In an era where early detection of diseases is paramount, integrating artificial intelligence (AI) into routine lung cancer screening offers a groundbreaking approach to simultaneously uncover multiple health conditions from a single scan. The fact that lung cancer is still the most common cause of cancer-related deaths globally emphasizes how important early detection is to raising survival rates. Traditional low dose computed tomography (LDCT) focuses primarily on identifying lung malignancies, often missing the opportunity to detect other clinically relevant biomarkers. This review explores the expanding role of AI in radiology, where AI-driven algorithms can simultaneously detect multiple biomarkers and composite health measures, facilitating the opportunistic identification of conditions beyond lung cancer. These include musculoskeletal disorders, cardiovascular diseases, pulmonary conditions, hepatic steatosis, and malignancies in the adrenal and thyroid glands, as well as breast tissue. Through an extensive review of current literature sourced from PubMed, the review highlights advancements in AI-driven biomarker detection, evaluates the potential benefits of a broader diagnostic approach, and addresses challenges related to model standardization and clinical integration. AI-enhanced LDCT screening shows significant promise in augmenting routine screenings, potentially advancing early detection, comprehensive patient assessments, and overall disease management across multiple health conditions.

This study analyzed the impact of liver cirrhosis on cardiac structure, function, tissue characteristics, and stress perfusion using cardiac magnetic resonance (CMR) imaging. Fifty patients with liver cirrhosis and 25 matched, healthy controls received a 3-T CMR exam. Left and right ventricular (LV, RV) and atrial (LA, RA) volumes and functions were analyzed, including ejection fraction (EF), and feature tracking strain analysis. T1/T2 relaxation times and extracellular volume (ECV) were determined. Patients with cirrhosis showed a higher LVEF (66.6 ± 5.8 vs. 59.6 ± 4.5

To investigate breast cancer therapy-related myocardial cardiotoxicity by analyzing right ventricular (RV), left atrial (LA), and right atrial (RA) function using cardiovascular magnetic resonance feature tracking (CMR-FT). This prospective single-center study involved 38 female breast cancer patients with a mean age of 50 ± 11 years, who received systemic anthracycline chemotherapy. CMR was performed in all patients before initiating therapy (at baseline (BL)) and after a 12-month follow-up (FU). FT was utilized to evaluate the RV global longitudinal (GLS), radial (GRS), and circumferential strain (GCS), as well as the biatrial reservoir, booster, and conduit strain. Paired t-tests were used to assess the differences in strain values from BL to FU. The mean RV GLS of all patients was significantly attenuated at FU compared to BL (−25.2 ± 3.9

To determine the influence of arterial hypertension (AHT), sex, and the interaction between both left- and right ventricular (LV, RV) morphology, function, and tissue characteristics. The Hamburg City Health Study (HCHS) is a population-based, prospective, monocentric study. 1972 individuals without a history of cardiac diseases/ interventions underwent 3 T cardiac MR imaging (CMR). Generalized linear models were conducted, including AHT, sex (and the interaction if significant), age, body mass index, place of birth, diabetes mellitus, smoking, hyperlipoproteinemia, atrial fibrillation, and medication. Of 1972 subjects, 68

The purpose of this study was to determine if dual-energy CT (DECT) vital iodine tumor burden (ViTB), a direct assessment of tumor vascularity, allows reliable response assessment in patients with GIST compared to established CT criteria such as RECIST1.1 and modified Choi (mChoi). From 03/2014 to 12/2019, 138 patients (64 years [32-94 years]) with biopsy proven GIST were entered in this prospective, multi-center trial. All patients were treated with tyrosine kinase inhibitors (TKI) and underwent pre-treatment and follow-up DECT examinations for a minimum of 24 months. Response assessment was performed according to RECIST1.1, mChoi, vascular tumor burden (VTB) and DECT ViTB. A change in therapy management could be because of imaging (RECIST1.1 or mChoi) and/or clinical progression. The DECT ViTB criteria had the highest discrimination ability for progression-free survival (PFS) of all criteria in both first line and second line and thereafter treatment, and was significantly superior to RECIST1.1 and mChoi (p < .034). Both, the mChoi and DECT ViTB criteria demonstrated a significantly early median time-to-progression (both delta 2.5 months; both p < .036). Multivariable analysis revealed 6 variables associated with shorter overall survival: secondary mutation (HR = 4.62), polymetastatic disease (HR = 3.02), metastatic second line and thereafter treatment (HR = 2.33), shorter PFS determined by the DECT ViTB criteria (HR = 1.72), multiple organ metastases (HR = 1.51) and lower age (HR = 1.04). DECT ViTB is a reliable response criteria and provides additional value for assessing TKI treatment in GIST patients. A significant superior response discrimination ability for median PFS was observed, including non-responders at first follow-up and patients developing resistance while on therapy.

