab Monotherapy Among Adults With Diffuse Malignant Peritoneal Mesothelioma.

Importance: Diffuse malignant peritoneal mesothelioma (DMPM) represents a rare and clinically distinct entity among malignant mesotheliomas. Pembrolizumab has activity in diffuse pleural mesothelioma but limited data are available for DMPM; thus, DMPM-specific outcome data are needed. Objective: To evaluate outcomes after the initiation of pembrolizumab monotherapy in the treatment of adults with DMPM. Design, Setting, and Participants: This retrospective cohort study was conducted in 2 tertiary care academic cancer centers (University of Pennsylvania Hospital Abramson Cancer Center and Memorial Sloan Kettering Cancer Center). All patients with DMPM treated between January 1, 2015, and September 1, 2019, were retrospectively identified and followed until January 1, 2021. Statistical analysis was performed between September 2021 and February 2022. Exposures: Pembrolizumab (200 mg or 2 mg/kg every 21 days). Main Outcomes and Measures: Median progression-free survival (PFS) and median overall survival (OS) were assessed using Kaplan-Meier estimates. The best overall response was determined using RECIST (Response Evaluation Criteria in Solid Tumors) criteria, version 1.1. The association of disease characteristics with partial response was evaluated using the Fisher exact test. Results: This study included 24 patients with DMPM who received pembrolizumab monotherapy. Patients had a median age of 62 years (IQR, 52.4-70.6 years); 14 (58.3%) were women, 18 (75.0%) had epithelioid histology, and most (19 [79.2%]) were White. A total of 23 patients (95.8%) received systemic chemotherapy prior to pembrolizumab, and the median number of lines of prior therapy was 2 (range, 0-6 lines). Of the 17 patients who underwent programmed death ligand 1 (PD-L1) testing, 6 (35.3%) had positive tumor PD-L1 expression (range, 1.0%-80.0%). Of the 19 evaluable patients, 4 (21.0%) had a partial response (overall response rate, 21.1% [95% CI, 6.1%-46.6%]), 10 (52.6%) had stable disease, and 5 (26.3%) had progressive disease (5 of 24 patients [20.8%] were lost to follow-up). There was no association between a partial response and the presence of a BAP1 alteration, PD-L1 positivity, or nonepithelioid histology. With a median follow-up of 29.2 (95% CI, 19.3 to not available [NA]) months, the median PFS was 4.9 (95% CI, 2.8-13.3) months and the median OS was 20.9 (95% CI, 10.0 to NA) months from pembrolizumab initiation. Three patients (12.5%) experienced PFS of more than 2 years. Among patients with nonepithelioid vs epithelioid histology, there was a numeric advantage in median PFS (11.5 [95% CI, 2.8 to NA] vs 4.0 [95% CI, 2.8-8.8] months) and median OS (31.8 [95% CI, 8.3 to NA] vs 17.5 [95% CI, 10.0 to NA] months); however, this did not reach statistical significance. Conclusions and Relevance: The results of this retrospective dual-center cohort study of patients with DMPM suggest that pembrolizumab had clinical activity regardless of PD-L1 status or histology, although patients with nonepithelioid histology may have experienced additional clinical benefit. The partial response rate of 21.0% and median OS of 20.9 months in this cohort with 75.0% epithelioid histology warrants further investigation to identify those most likely to respond to immunotherapy.

Conventional and radiomic features to predict pathology in the preoperative assessment of anterior mediastinal masses.

OBJECTIVES: The aim of this study was to differentiate benign from malignant tumors in the anterior mediastinum based on computed tomography (CT) imaging characteristics, which could be useful in preoperative planning. Additionally, our secondary aim was to differentiate thymoma from thymic carcinoma, which could guide the use of neoadjuvant therapy. MATERIALS AND METHODS: Patients referred for thymectomy were retrospectively selected from our database. Twenty-five conventional characteristics were evaluated by visual analysis, and 101 radiomic features were extracted from each CT. In the step of model training, we applied support vector machines to train classification models. Model performance was assessed using the area under the receiver operating curves (AUC). RESULTS: Our final study sample comprised 239 patients, 59 (24.7 %) with benign mediastinal lesions and 180 (75.3 %) with malignant thymic tumors. Among the malignant masses, there were 140 (58.6 %) thymomas, 23 (9.6 %) thymic carcinomas, and 17 (7.1 %) non-thymic lesions. For the benign versus malignant differentiation, the model that integrated both conventional and radiomic features achieved the highest diagnostic performance (AUC = 0.715), in comparison to the conventional (AUC = 0.605) and radiomic-only (AUC = 0.678) models. Similarly, regarding thymoma versus thymic carcinoma differentiation, the model that integrated both conventional and radiomic features also achieved the highest diagnostic performance (AUC = 0.810), in comparison to the conventional (AUC = 0.558) and radiomic-only (AUC = 0.774) models. CONCLUSION: CT-based conventional and radiomic features with machine learning analysis could be useful for predicting pathologic diagnoses of anterior mediastinal masses. The diagnostic performance was moderate for differentiating benign from malignant lesions and good for differentiating thymomas from thymic carcinomas. The best diagnostic performance was achieved when both conventional and radiomic features were integrated in the machine learning algorithms.

