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Background: Radiomics is a quantitative approach that allows the extraction of mineable data from medical images. Despite the growing clinical interest, radiomics studies are affected by variability stemming from analysis choices. We aimed to investigate the agreement between two open-source radiomics software for both contrast-enhanced computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) of lung cancers and to preliminarily evaluate the existence of radiomic features stable for both techniques. Methods: Contrast-enhanced CT and MRI images of 35 patients affected with non-small cell lung cancer (NSCLC) were manually segmented and preprocessed using three different methods. Sixty-six Image Biomarker Standardisation Initiative-compliant features common to the considered platforms, PyRadiomics and LIFEx, were extracted. The correlation among features with the same mathematical definition was analyzed by comparing PyRadiomics and LIFEx (at fixed imaging technique), and MRI with CT results (for the same software). Results: When assessing the agreement between LIFEx and PyRadiomics across the considered resampling, the maximum statistically significant correlations were observed to be 94% for CT features and 95% for MRI ones. When examining the correlation between features extracted from contrast-enhanced CT and MRI using the same software, higher significant correspondences were identified in 11% of features for both software. Conclusions: Considering NSCLC, (i) for both imaging techniques, LIFEx and PyRadiomics agreed on average for 90% of features, with MRI being more affected by resampling and (ii) CT and MRI contained mostly non-redundant information, but there are shape features and, more importantly, texture features that can be singled out by both techniques. Relevance statement: Identifying and selecting features that are stable cross-modalities may be one of the strategies to pave the way for radiomics clinical translation. Key points: • More than 90% of LIFEx and PyRadiomics features contain the same information. • Ten percent of features (shape, texture) are stable among contrast-enhanced CT and MRI. • Software compliance and cross-modalities stability features are impacted by the resampling method. [ABSTRACT FROM AUTHOR]

Simple Summary: T1 and T2 mapping are MRI techniques that are routinely used in the evaluation of both benign and malignant lesions in different organs and tissues. Immunohistochemical analysis is the gold standard method to assess the programmed death-ligand 1 protein (PD-L1) expression status in patients diagnosed with non-small cell lung cancer (NSCLC) to guide immunotherapy. There have been no studies on the correlation between T1 and T2 mapping values and PD-L1 expression of NSCLCs nor on the correlation between T2 mapping values and histological subtypes of lung tumors. Therefore, we present our preliminary results on the evaluation of the possible association of T1 and T2 mapping values with PD-L1 TPS and of their potential in distinguishing between the different histological subtypes of NSCLCs. In the future, T1 values could offer the possibility to help in the diagnosis and pathological classification of NSCLC through a non-invasive MRI exam. We investigated the association of T1/T2 mapping values with programmed death-ligand 1 protein (PD-L1) expression in lung cancer and their potential in distinguishing between different histological subtypes of non-small cell lung cancers (NSCLCs). Thirty-five patients diagnosed with stage III NSCLC from April 2021 to December 2022 were included. Conventional MRI sequences were acquired with a 1.5 T system. Mean T1 and T2 mapping values were computed for six manually traced ROIs on different areas of the tumor. Data were analyzed through RStudio. Correlation between T1/T2 mapping values and PD-L1 expression was studied with a Wilcoxon–Mann–Whitney test. A Kruskal–Wallis test with a post-hoc Dunn test was used to study the correlation between T1/T2 mapping values and the histological subtypes: squamocellular carcinoma (SCC), adenocarcinoma (ADK), and poorly differentiated NSCLC (PD). There was no statistically significant correlation between T1/T2 mapping values and PD-L1 expression in NSCLC. We found statistically significant differences in T1 mapping values between ADK and SCC for the periphery ROI (p-value 0.004), the core ROI (p-value 0.01), and the whole tumor ROI (p-value 0.02). No differences were found concerning the PD NSCLCs. [ABSTRACT FROM AUTHOR]

Simple Summary: Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) is an advanced magnetic resonance imaging (MRI) technique able to distinguish true diffusion from microcirculation-related perfusion without the use of contrast medium. Immunohistochemical analysis is the gold standard method to assess the programmed death-ligand 1 protein (PD-L1) expression status in patients affected by non-small cell lung cancer (NSCLC) to guide immunotherapy. We present our preliminary results on the evaluation of IVIM-DWI parameters and their correlation with the PD-L1 expression status in patients affected by stage III NSCLC. Since PD-L1 expression is very heterogeneous in NSCLCs, and an invasive biopsy of the tumor is necessary for immunohistochemical analysis, a non-invasive alternative method to quantify PD-L1 expression should be considered to provide information on the whole tumor. In the future, IVIM-DWI parameters could offer the possibility to perform diagnosis, pathological classification, to guide therapy, and to assess therapeutic responses. This study aims to investigate the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in magnetic resonance imaging (MRI) and programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC). Twenty-one patients diagnosed with stage III NSCLC from April 2021 to April 2022 were included. The tumors were distinguished into two groups: no PD-L1 expression (<1%), and positive PD-L1 expression (≥1%). Conventional MRI and IVIM-DWI sequences were acquired with a 1.5-T system. Both fixed-size ROIs and freehand segmentations of the tumors were evaluated, and the data were analyzed through a software using four different algorithms. The diffusion (D), pseudodiffusion (D*), and perfusion fraction (pf) were obtained. The correlation between IVIM parameters and PD-L1 expression was studied with Pearson correlation coefficient. The Wilcoxon–Mann–Whitney test was used to study IVIM parameter distributions in the two groups. Twelve patients (57%) had PD-L1 ≥1%, and 9 (43%) <1%. There was a statistically significant correlation between D* values and PD-L1 expression in images analyzed with algorithm 0, for fixed-size ROIs (189.2 ± 65.709 µm²/s × 104 in no PD-L1 expression vs. 122.0 ± 31.306 µm²/s × 104 in positive PD-L1 expression, p = 0.008). The values obtained with algorithms 1, 2, and 3 were not significantly different between the groups. The IVIM-DWI MRI parameter D* can reflect PD-L1 expression in NSCLC. [ABSTRACT FROM AUTHOR]