PURPOSE:This scoping review aimed to assess the current research on artificial intelligence (AI)--enhanced opportunistic screening approaches for stratifying osteoporosis and osteopenia risk by evaluating vertebral trabecular bone structure in CT scans. METHODS:PubMed, Scopus, and Web of Science databases were systematically searched for studies published between 2018 and December 2023. Inclusion criteria encompassed articles focusing on AI techniques for classifying osteoporosis/osteopenia or determining bone mineral density using CT scans of vertebral bodies. Data extraction included study characteristics, methodologies, and key findings. RESULTS:Fourteen studies met the inclusion criteria. Three main approaches were identified: fully automated deep learning solutions, hybrid approaches combining deep learning and conventional machine learning, and non-automated solutions using manual segmentation followed by AI analysis. Studies demonstrated high accuracy in bone mineral density prediction (86-96%) and classification of normal versus osteoporotic subjects (AUC 0.927-0.984). However, significant heterogeneity was observed in methodologies, workflows, and ground truth selection. CONCLUSIONS:The review highlights AI's promising potential in enhancing opportunistic screening for osteoporosis using CT scans. While the field is still in its early stages, with most solutions at the proof-of-concept phase, the evidence supports increased efforts to incorporate AI into radiologic workflows. Addressing knowledge gaps, such as standardizing benchmarks and increasing external validation, will be crucial for advancing the clinical application of these AI-enhanced screening methods. Integration of such technologies could lead to improved early detection of osteoporotic conditions at a low economic cost.

Medical three-dimensional (3D) printing is playing an increasingly important role in clinical practice. The use of 3D printed models in patient care offers a wide range of possibilities in terms of personalized medicine, training and education of medical professionals, and communication with patients. DICOM files from imaging modalities such as CT and MRI provide the basis for the majority of the 3D models in medicine. The image acquisition, processing, and interpretation of these lies within the responsibility of radiology, which can therefore play a key role in the application and further development of 3D printing.The purpose of this review article is to provide an overview of the principles of 3D printing in medicine and summarize its most important clinical applications. It highlights the role of radiology as central to developing and administering 3D models in everyday clinical practice.This is a narrative review article on medical 3D printing that incorporates expert opinions based on the current literature and practices from our own medical centers.While the use of 3D printing is becoming increasingly established in many medical specialties in Germany and is finding its way into everyday clinical practice, centralized "3D printing labs" are a rarity in Germany but can be found internationally. These labs are usually managed by radiology departments, as radiology is a connecting discipline that - thanks to the imaging technology used to produce data for 3D printing - can play a leading role in the application of medical 3D printing. Copying this approach should be discussed in Germany in order to efficiently use the necessary resources and promote research and development in the future. · 3D printing in medicine is a rapidly growing field.. · Image acquisition and processing provides an important basis for high-quality 3D models.. · Radiology, as the specialist discipline responsible for imaging, has a crucial role to play.. · Radiology should play a leading role in the introduction of 3D printing in everyday clinical practice. . · Streckenbach A, Schubert N, Streckenbach F et al. Current State and Outlook in Medical 3 D Printing and the Role of Radiology. Fortschr Röntgenstr 2024; DOI 10.1055/a-2436-7185.