A Phase 1 Safety Study of Avelumab Plus Stereotactic Body Radiation Therapy in Malignant Pleural Mesothelioma.

Introduction: Single-agent monoclonal antibody therapy against programmed death-ligand 1 (PD-L1) has modest effects in malignant pleural mesothelioma. Radiation therapy can enhance the antitumor effects of immunotherapy. Nevertheless, the safety of combining anti-PD-L1 therapy with stereotactic body radiation therapy (SBRT) is unknown. We present the results of a phase 1 trial to evaluate the safety of the anti-PD-L1 antibody avelumab plus SBRT in patients with malignant pleural mesothelioma. Methods: This was a single-arm, investigator-initiated trial in patients who progressed on prior chemotherapy. Avelumab was delivered every other week, and SBRT was delivered to one lesion in three to five fractions (minimum of 30 Gy) followed by continuation of avelumab up to 24 months or until disease progression. The primary end point of the study was safety on the basis of grade 3+ nonhematologic adverse events (AEs) within 3 months of SBRT. Results: Thirteen assessable patients received a median of seven cycles (range: 2-26 cycles) of avelumab. There were 27 grade 1, 17 grade 2, four grade 3, and no grade 4 or 5 avelumab-related AEs. The most common were infusion-related allergic reactions (n = 6), anorexia or weight loss (n = 6), fatigue (n = 6), thyroid disorders (n = 5), diarrhea (n = 3), and myalgia or arthralgias (n = 3). There were 10 grade 1, four grade 2, one grade 3, and no grade 4 or 5 SBRT-related AEs. The most common were diarrhea (n = 3), chest pain/myalgia (n = 2), fatigue (n = 2), cough (n = 2), dyspnea (n = 2), and nausea/vomiting (n = 2). Conclusions: Combination avelumab plus SBRT seems tolerable on the basis of the prespecified toxicity end points of the first stage of this Simon two-stage design phase 1 study.

Radiologic and histopathologic features of hydrogel sealant after lung resection in participants of a prospective randomized clinical trial.

PURPOSE: To summarize imaging and histopathologic characteristics of hydrogel sealant (plug) in lung parenchyma and assess their correlation with time since deployment of sealant. MATERIALS AND METHODS: Among a total of 208 participants randomized to the hydrogel sealant arm of a lung biopsy prospective randomized clinical trial, 51 underwent resection of the biopsied lesion. In 34 participants sealant material was present on histopathologic sections (n = 22), or they had cross-sectional imaging of chest between biopsy and resection (n = 23) or they had both imaging and histopathology (n = 11). Histopathologic and imaging findings were described. The association of these findings with time since sealant deployment was evaluated using the Wilcoxon rank sum test. RESULTS: The mean time since sealant deployment for histopathology was 45.7 days (median 36, range 14-181) and for imaging studies was 99 days (median 32, range 4-527). The sealant was infiltrated by inflammatory cells in 20 (91%) participants. The main general histopathologic pattern of sealant was foamy in 12 (57%) and mesh in 8 (38%) participants. Imaging appearance of sealant was serpiginous in 18 (60%), linear in 10 (33%) or lobulated in 2 (6.7%) participants. In 2 participants the sealant was hypermetabolic with no histopathologic evidence of tumor. No correlation was found between time since sealant deployment and imaging or histopathologic appearances. CONCLUSION: Hydrogel sealant appears as a serpiginous, linear, or lobulated opacity on cross-sectional imaging which can be metabolically active. It is associated with an inflammatory reaction with a foamy or mesh general pattern on histopathological assessment. No correlation was found between time since sealant deployment and imaging or histopathologic appearances.

Detection of COVID-19 pulmonary manifestations with radiotherapy simulation CT imaging.

