RPS 1816 - Modern strategies in thoracic oncologic imaging

Author Block: A. Cicchetti¹, P. Vallerio¹, A. Catalano¹, C. Sangalli¹, L. Marrazzo², R. Tummineri¹, A. Botti³, F. Dionisi⁴, E. Gioscio¹; ¹Milan/IT, ²Firenze/IT, ³Reggio Emilia/IT, ⁴Rome/IT
Purpose: To assess whether baseline CT-derived cardiovascular and metabolic biomarkers can stratify intermediate-risk patients with locally advanced non-small cell lung cancer (LA-NSCLC) treated with chemoradiotherapy+immunotherapy, thereby supporting personalized follow-up strategies and identifying candidates for advanced cardiological imaging.
Methods or Background: Baseline CT-scans from 305 LA-NSCLC patients enrolled in four Italian centers were retrospectively analyzed. Two-year overall survival (OS2Y) was recorded. Image-derived features included the Agatston score, body composition metrics, aorta diameters, and percent Emphysema. Gross tumor volume (GTV) was contoured by experts and added to the analysis together with chemo/immune information. Automatic segmentation and feature extraction was performed using open-source tools and locally developed scripts.
A Random Forest classifier was trained following feature selection; SHAP values were used for feature importance interpretation, and UMAP+HDBSCAN clustering was applied to identify patient subgroups.
Results or Findings: OS2Y was 62%. Patients receiving chemoradiotherapy (66%) combined with immunotherapy were 34%.
Four distinct survival clusters were identified based on selected features(GTV, Visceral Fat, Hepatic Fat, Agatston score, and Emphysema):

Cluster1 (n=69) – OS2Y 83.6%: characterized by small tumor volumes and absence of imaging risk factors above the median.

Cluster2 (n=24) – OS2Y 62.5%: tumor volumes comparable to Cluster 1, but high torso fat, very-high Agatston score and hepatic fat.

Cluster3 (n=201) – OS2Y 59.7%: features around median values, representing the average population group.

Cluster4 (n=11) – OS2Y 11.1%: characterized by large GTV volumes and moderate-to-high emphysema.
Conclusion: This unsupervised clustering approach demonstrated the ability to identify patient subgroups with shared clinical characteristics but distinct risk profiles. Importantly, it highlighted a significant survival impact (cl1-cl2=21.1%) for patients with baseline cardiac calcifications, visceral and hepatic fat, underlining their potential role as prognostic imaging biomarkers to guide follow-up strategies.
Limitations: Lack of systematic cardiological test, retrospective analysis
Funding for this study: The study LOCATION MATTERS was funded by AIRC MFAG 27480
Has your study been approved by an ethics committee? Yes
Ethics committee - additional information: Num INT 36/23

Author Block: F. Sparascio¹, E. Versienti¹, L. Cereser¹, T. Nadarević², C. Ciancimino¹, A. P. Pace¹, G. Como¹, R. Girometti¹, C. Zuiani¹; ¹Udine/IT, ²Rijeka/HR
Purpose: To assess intra- and inter-reader agreement for Node-RADS v1.0 in mediastinal lymph node evaluation on chest CT in stage I–III non-small cell lung cancer (NSCLC) and determine its diagnostic performance.
Methods or Background: This retrospective, single-center study included 46 patients (38 adenocarcinomas, 8 squamous cell carcinomas) with 158 pathologically confirmed mediastinal lymph nodes (22 malignant, 136 benign). A contrast- enhanced chest CT scan was available for all patients. Four radiologists (two experts, two juniors) independently assigned Node-RADS scores and descriptors (“size” and
“configuration”) in two sessions, three weeks apart. Intra- and inter-reader agreement were assessed using Gwet’s AC2. Diagnostic performance was assessed by ROC analysis; sensitivity, specificity, and predictive values were calculated at a Node-RADS score ≥3 threshold.
Results or Findings: Inter-reader agreement for Node-RADS scores was almost perfect for experts (Gwet’s AC2 = 0.97; 95% CI: 0.96–0.99) and juniors (Gwet’s AC2 = 0.95; 95% CI: 0.93–0.97). Intra-reader agreement Gwet’s AC2 values ranged from 0.95–0.99. Descriptor agreement was similarly high (Gwet’s AC2 ≥ 0.85). ROC AUCs ranged from 0.71–0.76 for experts and 0.68–0.84 for juniors. At the ≥3 threshold, specificity and negative predictive value were consistently ≥90%, while sensitivity remained limited (<64%) for all readers.
Conclusion: Node-RADS v1.0 shows excellent reproducibility across radiologists with different expertise for mediastinal lymph node assessment on CT in stage I–III NSCLC. Its high specificity and negative predictive value suggest a supportive role in excluding malignancy, although limited sensitivity warrants cautious interpretation and complementary diagnostic assessment.
Limitations: Single-center and retrospective study.
Funding for this study: No funding was received for this study.
Has your study been approved by an ethics committee? Yes
Ethics committee - additional information: This retrospective study has been approved by the Institutional Review Board (IRB) of the Department of Medicine, University of Udine. Study protocol code: 019/2025. Approval date: 15/01/2025.

