Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights.

While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept.

[18F]Fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) are indispensable components in modern medicine. Although PET can provide additional diagnostic value, it is costly and not universally accessible, particularly in low-income countries. To bridge this gap, we have developed a conditional generative adversarial network pipeline that can produce FDG-PET from diagnostic CT scans based on multi-center multi-modal lung cancer datasets (n = 1,478). Synthetic PET images are validated across imaging, biological, and clinical aspects. Radiologists confirm comparable imaging quality and tumor contrast between synthetic and actual PET scans. Radiogenomics analysis further proves that the dysregulated cancer hallmark pathways of synthetic PET are consistent with actual PET. We also demonstrate the clinical values of synthetic PET in improving lung cancer diagnosis, staging, risk prediction, and prognosis. Taken together, this proof-of-concept study testifies to the feasibility of applying deep learning to obtain high-fidelity PET translated from CT.

Heterogenous lung inflammation CT patterns distinguish pneumonia and immune checkpoint inhibitor pneumonitis and complement blood biomarkers in acute myeloid leukemia: proof of concept.

Background: Immune checkpoint inhibitors (ICI) may cause pneumonitis, resulting in potentially fatal lung inflammation. However, distinguishing pneumonitis from pneumonia is time-consuming and challenging. To fill this gap, we build an image-based tool, and further evaluate it clinically alongside relevant blood biomarkers. Materials and methods: We studied CT images from 97 patients with pneumonia and 29 patients with pneumonitis from acute myeloid leukemia treated with ICIs. We developed a CT-derived signature using a habitat imaging algorithm, whereby infected lungs are segregated into clusters ("habitats"). We validated the model and compared it with a clinical-blood model to determine whether imaging can add diagnostic value. Results: Habitat imaging revealed intrinsic lung inflammation patterns by identifying 5 distinct subregions, correlating to lung parenchyma, consolidation, heterogenous ground-glass opacity (GGO), and GGO-consolidation transition. Consequently, our proposed habitat model (accuracy of 79%, sensitivity of 48%, and specificity of 88%) outperformed the clinical-blood model (accuracy of 68%, sensitivity of 14%, and specificity of 85%) for classifying pneumonia versus pneumonitis. Integrating imaging and blood achieved the optimal performance (accuracy of 81%, sensitivity of 52% and specificity of 90%). Using this imaging-blood composite model, the post-test probability for detecting pneumonitis increased from 23% to 61%, significantly (p = 1.5E - 9) higher than the clinical and blood model (post-test probability of 22%). Conclusion: Habitat imaging represents a step forward in the image-based detection of pneumonia and pneumonitis, which can complement known blood biomarkers. Further work is needed to validate and fine tune this imaging-blood composite model and further improve its sensitivity to detect pneumonitis.

Incidence and Risk Factors for Pneumonitis Associated With Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer: A Single Center Experience.

INTRODUCTION: Immune checkpoint inhibitor (ICI) pneumonitis causes substantial morbidity and mortality. Estimates of real-world incidence and reported risk factors vary substantially. METHODS: We conducted a retrospective review of 419 patients with advanced non-small cell lung cancer (NSCLC) who were treated with anti-PD-(L)1 with or without anti-CTLA-4 therapy. Clinical, imaging, and microbiological data were evaluated by multidisciplinary adjudication teams. The primary outcome of interest was grade ≥2 (CTCAEv5) pneumonitis. Clinicopathologic variables, tobacco use, cancer therapies, and preexisting lung disease were assessed for univariate effects using Cox proportional hazards models. We created multivariate Cox proportional hazards models to assess risk factors for pneumonitis and mortality. Pneumonitis, pneumonia, and progression were modeled as time-dependent variables in mortality models. RESULTS: We evaluated 419 patients between 2013 and 2021. The cumulative incidence of pneumonitis was 9.5% (40/419). In a multivariate model, pneumonitis increased the risk for mortality (HR 1.6, 95% CI, 1.0-2.5), after adjustment for disease progression (HR 1.6, 95% CI, 1.4-1.8) and baseline shortness of breath (HR 1.5, 95% CI, 1.2-2.0). Incomplete resolution was more common with more severe pneumonitis. Interstitial lung disease was associated with higher risk for pneumonitis (HR 5.4, 95% CI, 1.1-26.6), particularly in never smokers (HR 26.9, 95% CI, 2.8-259.0). CONCLUSION: Pneumonitis occurred at a high rate and significantly increased mortality. Interstitial lung disease, particularly in never smokers, increased the risk for pneumonitis.

Neoadjuvant chemotherapy plus nivolumab with or without ipilimumab in operable non-small cell lung cancer: the phase 2 platform NEOSTAR trial.