COVID-19 is associated with characteristic lung CT findings. Radiotherapy simulation CT scans may reveal characteristic COVID-19 findings and identify patients with active or prior infection. We reviewed patients undergoing CT simulation at a major cancer center in an early epicenter of the COVID-19 pandemic in the United States. Scans were reviewed by radiation oncologists using established radiographic criteria for COVID-19 pneumonia. Radiographic classifications were compared with available COVID-19 PCR test results. A one-tailed t-test was used to compare the rate of positive COVID-19 tests in radiographically suspicious vs. non-suspicious groups. Scans deemed suspicious were re-reviewed by expert diagnostic radiologists. 414 CT simulation scans were performed on 400 patients. 119 patients had COVID-19 PCR test results available. Radiation oncologists considered 71 scans (17.1%) suspicious for COVID-19. Of these, 23 had corresponding COVID-19 PCR tests, and 3/23 (15.7%) were positive for COVID. 107 non-suspicious scans had corresponding COVID-19 test results, and 9 were positive (8.4%). The difference in positive test results between suspicious and non-suspicious groups was not significant (p = 0.23). Upon re-review by a diagnostic radiologist, 25 (35%) scans deemed suspicious by radiation oncologists were confirmed to meet criteria, while the rest were re-classified as "atypical" for COVID-19. We conclude that radiotherapy simulation CT scans can be reviewed for signs of COVID-19 pneumonia by radiation oncologists. However, suspicious CT simulation was not associated with a higher incidence of COVID infection compared with non-suspicious CT simulation, and there was low concordance between radiation oncologist and diagnostic radiologist classification of scans.

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer.

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.

Toward Improved Outcomes for Patients With Lung Cancer Globally: The Essential Role of Radiology and Nuclear Medicine.

PURPOSE: Key to achieving better population-based outcomes for patients with lung cancer is the improvement of medical imaging and nuclear medicine infrastructure globally. This paper aims to outline why and spark relevant health systems strengthening. METHODS: The paper synthesizes the global lung cancer landscape, imaging referral guidelines (including resource-stratified ones), the reliance of TNM staging upon imaging, relevant multinational health technology assessments, and precisely how treatment selection and in turn patient outcomes hinge upon imaging findings. The final discussion presents data on current global gaps in both diagnostics (including imaging) and therapies and how, informed by such data, improved population-based outcomes are tangible through strategic planning. RESULTS: Imaging findings are central to appropriate lung cancer patient management and can variably lead to life-prolonging interventions and/or to life-enhancing palliative measures. Early-stage lung cancer can be treated with curative intent but, unfortunately, most patients with lung cancer still present at advanced stages and many patients lack access to both diagnostics and therapies. Furthermore, half of lung cancer cases occur in low- and middle-income countries. The role of medical imaging and nuclear medicine in lung cancer management, as outlined herein, may help inform strategic planning. CONCLUSION: Lung cancer is the number one cancer killer worldwide. The essential role that medical imaging and nuclear medicine play in early diagnosis and disease staging cannot be overstated, pivotal in selecting the many patients for whom measurably improved outcomes are attainable. Prevention synergized with patient-centered, compassionate, high-quality lung cancer management provision mandate that strategic population-based planning, including universal health coverage strategies, should extend well beyond the scope of disease prevention to include both curative and noncurative treatment options for the millions afflicted with lung cancer.

CT-based Radiogenomic Analysis of Clinical Stage I Lung Adenocarcinoma with Histopathologic Features and Oncologic Outcomes.