Abstract Background  Spectral CT is gaining increasing clinical importance with multiple potential applications, including oncological imaging. Spectral CT-specific image data offers multiple advantages over conventional CT image data through various post-processing algorithms, which will be highlighted in the following review. Methodology  The purpose of this review article is to provide an overview of potential useful oncologic applications of spectral CT and to highlight specific spectral CT pitfalls. The technical background, clinical advantages of primary and follow-up spectral CT exams in oncology, and the application of appropriate spectral tools will be highlighted. Results/Conclusions  Spectral CT imaging offers multiple advantages over conventional CT imaging, particularly in the field of oncology. The combination of virtual native and low monoenergetic images leads to improved detection and characterization of oncologic lesions. Iodine-map images may provide a potential imaging biomarker for assessing treatment response. Key Points: The most important spectral CT reconstructions for oncology imaging are virtual unenhanced, iodine map, and virtual monochromatic reconstructions. The combination of virtual unenhanced and low monoenergetic reconstructions leads to better detection and characterization of the vascularization of solid tumors. Iodine maps can be a surrogate parameter for tumor perfusion and potentially used as a therapy monitoring parameter. For radiotherapy planning, the relative electron density and the effective atomic number of a tissue can be calculated. Citation Format Sauerbeck J, Adam G, Meyer M. Onkologische Bildgebung mittels Spektral-CT. Fortschr Röntgenstr 2023; 195: 21 – 29 Zusammenfassung Hintergrund  Die Spektral-CT gewinnt mit vielfältigen Einsatzmöglichen zunehmend an klinischer Bedeutung, so auch im Rahmen der onkologischen Bildgebung. Die Spektral-CT-spezifischen Bilddaten bieten durch verschiedene Nachbearbeitungsalgorithmen vielfältige Vorteile gegenüber konventionellen CT-Bilddaten, was im folgenden Review genauer beleuchtet werden soll. Methodik  Der vorliegende Review-Artikel soll einen Überblick über die potenziell nützlichsten onkologischen Anwendungsgebiete der Spektral-CT geben und auf spezifische Spektral-CT-Fallstricke hinweisen. Hierbei werden sowohl technische Hintergründe als auch klinische Vorteile von onkologischen Primär- und Verlaufsuntersuchungen mittels Spektral-CT beleuchtet und die Anwendung entsprechender Spektral-Tools erläutert. Ergebnisse/Schlussfolgerungen  Die Spektral-CT-Bildgebung bietet vielfältige Vorteile gegenüber der konventionellen CT-Bildgebung, insbesondere auf dem Gebiet der Onkologie. Die Kombination von virtuell nativen und niedrigenergetischen Bildern führt zu einer verbesserten Detektion und Charakterisierung von Tumorläsionen. Jodkarten-Bilder bieten einen potenziellen Imaging-Biomarker zur Beurteilung des Therapieansprechens. Kernaussagen   Die wichtigsten Spektral-CT-Rekonstruktionen für die onkologische Bildgebung sind die virtuell nativen, Jodkarten- und virtuelle monochromatische Rekonstruktionen. Die Kombination aus virtuell nativen und niedrigenergetischen Bildern führt zu einer verbesserten Detektion und Charakterisierung von vaskularisierten und nicht vaskularisierten Läsionen. Jodkarten können ein Surrogatparameter für die Tumorperfusion sein und potenziell als Therapie-Monitoring-Parameter verwendet werden. Für die Strahlentherapie-Planung lassen sich die relative Elektronendichte und die effektive Ordnungszahl eines Gewebes berechnen. Zitierweise Sauerbeck J, Adam G, Meyer M. Spectral CT in Oncology. Fortschr Röntgenstr 2023; 195: 21 – 29