Neoadjuvant ipilimumab + nivolumab (Ipi+Nivo) and nivolumab + chemotherapy (Nivo+CT) induce greater pathologic response rates than CT alone in patients with operable non-small cell lung cancer (NSCLC). The impact of adding ipilimumab to neoadjuvant Nivo+CT is unknown. Here we report the results and correlates of two arms of the phase 2 platform NEOSTAR trial testing neoadjuvant Nivo+CT and Ipi+Nivo+CT with major pathologic response (MPR) as the primary endpoint. MPR rates were 32.1% (7/22, 80% confidence interval (CI) 18.7-43.1%) in the Nivo+CT arm and 50% (11/22, 80% CI 34.6-61.1%) in the Ipi+Nivo+CT arm; the primary endpoint was met in both arms. In patients without known tumor EGFR/ALK alterations, MPR rates were 41.2% (7/17) and 62.5% (10/16) in the Nivo+CT and Ipi+Nivo+CT groups, respectively. No new safety signals were observed in either arm. Single-cell sequencing and multi-platform immune profiling (exploratory endpoints) underscored immune cell populations and phenotypes, including effector memory CD8+ T, B and myeloid cells and markers of tertiary lymphoid structures, that were preferentially increased in the Ipi+Nivo+CT cohort. Baseline fecal microbiota in patients with MPR were enriched with beneficial taxa, such as Akkermansia, and displayed reduced abundance of pro-inflammatory and pathogenic microbes. Neoadjuvant Ipi+Nivo+CT enhances pathologic responses and warrants further study in operable NSCLC. (ClinicalTrials.gov registration: NCT03158129 .).

Imaging of Lung Cancer Staging.

Lung cancer is a leading cause of cancer-related mortality worldwide. Imaging is integral in accurate clinical staging to stratify patients into groups to predict survival and determine treatment. The eighth edition of the tumor, node, and metastasis (TNM-8) staging system proposed by the International Association for the Study of Lung Cancer in 2016, accepted by both the Union for International Cancer Control and the American Joint Committee on Cancer, is the current standard method of staging lung cancer. This single TNM staging is used for all histologic subtypes of lung cancer, including nonsmall cell lung cancer, small cell lung cancer, and bronchopulmonary carcinoid tumor, and it addresses both clinical and pathologic staging. Familiarity with the strengths and limitations of imaging modalities used in staging, the nuances of TNM-8, its correct nomenclature, and potential pitfalls are important to optimize patient care. In this article, we discuss the role of computed tomography (CT) and positron emission tomography/CT in lung cancer staging, as well as current imaging recommendations pertaining to TNM-8.

Pearls and Pitfalls in Lung Cancer CT Screening.

Annual LDCT lung cancer screening is recommended by the United States Preventive Services Task Force (USPSTF) for high-risk population based on the results from the National Lung Cancer Screening Trial (NLST) that showed a significant (20%) reduction in lung cancer-specific mortality rate with the use of annual low-dose computed tomography (LDCT) screening. More recently, the benefits of lung cancer screening were confirmed by the Dutch- Belgian NELSON trial in Europe. With the implementation of lung screening in large scale, knowledge of the limitations related to false positive, false negative and other potential pitfalls is essential to avoid misdiagnosis. This review outlines the most common potential pitfalls in the characterization of screen-detected lung nodules that include artifacts in LDCT, benign nodules that mimic lung cancer, and causes of false negative evaluations of lung cancer with LDCT and PET/CT studies. Awareness of the spectrum of potential pitfalls in pulmonary nodule detection and characterization, including equivocal or atypical presentations, is important for avoiding misinterpretation that can alter patient management.

Invasive Fungal Pneumonia in Immunocompromised Patients.

Fungal pneumonia is the most frequent presentation of invasive fungal infections (IFIs) in patients with hematologic malignancies (HM) and hematopoietic stem cell transplantation (HSCT) recipients. The most common causes include Aspergillus, Mucor, Fusarium, and Candida species. The high incidence and high morbidity and mortality rate of fungal pneumonias in HM/HSCT populations arise from severe immune dysfunction that may be caused by both the underlying disease and/or its treatment. CT is routinely used when pulmonary complications are suspected after HSCT. Appropriate image interpretation of the posttransplant patient requires a combination of pattern recognition and knowledge of the clinical setting. In this article, we provide an overview of the clinical manifestations and CT imaging features of the most common invasive fungal pneumonias (IFPs) seen in severely immunosuppressed hosts.

Pneumonitis after immune checkpoint inhibitor therapies in patients with acute myeloid leukemia: A retrospective cohort study.

BACKGROUND: Immune checkpoint inhibitors (ICI), combined with hypomethylating agents, can be used to treat acute myeloid leukemia (AML), but this strategy results in a high rate of pneumonitis. The authors sought to determine risk factors for pneumonitis development and whether pneumonitis increased mortality. METHODS: The authors conducted a retrospective review of 258 AML patients who received ICI-containing regimens from 2016 to 2018. A multidisciplinary adjudication committee diagnosed pneumonia and pneumonitis by reviewing symptoms, imaging, microbiology, and response to therapies. To measure risk factors for pneumonitis and mortality, multivariate Cox proportional hazards models were constructed. Pneumonia, pneumonitis, and disease progression were modeled as a time-dependent variable and incorporated a standard risk set modifying variables into the models. RESULTS: Thirty patients developed pneumonitis (12%). Of these, 17 had partial or complete resolution, whereas 13 patients died from pneumonitis. Increasing age (hazard ratio [HR], 1.04 per year; 95% confidence interval [CI], 1.00-1.08), and baseline shortness of breath increased pneumonitis risk (HR, 2.51; 95% CI, 1.13-5.55). Female sex (HR, 0.33; 95% CI, 0.15-0.70) and increasing platelet count (HR, 0.52 per log-unit increase; 95% CI, 0.30-0.92) decreased pneumonitis risk. In adjusted models, ICI-related pneumonitis significantly increased mortality (HR, 2.84; 95% CI, 1.84-4.37). CONCLUSIONS: ICI-related pneumonitis occurs at a high rate in AML patients and increases mortality. LAY SUMMARY: Immune checkpoint inhibitors (ICIs) remove inhibitory signals that reduce T-cell function and allow T-cells to better attack cancer cells. In acute myeloid leukemia (AML), the effectiveness of ICIs is limited in part by inflammation of the lung, called pneumonitis. This study reviewed 258 patients with AML who received ICIs and identified 30 patients who developed pneumonitis, nearly half of whom died. Older age and baseline shortness of breath increased pneumonitis risk, whereas female sex and higher baseline platelet counts decreased pneumonitis risk. Pneumonitis increased mortality by nearly 3-fold. This work highlights the significant harm imposed by pneumonitis after ICI therapies.

Habitat Imaging Biomarkers for Diagnosis and Prognosis in Cancer Patients Infected with COVID-19.

OBJECTIVES: Cancer patients have worse outcomes from the COVID-19 infection and greater need for ventilator support and elevated mortality rates than the general population. However, previous artificial intelligence (AI) studies focused on patients without cancer to develop diagnosis and severity prediction models. Little is known about how the AI models perform in cancer patients. In this study, we aim to develop a computational framework for COVID-19 diagnosis and severity prediction particularly in a cancer population and further compare it head-to-head to a general population. METHODS: We have enrolled multi-center international cohorts with 531 CT scans from 502 general patients and 420 CT scans from 414 cancer patients. In particular, the habitat imaging pipeline was developed to quantify the complex infection patterns by partitioning the whole lung regions into phenotypically different subregions. Subsequently, various machine learning models nested with feature selection were built for COVID-19 detection and severity prediction. RESULTS: These models showed almost perfect performance in COVID-19 infection diagnosis and predicting its severity during cross validation. Our analysis revealed that models built separately on the cancer population performed significantly better than those built on the general population and locked to test on the cancer population. This may be because of the significant difference among the habitat features across the two different cohorts. CONCLUSIONS: Taken together, our habitat imaging analysis as a proof-of-concept study has highlighted the unique radiologic features of cancer patients and demonstrated effectiveness of CT-based machine learning model in informing COVID-19 management in the cancer population.

Nodal immune flare mimics nodal disease progression following neoadjuvant immune checkpoint inhibitors in non-small cell lung cancer.

Radiographic imaging is the standard approach for evaluating the disease involvement of lymph nodes in patients with operable NSCLC although the impact of neoadjuvant immune checkpoint inhibitors (ICIs) on lymph nodes has not yet been characterized. Herein, we present an ad hoc analysis of the NEOSTAR trial (NCT03158129) where we observed a phenomenon we refer to as "nodal immune flare" (NIF) in which patients treated with neoadjuvant ICIs demonstrate radiologically abnormal nodes post-therapy that upon pathological evaluation are devoid of cancer and demonstrate de novo non-caseating granulomas. Abnormal lymph nodes are analyzed by computed tomography and 18F-fluorodeoxyglucose positron emission tomography/computer tomography to evaluate the size and the maximum standard uptake value post- and pre-therapy in NEOSTAR and an independent neoadjuvant chemotherapy cohort. NIF occurs in 16% (7/44) of patients treated with ICIs but in 0% (0/28) of patients after neoadjuvant chemotherapy. NIF is associated with an inflamed nodal immune microenvironment and with fecal abundance of genera belonging to the family Coriobacteriaceae of phylum Actinobacteria, but not with tumor responses or treatment-related toxicity. Our findings suggest that this apparent radiological cancer progression in lymph nodes may occur due to an inflammatory response after neoadjuvant immunotherapy, and such cases should be evaluated by pathological examination to distinguish NIF from true nodal progression and to ensure appropriate clinical treatment planning.

Immune evolution from preneoplasia to invasive lung adenocarcinomas and underlying molecular features.

The mechanism by which anti-cancer immunity shapes early carcinogenesis of lung adenocarcinoma (ADC) is unknown. In this study, we characterize the immune contexture of invasive lung ADC and its precursors by transcriptomic immune profiling, T cell receptor (TCR) sequencing and multiplex immunofluorescence (mIF). Our results demonstrate that anti-tumor immunity evolved as a continuum from lung preneoplasia, to preinvasive ADC, minimally-invasive ADC and frankly invasive lung ADC with a gradually less effective and more intensively regulated immune response including down-regulation of immune-activation pathways, up-regulation of immunosuppressive pathways, lower infiltration of cytotoxic T cells (CTLs) and anti-tumor helper T cells (Th), higher infiltration of regulatory T cells (Tregs), decreased T cell clonality, and lower frequencies of top T cell clones in later-stages. Driver mutations, chromosomal copy number aberrations (CNAs) and aberrant DNA methylation may collectively impinge host immune responses and facilitate immune evasion, promoting the outgrowth of fit subclones in preneoplasia into dominant clones in invasive ADC.

Neoadjuvant nivolumab or nivolumab plus ipilimumab in operable non-small cell lung cancer: the phase 2 randomized NEOSTAR trial.

Ipilimumab improves clinical outcomes when combined with nivolumab in metastatic non-small cell lung cancer (NSCLC), but its efficacy and impact on the immune microenvironment in operable NSCLC remain unclear. We report the results of the phase 2 randomized NEOSTAR trial (NCT03158129) of neoadjuvant nivolumab or nivolumab + ipilimumab followed by surgery in 44 patients with operable NSCLC, using major pathologic response (MPR) as the primary endpoint. The MPR rate for each treatment arm was tested against historical controls of neoadjuvant chemotherapy. The nivolumab + ipilimumab arm met the prespecified primary endpoint threshold of 6 MPRs in 21 patients, achieving a 38% MPR rate (8/21). We observed a 22% MPR rate (5/23) in the nivolumab arm. In 37 patients resected on trial, nivolumab and nivolumab + ipilimumab produced MPR rates of 24% (5/21) and 50% (8/16), respectively. Compared with nivolumab, nivolumab + ipilimumab resulted in higher pathologic complete response rates (10% versus 38%), less viable tumor (median 50% versus 9%), and greater frequencies of effector, tissue-resident memory and effector memory T cells. Increased abundance of gut Ruminococcus and Akkermansia spp. was associated with MPR to dual therapy. Our data indicate that neoadjuvant nivolumab + ipilimumab-based therapy enhances pathologic responses, tumor immune infiltrates and immunologic memory, and merits further investigation in operable NSCLC.

Evolution of DNA methylome from precancerous lesions to invasive lung adenocarcinomas.

The evolution of DNA methylome and methylation intra-tumor heterogeneity (ITH) during early carcinogenesis of lung adenocarcinoma has not been systematically studied. We perform reduced representation bisulfite sequencing of invasive lung adenocarcinoma and its precursors, atypical adenomatous hyperplasia, adenocarcinoma in situ and minimally invasive adenocarcinoma. We observe gradual increase of methylation aberrations and significantly higher level of methylation ITH in later-stage lesions. The phylogenetic patterns inferred from methylation aberrations resemble those based on somatic mutations suggesting parallel methylation and genetic evolution. De-convolution reveal higher ratio of T regulatory cells (Tregs) versus CD8 + T cells in later-stage diseases, implying progressive immunosuppression with neoplastic progression. Furthermore, increased global hypomethylation is associated with higher mutation burden, copy number variation burden and AI burden as well as higher Treg/CD8 ratio, highlighting the potential impact of methylation on chromosomal instability, mutagenesis and tumor immune microenvironment during early carcinogenesis of lung adenocarcinomas.

18F-fluorodeoxyglucose positron emission tomography correlates with tumor immunometabolic phenotypes in resected lung cancer.