Background A preoperative predictive model is needed that can be used to identify patients with lung adenocarcinoma (LUAD) who have a higher risk of recurrence or metastasis. Purpose To investigate associations between CT-based radiomic consensus clustering of stage I LUAD and clinical-pathologic features, genomic data, and patient outcomes. Materials and Methods Patients who underwent complete surgical resection for LUAD from April 2014 to December 2017 with preoperative CT and next-generation sequencing data were retrospectively identified. Comprehensive radiomic analysis was performed on preoperative CT images; tumors were classified as solid, ground glass, or mixed. Patients were clustered into groups based on their radiomics features using consensus clustering, and clusters were compared with tumor genomic alterations, histopathologic features, and recurrence-specific survival (Kruskal-Wallis test for continuous data, χ2 or Fisher exact test for categorical data, and log-rank test for recurrence-specific survival). Cluster analysis was performed on the entire cohort and on the solid, ground-glass, and mixed lesion subgroups. Results In total, 219 patients were included in the study (median age, 68 years; interquartile range, 63-74 years; 150 [68%] women). Four radiomic clusters were identified. Cluster 1 was associated with lepidic, acinar, and papillary subtypes (76 of 90 [84%]); clusters 2 (13 of 50 [26%]) and 4 (13 of 45 [29%]) were associated with solid and micropapillary subtypes (P < .001). The EGFR alterations were highest in cluster 1 (38 of 90 [42%], P = .004). Clusters 2, 3, and 4 were associated with lymphovascular invasion (19 of 50 [38%], 14 of 34 [41%], and 28 of 45 [62%], respectively; P < .001) and tumor spread through air spaces (32 of 50 [64%], 21 of 34 [62%], and 31 of 45 [69%], respectively; P < .001). STK11 alterations (14 of 45 [31%]; P = .006), phosphoinositide 3-kinase pathway alterations (22 of 45 [49%], P < .001), and risk of recurrence (log-rank P < .001) were highest in cluster 4. Conclusion CT-based radiomic consensus clustering enabled identification of associations between radiomic features and clinicalpathologic and genomic features and outcomes in patients with clinical stage I lung adenocarcinoma. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Nishino in this issue.

Radiogenomics in personalized management of lung cancer patients: Where are we?

With the rise of artificial intelligence, radiomics has emerged as a field of translational research based on the extraction of mineable high-dimensional data from radiological images to create "big data" datasets for the purpose of identifying distinct sub-visual imaging patterns. The integrated analysis of radiomic data and genomic data is termed radiogenomics, a promising strategy to identify potential imaging biomarkers for predicting driver mutations and other genomic parameters. In lung cancer, recent advances in whole-genome sequencing and the identification of actionable molecular alterations have led to an increased interest in understanding the complex relationships between imaging and genomic data, with the potential of guiding therapeutic strategies and predicting clinical outcomes. Although the integration of the radiogenomics data into lung cancer management may represent a new paradigm in the field, the use of this technique as a clinical biomarker remains investigational and still necessitates standardization and robustness to be effectively translated into the clinical practice. This review summarizes the basic concepts, potential contributions, challenges, and opportunities of radiogenomics in the management of patients with lung cancer.

Phase 1 Clinical Trial of Trametinib and Ponatinib in Patients With NSCLC Harboring KRAS Mutations.

INTRODUCTION: Somatic KRAS mutations occur in 25% of patients with NSCLC. Treatment with MEK inhibitor monotherapy has not been successful in clinical trials to date. Compensatory activation of FGFR1 was identified as a mechanism of trametinib resistance in KRAS-mutant NSCLC, and combination therapy with trametinib and ponatinib was synergistic in in vitro and in vivo models. This study sought to evaluate this drug combination in patients with KRAS-mutant NSCLC. METHODS: A phase 1 dose escalation study of trametinib and ponatinib was conducted in patients with advanced NSCLC with KRAS mutations. A standard 3-plus-3 dose escalation was done. Patients were treated with the study therapy until intolerable toxicity or disease progression. RESULTS: A total of 12 patients with KRAS-mutant NSCLC were treated (seven at trametinib 2 mg and ponatinib 15 mg, five at trametinib 2 mg and ponatinib 30 mg). Common toxicities observed were rash, diarrhea, and fever. Serious adverse events potentially related to therapy were reported in five patients, including one death in the study and four cardiovascular events. Serious events were observed at both dose levels. Of note, 75% (9 of 12) were assessable for radiographic response and no confirmed partial responses were observed. The median time on study was 43 days. CONCLUSIONS: In this phase 1 study, in patients with KRAS-mutant advanced NSCLC, combined treatment with trametinib and ponatinib was associated with cardiovascular and bleeding toxicities. Exploring the combination of MEK and FGFR1 inhibition in future studies is potentially warranted but alternative agents should be considered to improve safety and tolerability.

COVID-19 in patients with cancer: can baseline radiologic severity and early evolution predict clinical outcomes?