Parametric cardiac magnetic resonance (CMR) techniques have improved the diagnosis of pathologies. However, the primary tool for differentiating non-ST elevation myocardial infarction (NSTEMI) from myocarditis is still a visual assessment of conventional signal-intensity-based images. This study aimed at analyzing the ability of parametric compared to conventional techniques to visually differentiate ischemic from non-ischemic myocardial injury patterns. Twenty NSTEMI patients, twenty infarct-like myocarditis patients, and twenty controls were examined using cine, T2-weighted CMR (T2w) and late gadolinium enhancement (LGE) imaging and T1/T2 mapping on a 1.5 T scanner. CMR images were presented in random order to two experienced fully blinded observers, who had to assign them to three categories by a visual analysis: NSTEMI, myocarditis, or healthy. The conventional approach (cine, T2w and LGE combined) had the best diagnostic accuracy with 92 • A visual differentiation of ischemic from non-ischemic patterns of myocardial injury is reliably achieved by a combination of conventional CMR techniques (cine, T2-weighted and LGE imaging). • There is no significant difference in accuracies between visual pattern analysis on native T1 maps without providing quantitative values and a conventional combined approach for differentiating non-ST elevation myocardial infarction, infarct-like myocarditis, and controls. • T2 maps do not provide a sufficient diagnostic accuracy for visual pattern analysis for differentiating non-ST elevation myocardial infarction, infarct-like myocarditis, and controls.

BACKGROUND. CT-based criteria for assessing the gastrointestinal stromal tumor (GIST) response to tyrosine kinase inhibitor (TKI) therapy are limited in part because tumor attenuation is influenced by treatment-related changes including hemorrhage and calcification. The iodine concentration may be less impacted by such changes. OBJECTIVE. The purpose of this study was to determine whether the dual-energy CT (DECT) vital iodine tumor burden (TB) allows improved differentiation between treatment responders and nonresponders among patients with metastatic GIST who are undergoing TKI therapy compared with established CT and PET/CT criteria. METHODS. An anthropomorphic phantom with spherical inserts mimicking GIST lesions of varying iodine concentrations and having nonenhancing central necrotic cores underwent DECT to determine a threshold iodine concentration. Forty patients (25 women and 15 men; median age, 57 years) who were treated with TKI for metastatic GIST were retrospectively evaluated. Patients underwent baseline and follow-up DECT and FDG PET/CT. Response assessment was performed using RECIST 1.1, modified Choi (mChoi) criteria, vascular tumor burden (VTB) criteria, DECT vital iodine TB criteria, and European Organization for Research and Treatment of Cancer (EORTC) PET criteria. DECT vital iodine TB criteria used the same percentage changes as RECIST 1.1 response categories. Progression-free survival was compared between responders and nonresponders for each response criterion by use of Cox proportional hazard ratios and Harrell C-indexes (i.e., concordance indexes). RESULTS. The phantom experiment identified a threshold of 0.5 mg/mL to differentiate vital from nonvital tissue. With use of the DECT vital iodine TB, median progression-free survival was significantly different between responders and nonresponders (623 vs 104 days; p < .001).. For nonresponders versus responders, the hazard ratio for disease progression for DECT vital iodine TB was 6.9 versus 7.6 for EORTC PET criteria, 3.3 for VTB criteria, 2.3 for RECIST 1.1, and 2.1 for mChoi criteria. The C-index was 0.74 for EORTC PET criteria, 0.73 for DECT vital iodine TB criteria, 0.67 for VTB criteria, 0.61 for RECIST 1.1, and 0.58 for mChoi criteria. The C-index was significantly greater for DECT vital iodine TB criteria than for RECIST 1.1 (p = .02) and mChoi criteria (p = .002), but it was not different from that for VTB and EORTC PET criteria (p > .05). CONCLUSION. DECT vital iodine TB criteria showed performance comparable to that of EORTC PET criteria and outperformed RECIST 1.1 and mChoi criteria for response assessment of metastatic GIST treated with TKI therapy. CLINICAL IMPACT. DECT vital iodine TB could help guide early management decisions in patients receiving TKI therapy.