Author Block: W. Yang, Q. Feng, X. Chen, X. Xin; Nanjing/CN
Purpose: This study evaluated the potential of spectral image-based histogram features for early assessment of immunotherapy response in advanced lung cancer.
Methods or Background: Thirty-five patients who underwent baseline and follow-up spectral contrast-enhanced CT scans before and during immunotherapy were retrospectively analyzed. Treatment response at the 4th follow-up was determined using RECIST 1.1 and categorized as response (CR, PR) or non-response (SD, PD). Spectral image series-including conventional images, 40/70 keV virtual monoenergetic images (VMI), iodine density, effective atomic number, electron density, and water/iodine-based maps-were reconstructed in arterial and venous phases. VMI-40 keV images were used for 3D semi-automatic lesion segmentation, and first-order histogram features were extracted. Features were standardized with Z-scores, and significant predictors were identified by Mann-Whitney U-test. Logistic regression models were built, and discriminatory ability was evaluated with ROC AUC; AUC differences were compared with the DeLong test.
Results or Findings: Based on RECIST 1.1, 2 patients achieved CR, 23 PR, 9 SD, and 1 PD. From baseline spectral data, three histogram features distinguished response from non-response with an AUC of 0.796. When combining baseline and first follow-up data, three features achieved an improved AUC of 0.852. No predictive features were identified from conventional images.
Conclusion: Histogram features derived from spectral CT, particularly when incorporating both baseline and early follow-up data, show promise for early prediction of immunotherapy response in advanced lung cancer patients.
Limitations: Sample size is small.
Funding for this study: Not applicable
Has your study been approved by an ethics committee? Yes
Ethics committee - additional information: This study was approved by the Institutional Ethics Committee. The requirement for informed consent was waived due to the retrospective nature of the analysis.

Author Block: H. W. Phillips¹, P. Marra¹, A. Smedile², M. Bertuletti², C. Gargiulo¹, K. D. Martins De Mattos¹, P. A. Bonaffini², G. Muscogiuri², S. Sironi¹; ¹Milan/IT, ²Bergamo/IT
Purpose: Lung cancer screening of at-risk individuals remains under investigation, with heterogeneous results being expected due to local environmental and epidemiological factors. We present the preliminary experience of the experimental low-dose chest CT screening campaign at a single Italian centre.
Methods or Background: Eligibility criteria include age (55-75) and positive smoking-history (≥30 pack years, active or cessation within the last 15 years) with follow-up imaging at variable intervals based on Lung-RADS 1.1 (2019) risk stratification. Suspect nodules underwent further evaluation following specialist review, often 18FDG-PET, biopsy and/or surgical excision. A review of all lung and collateral oncological findings in the study population was performed.
Results or Findings: From 11/02/23, 796 individuals have been imaged, with 593 having a second scan by 30/06/25. 16 diagnoses of NSCLC (2% detection rate) have been made, all categorised as LR4 (sensitivity 100%, specificity 89.5%, PPV 16.3%, NPV 100%), 15/16 at initial CT. All underwent 18FDG-PET (seven positive, nine nonspecific), 12 were biopsied (nine CT-guided, three by EBUS-TBNA) whilst four proceeded directly to surgery. Initial CT also identified 56 others with LR4 nodules, 19 of whom were evaluated by 18FDG-PET. Four had EBUS-TBNA biopsies whilst three were directly excised. Follow-up scans showed evolution to LR4 in 26 others, resulting in six 18FDG-PET scans, one EBUS-TBNA biopsy and one excision. During the project, 17 participants were diagnosed with extra-pulmonary malignancies, seven as a result of their screening CT: two thyroid, two breast, one tonsillar, one lymphoma and one thymoma.
Conclusion: Lung cancer screening at a national level and its potential to provide earlier detection seems valuable, though false positives and resultant investigations deserve consideration.
Limitations: Limitations include provisional data use, cohort factors with strict eligibility criteria, compliance and imaging interpretation, particularly of slow growing malignancies.
Funding for this study: None.
Has your study been approved by an ethics committee? Yes
Ethics committee - additional information: Data obtained from a national multicentre prospective study.