Introduction: Radiomics extracts a large amount of quantitative information from medical images using specific data characterization algorithms. This information, called radiomic features, can be combined with clinical data to build prediction models for prognostic evaluation and treatment selection.Areas covered: We outlined a series of studies investigating the correlation between radiomics features and outcome (prognostic) as well as response to therapy (predictive) in non-small cell lung cancer (NSCLC). We performed our analysis both in the setting of early and advanced stage of disease, with a focus on the different therapies and imaging modalities adopted.Expert opinion: The prognostic and predictive potential of the radiomic approach, combined with clinical models, could help decision-making process and guide toward the creation of an optimal and 'tailored' therapeutic strategy for lung cancer patients. However, due to the low reproducibility of most of the conducted studies and the lack of validated results, such a desirable scenario has not yet been translated to routine clinical practice. [ABSTRACT FROM AUTHOR]

Objective: The main challenge of screening a healthy population with low-dose computed tomography is to balance the excessive use of diagnostic procedures with the risk of delayed cancer detection. We evaluated the pitfalls, difficulties, and sources of mistakes in the management of lung nodules detected in volunteers in the Cosmos single-center screening trial. Methods: A total of 5201 asymptomatic high-risk volunteers underwent screening with multidetector low-dose computed tomography. Nodules detected at baseline or new nodules at annual screening received repeat low-dose computed tomography at 1 year if less than 5 mm, repeat low-dose computed tomography 3 to 6 months later if between 5 and 8 mm, and fluorodeoxyglucose positron emission tomography if more than 8 mm. Growing nodules at the annual screening received low-dose computed tomography at 6 months and computed tomography-positron emission tomography or surgical biopsy according to doubling time, type, and size. Results: During the first year of screening, 106 patients underwent lung biopsy and 91 lung cancers were identified (70% were stage I). Diagnosis was delayed (false-negative) in 6 patients (stage IIB in 1 patient, stage IIIA in 3 patients, and stage IV in 2 patients), including 2 small cell cancers and 1 central lesion. Surgical biopsy revealed benign disease (false-positives) in 15 cases (14%). Positron emission tomography sensitivity was 88% for prevalent cancers and 70% for cancers diagnosed after first annual screening. No needle biopsy procedures were performed in this cohort of patients. Conclusion: Low-dose computed tomography screening is effective for the early detection of lung cancers, but nodule management remains a challenge. Computed tomography-positron emission tomography is useful at baseline, but its sensitivity decreases significantly the subsequent year. Multidisciplinary management and experience are crucial for minimizing misdiagnoses. [Copyright &y& Elsevier]

Summary: Background: Indeterminate non-calcified lung nodules are frequent when low-dose spiral computed tomography (LD-CT) is used for lung cancer screening. We assessed the diagnostic utility of a non-invasive work-up protocol for nodules detected at baseline in volunteers enrolled in our single-centre screening trial, and followed for at least 1 year. Methods: 5201 high-risk volunteers, recruited over 1 year from October 2004, underwent baseline LD-CT; 4821 (93%) returned for the first repeat LD-CT. Nodules ≤5mm underwent repeat LD-CT at 1 year; nodules 5.1–8mm underwent LD-CT 3 months later; lesions >8mm received combined CT-positron emission tomography (CT-PET). A subset of nodules >8mm was studied by CT with contrast. Protocol failures were delayed diagnosis with disease progression beyond stage I, and negative surgical biopsy. Results: 2754 (53%) volunteers presented one or more non-calcified nodules. Ninety-two lung cancers were diagnosed: 55 at baseline and 37 at annual screening (66% stage I). Among the 37 incident cancers, 17 had a baseline nodule that remained stage I, 7 had a baseline nodule that progressed beyond stage I, and 13 presented a new malignant nodule. Baseline and annual cancers were 79 (1.5%) and 13 (0.2%), respectively. In 15 of 104 (14%) invasive diagnostic procedures, the lesion was benign. Sensitivity, and specificity were 91 and 99.7%, respectively, for the entire protocol; 88 and 93% for CT-PET; and 100 and 59% for CT with contrast. Conclusions: The protocol limits invasive diagnostic procedures while few patients have diagnosis delay, supporting the feasibility of lung cancer screening in high-risk subjects by LD-CT. Nevertheless further optimization of the clinical management of screening-detected nodules is necessary. [Copyright &y& Elsevier]