Objective: Within in a prospectively conducted trial (‘Unifying Advanced Treatment With Advanced Imaging’, GISTm3, NCT 03404076) we aimed at developing and validating a CT radiomics model to predict to response to tyrosine kinase inhibitors in GIST patients. We used the intratumoral iodine concentration which is less corroborated by tumor sclerosis or intratumoral hemorrhage than classical CT criteria. Materials and Methods: This is a prospective multi-center study of 94 patients (mean age 61 years; age range 28-83 years; 51m, 43f) who underwent a single-energy contrast-enhanced staging CT in a portal venous phase. All patients underwent subsequent preoperative imatinib therapy for at least 6 months (median 12 months, range 4-36 months) and follow-up CT examination. Patients were graded binary as responders and non-responders using their best response throughout the drug treatment course according to the vascular tumor burden to account for pseudo-progression under therapy. Response assessment was performed using RECIST 1.1, modified Choi (mChoi), vascular tumor burden (VTB), DECT vital iodine TB. Two radiologists performed a 3D-segmentation analysis of the GIST lesions on the pre-treatment CT using a dedicated radiomics software (Radiomics Version 1.0.9, Siemens Healthineers, Forchheim, Germany) and a visual evaluation of enhancement and non-enhancement parameters of each GIST lesion. Using a training dataset (n=17), a multivariable logistic regression by least absolute shrinkage and selection operator identified features that predicted therapy response was build. This model was then evaluated in the independent cohort (n=78) for temporal validation. Results: 77 GIST lesions responded to the drug. A total of 53 radiological visual features and radiomic features were rated reproducible (intraclass correlation >0.8). The radiological visual grading and the radiomic features alone resulted in a similar AUC (0.62, 95%CI 0.49-0.76 vs 0.64 95%CI 0.50-0.77). The final model which combined both radiological visual grading (3 features) and also 3 radiomic features had a significantly higher AUC (0.75, 95%CI 0.64-0.86; both p<0.01) when compared to both separate predictive models alone. Using DECT vital iodine TB, median PFS was significantly different between non-responders and responders (18.8 mos vs. 5.6 mos, resp.; p=.02). HR for progression for DECT vital iodine TB non-responders vs. responders was 6.9, 3.3 for VTB, 2.3 for RECIST 1.1, and 2.1 for mChoi. Conclusion: The study presents a predictive model that incorporates radiologist grading and radiomics features. DECT vital iodine TB criteria outperformed RECIST 1.1, VTB and mChoi for response assessment of metastatic GIST under TKI therapy. The technique should be very useful in guiding early management decisions in patients. Citation Format: Peter Hohenberger, Mathias Meyer, Thomas Henzler, Richard F. Riedel, Christina Messiou, Daniele Marin, Stefan Schoenberg. Dual energy analysis of TKI response in GIST - results of a prospective trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4139.

Strain is an important imaging parameter to determine myocardial deformation. This study sought to 1) assess changes in left ventricular strain and ejection fraction (LVEF) from acute to chronic ST-elevation myocardial infarction (STEMI) and 2) analyze strain as a predictor of late gadolinium enhancement (LGE). 32 patients with STEMI and 18 controls prospectively underwent cardiac magnetic resonance imaging. Patients were scanned 8 ± 5 days and six months after infarction (± 1.4 months). Feature tracking was performed and LVEF was calculated. LGE was determined visually and quantitatively on short-axis images and myocardial segments were grouped according to the LGE pattern (negative, non-transmural and transmural). Global strain was impaired in patients compared to controls, but improved within six months after STEMI (longitudinal strain from −14 ± 4 to −16 ± 4

Introduction: ECG-gated vs high-pitch non-ECG-gated CT angiography (CTA) for trans-catheter aortic valve replacement (TAVR) planning has been controversially discussed, with current recommendations of ECG-gated CTA. However, the impact on clinical outcome, including post-interventional paravalvular leakage (PVL), remains unclear. Thus, the purpose of this study was to compare a retrospectively ECG-gated CTA against a high-pitch non-ECG-gated CTA protocol for TAVR planning and their associated impact on clinical outcome.