Enhanced tumor glycolytic activity is a mechanism by which tumors induce an immunosuppressive environment to resist adoptive T cell therapy; therefore, methods of assessing intratumoral glycolytic activity are of considerable clinical interest. In this study, we characterized the relationships among tumor 18F-fluorodeoxyglucose (FDG) retention, tumor metabolic and immune phenotypes, and survival in patients with resected non-small cell lung cancer (NSCLC). We retrospectively analyzed tumor preoperative positron emission tomography (PET) 18F-FDG uptake in 59 resected NSCLCs and investigated correlations between PET parameters (SUVMax, SUVTotal, SUVMean, TLG), tumor expression of glycolysis- and immune-related genes, and tumor-associated immune cell densities that were quantified by immunohistochemistry. Tumor glycolysis-associated immune gene signatures were analyzed for associations with survival outcomes. We found that each 18F-FDG PET parameter was positively correlated with tumor expression of glycolysis-related genes. Elevated 18F-FDG SUVMax was more discriminatory of glycolysis-associated changes in tumor immune phenotypes than other 18F-FDG PET parameters. Increased SUVMax was associated with multiple immune factors characteristic of an immunosuppressive and poorly immune infiltrated tumor microenvironment, including elevated PD-L1 expression, reduced CD57+ cell density, and increased T cell exhaustion gene signature. Elevated SUVMax identified immune-related transcriptomic signatures that were associated with enhanced tumor glycolytic gene expression and poor clinical outcomes. Our results suggest that 18F-FDG SUVMax has potential value as a noninvasive, clinical indicator of tumor immunometabolic phenotypes in patients with resectable NSCLC and warrants investigation as a potential predictor of therapeutic response to immune-based treatment strategies.

A Phase I/II Study of Neoadjuvant Cisplatin, Docetaxel, and Nintedanib for Resectable Non-Small Cell Lung Cancer.

PURPOSE: Nintedanib enhances the activity of chemotherapy in metastatic non-small cell lung cancer (NSCLC). In this phase I/II study, we assessed safety and efficacy of nintedanib plus neoadjuvant chemotherapy, using major pathologic response (MPR) as primary endpoint. PATIENTS AND METHODS: Eligible patients had stage IB (≥4 cm)-IIIA resectable NSCLC. A safety run-in phase was followed by an expansion phase with nintedanib 200 mg orally twice a day (28 days), followed by three cycles of cisplatin (75 mg/m2), docetaxel (75 mg/m2) every 21 days plus nintedanib, followed by surgery. With 33 planned patients, the study had 90% power to detect an MPR increase from 15% to 35%. RESULTS: Twenty-one patients (stages I/II/III, N = 1/8/12) were treated. One of 15 patients treated with nintedanib 200 mg achieved MPR [7%, 95% confidence interval (CI), 0.2%-32%]. Best ORR in 20 evaluable patients was 30% (6/20, 95% CI, 12%-54%). Twelve-month recurrence-free survival and overall survival were 66% (95% CI, 47%-93%) and 91% (95% CI, 79%-100%), respectively. Most frequent treatment-related grade 3-4 toxicities were transaminitis and electrolyte abnormalities. On the basis of an interim analysis the study was discontinued for futility. Higher levels of CD3+ and cytotoxic CD3+CD8+ T cells were found in treated tumors of patients who were alive than in those who died (652.8 vs. 213.4 cells/mm2, P = 0.048; 142.3 vs. 35.6 cells/mm2, P = 0.018). CONCLUSIONS: Although tolerated, neoadjuvant nintedanib plus chemotherapy did not increase MPR rate compared with chemotherapy historical controls. Additional studies of the combination in this setting are not recommended. Posttreatment levels of tumor-infiltrating T cells were associated with patient survival. Use of MPR facilitates the rapid evaluation of neoadjuvant therapies.See related commentary by Blakely and McCoach, p. 3499.

CT Signs in the Lungs.

Radiologic signs are often based on items or patterns that are encountered in everyday life. They are especially useful because their observation allows the differential diagnosis to be narrowed, and in some cases, enables a diagnosis to be made. In this review, several classic and newer computed tomography signs in the lungs are discussed.

Imaging of Pneumonias and Other Thoracic Complications After Hematopoietic Stem Cell Transplantation.

Hematopoietic stem cell transplantation (HSCT) is used in the treatment of various oncologic and hematologic diseases. After HSCT, patients are immunocompromised and are at risk for a wide variety of infectious and noninfectious complications. CT is routinely used when pulmonary complications are suspected after HSCT. In this article, we review the CT appearance of pulmonary complications that occur in the post-transplantation period with special emphasis on opportunistic infections, many of which are life-threatening.