OBJECTIVE: To determine whether the degree of parenchymal involvement on chest radiograph (CXR) at the time of COVID-19 diagnosis and its early radiologic evolution can predict adverse events including hospitalization, intubation, and death in patients with cancer. METHODS: Retrospective study of 627 COVID-19-positive patients between March and April 2020, of which 248 had baseline CXR within 72 h of diagnosis and 64 patients had follow-up wihtin72 h. CXRs were classified as abnormal (i.e., radiologic findings suggestive of COVID-19 infection were noted), normal, or indeterminate. Baseline and follow-up severity scores were calculated based on lung regions in abnormal CXRs. Statistical analysis was performed to determine associations between abnormal CXR or severity score with adverse events. RESULTS: Of 248 patients (median age = 65) with a baseline CXR, 172/248 (69%) had an abnormal baseline study, which was associated with hospitalization (p < 0.001), intubation (p = 0.001), and death (p = 0.005). For patients with solid neoplasms, when adjusted for stage, it was associated with hospitalization (p = 0.0002), intubation (p = 0.019), and death (p = 0.03). The median baseline severity score was 3 (range = 1-10); the greater the score, the higher the likelihood of adverse outcome (p < 0.003 for all). A baseline severity score > 9 predicted > 50% probability of intubation and a score of ≥ 10 predicted > 50% of probability of death. The baseline severity score was not correlated with cancer-related treatment. Early radiologic progression was not correlated with hospitalization, intubation, or death. CONCLUSION: The degree of parenchymal involvement on CXR within 72 h of COVID-19 diagnosis is associated with adverse outcomes in patients with cancer. KEY POINTS: • In patients with cancer, the presence and severity of radiologic manifestation of COVID-19 on chest radiographs within 72 h of COVID-19 diagnosis are associated with hospitalization, intubation, and death. • Early radiologic progression on chest radiographs is not correlated with adverse outcomes.

CT Radiomic Features for Predicting Resectability and TNM Staging in Thymic Epithelial Tumors.

BACKGROUND: To explore the performance of a computed tomography based radiomics model in the preoperative prediction of resectability status and TNM staging in thymic epithelial tumors. METHODS: We reviewed the last preoperative computed tomography scan of patients with thymic epithelial tumors prior to resection and pathology evaluation at our institution between February 2008 and June 2019. A total of 101 quantitative features were extracted and a radiomics model was trained using elastic net penalized logistic regressions for each aim. In the set-aside testing sets, discriminating performance of each model was assessed with area under receiver operating characteristic curve. RESULTS: Our final population consisted of 243 patients with: 153 (87%) thymomas, 23 (9%) thymic carcinomas, and 9 (4%) thymic carcinoids. Incomplete resections (R1 or R2) occurred in 38 (16%) patients, and 67 (28%) patients had more advanced stage tumors (stage III or IV). In the set-aside testing sets, the radiomics model achieved good performance in preoperatively predicting incomplete resections (area under receiver operating characteristic curve: 0.80) and advanced stage tumors (area under receiver operating characteristic curve: 0.70). CONCLUSIONS: Our computed tomography radiomics model achieved good performance to predict resectability status and staging in thymic epithelial tumors, suggesting a potential value for the evaluation of radiomic features in the preoperative prediction of surgical outcomes in thymic malignancies.

Intra- and inter-reader agreement of iRECIST and RECIST 1.1 criteria for the assessment of tumor response in patients receiving checkpoint inhibitor immunotherapy for lung cancer.

OBJECTIVES: To investigate the inter- and intra-reader agreement of immune Response Evaluation Criteria in Solid Tumors (iRECIST) and Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) in patients with lung cancer treated with immunotherapy. MATERIALS AND METHODS: This retrospective study included 85 patients with lung cancer treated with PD-1 blockade. Four radiologists evaluated computed topography (CT) scans before and after initiation of immunotherapy using iRECIST and RECIST 1.1. Weighted kappa (k) with equal weights was used to assess the intra-reader agreement between 2 repeated reads on overall response at all time points, best overall response, and the response at the time point of progression, as well as the intra-reader agreement between iRECIST and RECIST. The inter-reader agreement was calculated using Light's kappa. RESULTS: Intra-reader agreement for overall response at all time points, best overall response, and time point of progression was substantial to almost perfect for both iRECIST and RECIST 1.1 (k = 0.651-0.983). Inter-reader agreement was substantial for iRECIST (κ = 0.657-0.742) while RECIST 1.1 was moderate to substantial (κ = 0.587-0.686). The level of inter-reader agreement was not higher on repeat read for iRECIST (κ = 0.677-0.709 and κ = 0.657-0.742 for first and second read, respectively) as well as for RECIST 1.1 (κ = 0.587-0.659 and κ = 0.633-0.686 for first and second read, respectively). Almost perfect agreement was observed between RECIST 1.1 and iRECIST at first (κ = 0.813-0.923) and second read (κ = 0.841-0.912). CONCLUSION: The inter- and intra-reader agreement of iRECIST is high and similar to RECIST 1.1 in patients with lung cancer treated with immunotherapy.