Background The value of dual-energy computed tomography (DECT)-based radiomics in renal lesions is unknown. Purpose To develop DECT-based radiomic models and assess their incremental values in comparison to conventional measurements for differentiating enhancing from non-enhancing small renal lesions. Material and Methods A total of 349 patients with 519 small renal lesions (390 non-enhancing, 129 enhancing) who underwent contrast-enhanced nephrographic phase DECT examinations between June 2013 and January 2020 on multiple DECT platforms were retrospectively recruited. Cohort A included all lesions, while cohort B included Bosniak II–IV and solid enhancing renal lesions. Radiomic models were built with features selected by the least absolute shrinkage and selection operator regression (LASSO). ROC analyses were performed to compare the diagnostic accuracy among conventional and radiomic models for predicting enhancing renal lesions. Results The individual iodine concentration (IC), normalized IC, mean attenuation on 75-keV images, radiomic model of iodine images, 75-keV images and a combined model integrating all the above-mentioned features all demonstrated high AUCs for predicting renal lesion enhancement in cohort A (AUCs = 0.934–0.979) as well as in the test dataset (AUCs = 0.892–0.962) of cohort B (P values with Bonferroni correction >0.003). The AUC (0.864) of mean attenuation on 75-keV images was significantly lower than those of other models (all P values ≤0.001) except the radiomic model of 75-keV images (P = 0.038) in the training dataset of cohort B. Conclusion No incremental value was found by adding radiomic and machine learning analyses to iodine images for differentiating enhancing from non-enhancing renal lesions.

Purpose To evaluate the sensitivity, specificity, and interobserver reliability of high-pitch dual-source computed tomography angiography (CTA) in the detection of anomalous pulmonary venous connection (APVC) in infants with congenital heart defects and to assess the associated radiation exposure. Materials and Methods 78 pulmonary veins in 17 consecutively enrolled patients with congenital heart defects (6 females; 11 males; median age: 6 days; range: 1-299 days) were retrospectively included in this study. All patients underwent high-pitch dual-source CTA of the chest at low tube voltages (70 kV). APVC was evaluated independently by two radiologists. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and interobserver agreement were determined. For standard of reference, one additional observer reviewed CT scans, echocardiography reports, clinical reports as well as surgical reports. In cases of disagreement the additional observer made the final decision based on all available information. Results Detection of APVC with high-pitch dual-source CTA revealed a good sensitivity (91 %) and specificity (99 %), with PPV and NPV of 98 % and 97 %. Interobserver agreement was almost perfect (Kappa = 0.84). The median DLP was 3.8 mGy*cm (IQR 3.3-4.7 mGy*cm) and the median radiation dose was 0.33mSv (IQR 0.26-0.39 mSv). Conclusion High-pitch dual-source CTA in infants with congenital heart defects allows for accurate and reliable assessment of APVC at a low radiation dose.

Background Current imaging methods for prediction of complete margin resection (R0) in patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To investigate whether tumor-related and perivascular CT radiomic features improve preoperative assessment of arterial involvement in patients with surgically proven PDAC. Materials and Methods This retrospective study included consecutive patients with PDAC who underwent surgery after preoperative CT between 2012 and 2019. A three-dimensional segmentation of PDAC and perivascular tissue surrounding the superior mesenteric artery (SMA) was performed on preoperative CT images with radiomic features extracted to characterize morphology, intensity, texture, and task-based spatial information. The reference standard was the pathologic SMA margin status of the surgical sample: SMA involved (tumor cells ≤1 mm from margin) versus SMA not involved (tumor cells >1 mm from margin). The preoperative assessment of SMA involvement by a fellowship-trained radiologist in multidisciplinary consensus was the comparison. High reproducibility (intraclass correlation coefficient, 0.7) and the Kolmogorov-Smirnov test were used to select features included in the logistic regression model. Results A total of 194 patients (median age, 66 years; interquartile range, 60-71 years; age range, 36-85 years; 99 men) were evaluated. Aside from surgery, 148 patients underwent neoadjuvant therapy. A total of 141 patients' samples did not involve SMA, whereas 53 involved SMA. A total of 1695 CT radiomic features were extracted. The model with five features (maximum hugging angle, maximum diameter, logarithm robust mean absolute deviation, minimum distance, square gray level co-occurrence matrix correlation) showed a better performance compared with the radiologist assessment (model vs radiologist area under the curve, 0.71 [95% CI: 0.62, 0.79] vs 0.54 [95% CI: 0.50, 0.59]; P < .001). The model showed a sensitivity of 62% (33 of 53 patients) (95% CI: 51, 77) and a specificity of 77% (108 of 141 patients) (95% CI: 60, 84). Conclusion A model based on tumor-related and perivascular CT radiomic features improved the detection of superior mesenteric artery involvement in patients with pancreatic ductal adenocarcinoma. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Do and Kambadakone in this issue.