Author Block: Y. Li¹, X. Yang¹, P. Wang², W. Meng¹; ¹Harbin/CN, ²Beijing/CN
Purpose: This study aimed to quantify intratumoural heterogeneity (ITH) to preoperatively predict the spread through air spaces (STAS) status of lung adenocarcinoma (LUAD) and further explore the potential biological basis underlying the prediction model.
Methods or Background: STAS is an aggressive pattern of primary LUAD that affects both prognosis and treatment strategies for patients. In our study, conventional radiomics features and habitat features were extracted from intratumoural and peritumoural regions on preoperative CT images. A new index, the ITH score, was developed to quantify ITH. Clinical-radiologic characteristics associated with STAS were identified by multivariable logistic regression analyses. Additionally, intratumoural-peritumoural habitat features, ITH score, and clinical-radiologic characteristics were integrated into a combined model by various machine learning algorithms. Finally, 24 patients with RNA sequencing data were utilised for gene expression analysis.
Results or Findings: A total of 1268 patients (median age, 60 years; IQR, 53.8–66.0 years; 850 female) were divided into the training set (n=943), validation set (n=236), and external test set (n=89). Using the Light Gradient Boosting Machine classifier, the combined model demonstrated the highest predictive performance for STAS, achieving an AUC value of 0.97 in the training, 0.98 in the validation, and 0.91 in the external test set. Differentially expressed genes in high probability group were associated with monocarboxylic acid transport and metabolism.
Conclusion: The combined model demonstrated superior performance in predicting STAS in primary LUAD.
Limitations: First, its retrospective design may introduce bias, and further prospective studies are needed to validate the model's accuracy. Second, manual tumor delineation by different radiologists could affect the consistency of radiomic features, so future research should prioritize automated segmentation methods. Third, the limited RNA-seq sample size may weaken biological validation, and larger, more diverse cohorts are needed in future studies.
Funding for this study: This study was supported by the Scientific and Technological Innovation 2030-New Generation Artificial Intelligence Project of the National Key Research and Development Program of China, the National Natural Science Foundation of China, and the Climbing Fund of the National Cancer Center.
Has your study been approved by an ethics committee? Yes
Ethics committee - additional information: Ky2024-104

Author Block: P. Eckwolf, D. Kifjak, H. Prosch, L. Beer; Wien/AT
Purpose: To assess whether quantitative 18F-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography/computed tomography (PET/CT) parameters improve preoperative thoracic lymph node (LN) staging accuracy in non-small-cell lung cancer (NSCLC).
Methods or Background: Thirty-eight treatment-naïve patients (mean age 67 ± 9 years) with confirmed NSCLC (29 adenocarcinoma [76.3%], 8 squamous cell carcinoma [21.1%], 1 large cell carcinoma [2.6%]) underwent pre-interventional long field-of-view 18F-FDG PET/CT. A total of 149 thoracic LN were sampled intraoperatively, by transbronchial needle aspiration (TBNA), or both. PET metrics included maximum, peak, and mean standardized uptake value (SUVmax, SUVpeak, SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG).
Results or Findings: Twelve patients (32%) had metastatic thoracic LN (19/149, 12.8%). Metastatic LN were significantly larger (P=0.013) and more metabolically active (P<0.001) than non-metastatic nodes. ROC analysis showed the best diagnostic performance for SUVmax and SUVpeak (AUC 0.86 and 0.862). Using a sensitivity-optimized SUVmax cutoff of 2.82 yielded a negative predictive value (NPV) of 98%, moderate positive predictive value (PPV, 38%), and overall accuracy of 80%. False positives included reactive LN with SUVmax up to 12, limiting PPV despite high NPV.
Conclusion: Quantitative 18F-FDG PET/CT, particularly SUVmax and SUVpeak, enables highly reliable exclusion of thoracic LN metastasis in NSCLC, with excellent NPV for nodes showing low FDG uptake. However, positive findings remain nonspecific and require histopathological confirmation.
Limitations: Retrospective single-center design and modest sample size.
Funding for this study: The financial support by the Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development and the Christian Doppler Research Association is gratefully acknowledged.
Has your study been approved by an ethics committee? Yes
Ethics committee - additional information: Ethic committee number: 1187/2025

Author Block: E. Suderland, G. J. Schmid; Neuss/DE
Purpose: To evaluate feasibility, safety, and local tumour control after CT-guided percutaneous cryoablation of primary and metastatic lung cancer.
Methods or Background: This retrospective single-center study included 29 patients (11 men, 18 women; mean age 67.8 years) with 33 pulmonary lesions ≤3 cm treated between 2012 and 2025. Mean lesion size was 17.3 mm (range 7-30 mm). Eight lesions represented primary lung cancer (1 SCLC, 1 SCC, 6 Adenocarcinomas), and 25 metastases (14 colorectal, 4 breast, 3 uterine, 4 others). Cryoablation was performed under general anaesthesia with CT-guidance. The cryoablation protocol usually consisted of 3 freezing cycles of 3/7/10 minutes, followed by passive and active thawing. Depending on tumor size and location 1-3 cryoprobes were used. Chest tubes were placed during or after treatment in cases of pneumothorax. Treatment decisions were approved by a multidisciplinary tumour board and oncologic consultation.
Results or Findings: Initial technical success was 100%. No major adverse events occured. Minor complications included 18 peri-interventional pneumothoraces and 6 post-interventional pneumothoraces; in total, 18 chest tubes were placed. Additional minor events were perifocal bleeding, post-procedural haemoptysis and pneumonia. Mean hospital stay was 4.2 days (SD 2.1). After a mean follow-up of 14.7 months (SD 13.6), 21 lesions showed local tumor control, 6 showed progression and for 6 lesions follow-up was not available.
Conclusion: CT-guided cryoablation is safe and effective for selected primary and secondary lung tumours, achieving high technical success with low complication rates and good intermediate local tumor control.
Limitations: The study is limited by its retrospective, single-centre design and the relatively small patient cohort. In 6 cases follow-up was missing to fully assess local tumour control.
Funding for this study: No funding was received for this study.
Has your study been approved by an ethics committee? Not applicable
Ethics committee - additional information: