In most of the cases Interventional Radiology techniques and therapies are proposed for the management of symptomatic soft tissue benign tumors responsible for pain and/or compression symptoms aiming to offer a curative intent by means of tumor necrosis with subsequent symptoms’ management and improvement of life quality. The ablative therapies include chemical, thermal and non-thermal approaches while, trans-arterial (chemo)embolization also has a distinct role. Adjunct ancillary techniques should be performed whenever necessary to increase efficacy and safety and avoid or reduce complications. The purpose of the current review is to identify the basis for treating soft tissue benign tumors with Interventional Radiology therapies, to offer a detailed review of them, to explain the expected outcomes and describe techniques for avoiding complications. Furthermore, a reflection upon future directions will be suggested.

BackgroundRisk stratification of COVID-19 patients can support therapeutic decisions, planning and resource allocation in the hospital. In times of high incidence, a prognostic model based on data efficiently retrieved from one source can enable fast decision support.MethodsA model was developed to identify patients at risk of developing severe COVID-19 within one month based on their age, sex and imaging features extracted from the thoracic computed tomography (CT). The model was trained on publicly available data from the Study of Thoracic CT in COVID-19 (STOIC) challenge and validated on unseen data from the same study and an external, multicentric dataset. The model, trained on data acquired before any variant of concern dominated, was assessed separately on data collected at later stages of the pandemic when the delta and omicron variants were most prevalent.ResultsA logistic regression based on handcrafted features was found to perform on par with a direct deep learning approach, and the former was selected for simplicity. Volumetric and intensity-based features of lesions and healthy lung parenchyma proved most predictive, in addition to patient age and sex. The model reached an area under the curve of 0.78 on the challenge test set and 0.74 on the external test set. The performance did not drop for the subset acquired at a later stage of the pandemic.ConclusionsA logistic regression utilizing features from thoracic CT and its metadata can provide rapid decision support by estimating short-term COVID-19 severity. Its stable performance underscores its potential for real-world clinical integration. By enabling rapid risk stratification using readily available imaging data, this approach can support early clinical decision-making, optimize resource allocation, and improve patient management, particularly during surges in COVID-19 cases. Furthermore, this study provides a foundation for future research on prognostic modelling in respiratory infections.

Objectives: Primary objective was to report the feasibility, safety and efficacy of percutaneous ablation of hepatic malignant tumors that are undetectable or inconspicuous in non-enhanced computed tomography (CT) scans using an electromagnetic navigation system with a marker option. Secondary objectives included the evaluation of technical parameters including the accuracy of needle placement, the number of control CT acquisitions, and procedural duration. Methods: This prospective study (performed from 1 March 2022 until 30 November 2024) included all patients with hepatic tumors (not visible or poorly defined on non-enhanced CT) who underwent percutaneous microwave ablation (MWA). Technical efficacy was assessed with contrast-enhanced CT immediately post-ablation, and oncologic outcomes (overall and progression-free survival) were evaluated with MRI at 1, 3, and 6 months. Results: Fifteen patients (12 males, 3 females; mean age of 66 years) with 16 tumors (median diameter of 15 mm) were treated in 16 sessions. Tumor types included hepatocellular carcinoma (n = 7), colorectal metastasis (n = 4), ocular melanoma (n = 1), neuroendocrine tumor (n = 1), intrahepatic cholangiocarcinoma (n = 1), and breast cancer metastasis (n = 1). Median procedure time was 53 min, scans number was nine, needle length was 12 cm, and median deviation was 1 mm. No complications were reported. Primary efficacy rate was 94% (15/16), rising to a secondary (assisted) technique efficacy of 100% after re-ablation (one session). During median follow-up of 23 months, local tumor progression-free survival was 100%; distant progression-free survival was 80%, and two patients (13.3%) died, one being cancer-related. Conclusions: Electromagnetic navigation with a marker option enables safe, accurate, and effective MWA of inconspicuous hepatic tumors, achieving excellent local control with favorable oncologic outcomes.

Objectives: To evaluate the non-inferiority of non-contrast CT compared to contrast-enhanced CT with both intravenous and rectal contrast application for the diagnosis of acute colonic diverticulitis. Methods: Five readers retrospectively evaluated the non-contrast and contrast-enhanced series of CTs of 205 consecutive patients with clinical suspicion of acute diverticulitis. Two randomized reading sessions, both containing all 205 cases as either contrast-enhanced or non-contrast (1:1) series, were performed with ≥8 weeks washout between them. The non-inferiority margin was set to 0.1. Results: The pooled prevalence (all readers) of diverticulitis was similar for non-contrast CT (63.9%, range: 60.5–65.0%) and contrast-enhanced CT (64.4%, 61.5–67.8%). Non-contrast CT was non-inferior for the diagnosis of diverticulitis (accuracy 0.90 [95% confidence interval: 0.89, 0.92]) compared to contrast-enhanced CT (0.92 [0.90, 0.94]; the difference in accuracy: −0.01 [−0.04, 0.01]) (normal deviate test: p-valueone-sided = 5.20 × 10−6). Sensitivities for perforation and abscess were slightly but significantly lower for the non-contrast CT than for the contrast-enhanced CT (differences: −0.15 [−0.20, −0.05], −0.17 [−0.27, −0.07]), while no differences in accuracies and specificities were observed. Conclusions: Non-contrast CT is non-inferior to contrast-enhanced CT (intravenous and rectal contrast) for the diagnosis of acute colonic diverticulitis. Contrast-enhanced CT is associated with significantly higher sensitivities for the presence of an abscess or perforation.

AI is emerging as a promising tool for diagnosing COVID-19 based on chest CT scans. The aim of this study was the comparison of AI models for COVID-19 diagnosis. Therefore, we: (1) trained three distinct AI models for classifying COVID-19 and non-COVID-19 pneumonia (nCP) using a large, clinically relevant CT dataset, (2) evaluated the models’ performance using an independent test set, and (3) compared the models both algorithmically and experimentally. In this multicenter multi-vendor study, we collected n=1591 chest CT scans of COVID-19 (n=762) and nCP (n=829) patients from China and Germany. In Germany, the data was collected from three RACOON sites. We trained and validated three COVID-19 AI models with different architectures: COVNet based on 2D-CNN, DeCoVnet based on 3D-CNN, and AD3D-MIL based on 3D-CNN with attention module. 991 CT scans were used for training the AI models using 5-fold cross-validation. 600 CT scans from 6 different centers were used for independent testing. The models’ performance was evaluated using accuracy (Acc), sensitivity (Se), and specificity (Sp). The average validation accuracy of the COVNet, DeCoVnet, and AD3D-MIL models over the 5 folds was 80.9%, 82.0%, and 84.3%, respectively. On the independent test set with n=600 CT scans, COVNet yielded Acc=76.6%, Se=67.8%, Sp=85.7%; DeCoVnet provided Acc=75.1%, Se=61.2%, Sp=89.7%; and AD3D-MIL achieved Acc=73.9%, Se=57.7%, Sp=90.8%. The classification performance of the evaluated AI models is highly dependent on the training data rather than the architecture itself. Our results demonstrate a high specificity and moderate sensitivity. The AI classification models should not be used unsupervised but could potentially assist radiologists in COVID-19 and nCP identification.

This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass. Detection sensitivity and specificity were calculated and readers rated their subjective diagnostic certainty. For statistical analysis of sensitivity and specificity, a paired t-test and ANOVA were used (significance level p = 0.05). A total of 50 female patients (median age 51 years, range 28–83 years) participated. IM had the highest overall scores in sensitivity and specificity for breast cancer detection, with 0.97 ± 0.06 and 0.95 ± 0.07, respectively, compared with 0.90 ± 0.04 and 0.92 ± 0.06 in CI. MonoE40 yielded a sensitivity of 0.96 ± 0.02 and specificity of 0.94 ± 0.08. All differences in sensitivity and specificity between MonoE or IM and CI were statistically significant (p < 0.001). The superiority of IM sensitivity and specificity was most pronounced in patients with dense breasts. Spectral CT improved the detection of breast cancer with higher sensitivity and specificity compared to conventional image data in our study.

Purpose: Evaluation of the influence of intrinsic and extrinsic conditions on ablation zone volumes (AZV) after microwave ablation (MWA). Methods: Retrospective analysis of 38 MWAs of therapy-naïve liver tumours performed with the NeuWave PR probe. Ablations were performed either in the ‘standard mode’ (65 W, 10 min) or in the ‘surgical mode’ (95 W, 1 min, then 65 W, 10 min). AZV measurements were obtained from contrast-enhanced computed tomography immediately post-ablation. Results: AZVs in the ‘standard mode’ were smaller than predicted by the manufacturer (length 3.6 ± 0.6 cm, 23% below 4.7 cm; width 2.7 ± 0.6, 23% below 3.5 cm). Ablation zone past the tip was limited to 6 mm in 28/32 ablations. Differences in AZV between the ‘surgical mode’ and ‘standard mode’ were not significant (15.6 ± 7.8 mL vs. 13.9 ± 8.8 mL, p = 0.6). AZVs were significantly larger in case of hepatocellular carcinomas (HCCs) (n = 19) compared to metastasis (n = 19; 17.8 ± 9.9 mL vs. 10.1 ± 5.1 mL, p = 0.01) and in non-perivascular tumour location (n = 14) compared to perivascular location (n = 24, 18.7 ± 10.4 mL vs. 11.7 ± 6.1 mL, p = 0.012), with both factors remaining significant in two-way analysis of variance (HCC vs. metastasis: p = 0.02; perivascular vs. non-perivascular tumour location: p = 0.044). Conclusion: Larger AZVs can be expected in cases of HCCs compared with metastases and in non-perivascular locations. Using the ‘surgical mode’ does not increase AZV significantly.

BACKGROUND:Computer-aided detection (CAD) tools for TB detection have the potential to enable screening programmes and reduce the diagnostic gap in settings where access to radiologists is limited. However, there are concerns that other common chest X-ray (CXR) abnormalities not due to TB may be missed. METHODS:We assessed the performance of three commercialised CAD tools (qXR, INSIGHT CXR and DrAIDTM TB XR) to detect common non-TB abnormalities against readings with a standardised annotation guide by an expert radiologist. More than 20 well-characterised diagnoses besides TB significant in TB high-burden countries were examined. RESULTS:The 517 CXRs included were deemed abnormal by the three CAD with a sensitivity of respectively 97% (95% CI 95-98), 94% (95% CI 91-95), and 87% (95% CI 84-90) for INSIGHT CXR, qXR, and DrAID. The CAD generally detected abnormalities in patients with critical diagnoses such as lung cancer or heart failure. Performance for detecting other abnormalities was variable. CONCLUSION:This study showed that the three CAD tools identified CXRs as abnormal when diseases other than TB were present. Our findings alleviate ethical concerns of missing abnormalities other than TB when using commercially available CAD for TB screening and show their potential broader applicability.

Introduction: Endometriosis is a common benign condition affecting 10-15% of women of reproductive age. An unusual site of endometriosis is the canal of Nuck, which is a physiologically obliterated space in women spanning the area from the deep inguinal ring to the labia majora. Case presentation: A 37-year-old woman, with a past medical history of several in vitro fertilization attempts, presented with a right-sided painful inguinal mass. She was subsequently offered surgical exploration and excision of the lesion, which revealed the presence of endometrial glands and stroma. Discussion: Despite being a relatively common and benign pelvic condition, endometriosis can rarely manifest in the inguinal region, within the canal of Nuck. The treating physician should be cognizant of Nuck canal endometriosis, especially in young female patients presenting with an irreducible mass in the inguinal region and associated cyclic pain or infertility. Conclusion: When clinically and radiologically suspected, surgical excision is indicated to establish the diagnosis, provide symptomatic relief and guide further decision making.

Transarterial chemoembolization (TACE) has revolutionized the treatment landscape for malignant liver disease, offering localized therapy with reduced systemic toxicity. This manuscript delves into the use of degradable microspheres (DMS) in TACE, exploring its potential advantages and clinical applications. DMS-TACE emerges as a promising strategy, offering temporary vessel occlusion and optimized drug delivery. The manuscript reviews the existing literature on DMS-TACE, emphasizing its tolerability, toxicity, and efficacy. Notably, DMS-TACE demonstrates versatility in patient selection, being suitable for both intermediate and advanced stages. The unique properties of DMS provide advantages over traditional embolic agents. The manuscript discusses the DMS-TACE procedure, adverse events, and tumor response rates in HCC, ICC, and metastases.

Zielsetzung Brusttumoren sind ein häufiger Zufallsbefund der Thorax-CT, können jedoch leicht zu übersehen und schwer zu beurteilen sein. Ziel dieser Studie war die Untersuchung der diagnostischen Überlegenheit von monoenergetischen 40keV-Bildern (MonoE40) und Jodkarten (IM) im Vergleich zu konventionellen Bildern (CI) hinsichtlich der Erkennung von Brustkrebs bei Routine-CT-Untersuchungen.

OBJECTIVES:Differentiation between COVID-19 and community-acquired pneumonia (CAP) in computed tomography (CT) is a task that can be performed by human radiologists and artificial intelligence (AI). The present study aims to (1) develop an AI algorithm for differentiating COVID-19 from CAP and (2) evaluate its performance. (3) Evaluate the benefit of using the AI result as assistance for radiological diagnosis and the impact on relevant parameters such as accuracy of the diagnosis, diagnostic time, and confidence.METHODS:We included n = 1591 multicenter, multivendor chest CT scans and divided them into AI training and validation datasets to develop an AI algorithm (n = 991 CT scans; n = 462 COVID-19, and n = 529 CAP) from three centers in China. An independent Chinese and German test dataset of n = 600 CT scans from six centers (COVID-19 / CAP; n = 300 each) was used to test the performance of eight blinded radiologists and the AI algorithm. A subtest dataset (180 CT scans; n = 90 each) was used to evaluate the radiologists' performance without and with AI assistance to quantify changes in diagnostic accuracy, reporting time, and diagnostic confidence.RESULTS:The diagnostic accuracy of the AI algorithm in the Chinese-German test dataset was 76.5%. Without AI assistance, the eight radiologists' diagnostic accuracy was 79.1% and increased with AI assistance to 81.5%, going along with significantly shorter decision times and higher confidence scores.CONCLUSION:This large multicenter study demonstrates that AI assistance in CT-based differentiation of COVID-19 and CAP increases radiological performance with higher accuracy and specificity, faster diagnostic time, and improved diagnostic confidence.KEY POINTS:• AI can help radiologists to get higher diagnostic accuracy, make faster decisions, and improve diagnostic confidence. • The China-German multicenter study demonstrates the advantages of a human-machine interaction using AI in clinical radiology for diagnostic differentiation between COVID-19 and CAP in CT scans.

BACKGROUND:Serum amylase activity greater than the institutional upper limit of normal (hyperamylasemia) on postoperative day 0-2 has been suggested as a criterion to define postoperative acute pancreatitis after pancreatoduodenectomy, but robust evidence supporting this definition is lacking.BACKGROUND:To assess the clinical impact of hyperamylasemia after pancreatoduodenectomy and to define postoperative acute pancreatitis.METHODS:Data of 1,235 consecutive patients who had undergone pancreatoduodenectomy between January 2010 and December 2014 were extracted from a prospective database and analyzed. Postoperative acute pancreatitis was defined based on the computed tomography severity index. Logistic regression modeling was used to calculate the postoperative acute pancreatitis rate of the entire study population.RESULTS:Hyperamylasemia on postoperative day 1 was found in 52% of patients after pancreatoduodenectomy. Patients with hyperamylasemia on postoperative day 1 had statistically significantly greater morbidity and mortality than patients with a normal serum amylase activity on postoperative day 1 with the rates of postoperative pancreatic fistula of 14.5% vs 2.1%, and 90-day mortality of 6.6% vs 2.2%, respectively. Of the 364 patients who underwent postoperative computed tomography, 103 (28%) had radiologic signs of acute pancreatitis, thus defining them as having postoperative acute pancreatitis by our definition. Logistic regression modeling showed a 14.7% rate of postoperative acute pancreatitis for the entire patient cohort and 29.2% for patients with hyperamylasemia on postoperative day 1. Outcomes of patients with postoperative acute pancreatitis defined based on the computed tomography severity index showed a rate of postoperative pancreatic fistula of 32.4% and a 90-day mortality rate of 11.8%, which were worse than those of patients with hyperamylasemia on postoperative day 1 alone.CONCLUSION:Hyperamylasemia on postoperative day 1 is a frequent finding after pancreatoduodenectomy, but hyperamylasemia on postoperative day 1 alone is not synonymous with postoperative acute pancreatitis because only 29.2% of such patients have acute pancreatitis based on computed tomography findings. Postoperative acute pancreatitis is a dangerous complication after pancreatoduodenectomy, but its prevalence, according to the gold standard of CT, is not as high as reported previously. Our data suggest that hyperamylasemia on postoperative day 1 and postoperative acute pancreatitis are 2 different entities.

Purpose: To examine the performance of radiologists in differentiating COVID-19 from non-COVID-19 atypical pneumonia and to perform an analysis of CT patterns in a study cohort including viral, fungal and atypical bacterial pathogens. Methods: Patients with positive RT-PCR tests for COVID-19 pneumonia (n = 90) and non-COVID-19 atypical pneumonia (n = 294) were retrospectively included. Five radiologists, blinded to the pathogen test results, assessed the CT scans and classified them as COVID-19 or non-COVID-19 pneumonia. For both groups specific CT features were recorded and a multivariate logistic regression model was used to calculate their ability to predict COVID-19 pneumonia. Results: The radiologists differentiated between COVID-19 and non-COVID-19 pneumonia with an overall accuracy, sensitivity, and specificity of 88% +/- 4 (SD), 79% +/- 6 (SD), and 90% +/- 6 (SD), respectively. The percentage of correct ratings was lower in the early and late stage of COVID-19 pneumonia compared to the progressive and peak stage (68 and 71% vs 85 and 89%). The variables associated with the most increased risk of COVID-19 pneumonia were band like subpleural opacities (OR 5.55, p < 0.001), vascular enlargement (OR 2.63, p = 0.071), and subpleural curvilinear lines (OR 2.52, p = 0.021). Bronchial wall thickening and centrilobular nodules were associated with decreased risk of COVID-19 pneumonia with OR of 0.30 (p = 0.013) and 0.10 (p < 0.001), respectively. Conclusions: Radiologists can differentiate between COVID-19 and non-COVID-19 atypical pneumonias at chest CT with high overall accuracy, although a lower performance was observed in the early and late stage of COVID 19 pneumonia. Specific CT features might help to make the correct diagnosis.

The "bullseye" sign has been exclusively reported in patients suffering from coronavirus disease 2019 (COVID-19) pneumonia. It is theorized that this newly recognized computed tomography (CT) feature represents a sign of organizing pneumonia. Well established signs of organizing pneumonia also reported in COVID-19 patients include linear opacities, the "reversed halo" sign (or "atoll" sign), and a perilobular distribution of abnormalities. These findings are usually present on imaging in the intermediate and late stage of the disease. This is a case of simultaneous presence of the "bullseye" and the "reversed halo" sign on chest CT images of a COVID-19 patient examined 22 days after symptom onset.

Purpose: This study aimed to evaluate contrast-enhanced computed tomography (CE-CT) features for prediction of arterial tumor invasion in pancreatic cancer (PDAC) patients in the event of arterial encasement >180 degrees after neoadjuvant (radio-)chemotherapy (NAT). Methods: Seventy PDAC patients with seventy-five arteries showing encasement >180 degrees after completion of NAT were analyzed. All patients underwent surgical exploration with either tumor resection including arterial resection, periadventitial dissection (arterial divestment) or confirmation of locally irresectable disease. CE-CT scans were assessed regarding tumor extent and artery-specific imaging features. The results were analyzed on a per-artery basis. Based on the intraoperative and histopathological findings, encased arteries were classified as either invaded or non-invaded. Results: Eighteen radiologically encased arteries were resected; of these, nine had pathologic evidence for tumor invasion. In 42 encased arteries, the tumor could be removed by arterial divestment. In 13 patients with 15 encased arteries, the tumor was deemed technically irresectable. Median tumor size, length of solid soft tissue contact, and degree of circumferential contiguity by solid soft tissue along the artery in CE-CT were significantly lower in the non-invaded than in the invaded artery group (p <= 0.017). Imaging features showed moderate accuracies for prediction of arterial invasion (<= 72.0 %). The thresholds <= 26 mm for post-NAT solid soft tissue contact and <= 270 degrees for circumferential contiguity by solid soft tissue had high negative predictive values (>= 87.5 %). Conclusion: Although post-NAT prediction of arterial invasion remains difficult, arteries with <270 degrees contiguity by soft tissue and arteries with <= 26 mm length of solid soft tissue contact are unlikely to be invaded, with possible implications for surgical planning.

Objective: Evaluation of software tools for segmentation, quantification, and characterization of fibrotic pulmonary parenchyma changes will strengthen the role of CT as biomarkers of disease extent, evolution, and response to therapy in idiopathic pulmonary fibrosis (IPF) patients. Methods: 418 nonenhanced thin-section MDCTs of 127 IPF patients and 78 MDCTs of 78 healthy individuals were analyzed through 3 fully automated, completely different software tools: YACTA, LUFIT, and IMBIO. The agreement between YACTA and LUFIT on segmented lung volume and 80th (reflecting fibrosis) and 40th (reflecting ground-glass opacity) percentile of the lung density histogram was analyzed using Bland-Altman plots. The fibrosis and ground-glass opacity segmented by IMBIO (lung texture analysis software tool) were included in specific regression analyses. Results: In the IPF-group, LUFIT outperformed YACTA by segmenting more lung volume (mean difference 242 mL, 95% limits of agreement -54 to 539 mL), as well as quantifying higher 80th (76 HU, -6 to 158 HU) and 40th percentiles (9 HU, -73 to 90 HU). No relevant differences were revealed in the control group. The 80th/40th percentile as quantified by LUFIT correlated positively with the percentage of fibrosis/ground-glass opacity calculated by IMBIO (r = 0.78/r = 0.92). Conclusions: In terms of segmentation of pulmonary fibrosis, LUFIT as a shape model-based segmentation software tool is superior to the threshold-based YACTA, tool, since the density of (severe) fibrosis is similar to that of the surrounding soft tissues. Therefore, shape modeling as used in LUFIT may serve as a valid tool in the quantification of IPF, since this mainly affects the subpleural space.

Background: The clinical relevance of hyperamylasemia after distal pancreatectomy (DP) remains unclear and no internationally accepted definition of postoperative acute pancreatitis (POAP) exists. The aim of this study was to characterize POAP after DP and to assess the role of serum amylase (SA) in POAP. Methods: Outcomes of 641 patients who had undergone DP between 2015 and 2019 were analyzed. Postoperative SA was determined in all patients. POAP was defined based on contrast-enhanced computed tomography (CT) or intraoperative findings during relaparotomy. Results: An elevation of SA on postoperative day 1 (hyperamylasemiaPOD1) was found in 398 patients (62.1%). Twelve patients (1.87%) were identified with POAP. Ten patients demonstrated radiologic criteria for POAP and in two patients POAP was diagnosed during relaparotomy. Outcome of POAP patients was worse than that of patients with hyperamylasemiaPOD1 alone and that with normal SAPOD1 without POAP evidence (postoperative pancreatic fistula 50% vs 30.6% vs 18.5%; length of hospital stay 26 days vs 12 vs 11, respectively). The overall 90-day mortality of all 641 patients was 0.6%. Conclusion: POAP is a serious but rare complication after DP. HyperamylasemiaPOD1 is of prognostic relevance after DP, but it seems not sufficient as a single parameter to diagnose POAP.

Introduction: CT is essential in diagnosis of acute exacerbation of IPF (AE) showing new ground-glass abnormalities (GGO) along to reticular pattern (RE). However, quantification is subject to inter-reader variability and limited reproducibility. Aim of this work was to compare visual scoring (VS) to fully automated computer-aided quantification of sequential CTs in patients with and without AE. Methods: Paired follow-up non-enhanced thin-section CT were analyzed using LUng FIbrosis quantification Tool (LUFIT) in 49 IPF patients (pt). Longitudinal VS assessment was performed by an experienced chest radiologist. Spearman correlation was applied for 40th and 80th percentile (PERC) histogram of lung density (reflecting RE and GGO respectively) and VS. Results: 30pt with AE (FVC 67% ±18, DLCO 35% ±13) and 19pt without AE (NoAE) (FVC 81% ±24, DLCO 49% ±16) at follow-up were included, resulting in serial analysis of 98 paired CT data-sets. Automated CT analysis ran unattended and successfully. In pt experiencing AE, GGO increased +6% in VS and +29HU (40th PERC) in LUFIT (p<0.01/p<0.001), while RE increased by +2% in VS and +57HU (80th PERC) in LUFIT respectively (p=0.06/p<0.01). There were no significant changes in the NoAE group at follow-up. Correlation analysis between VS and LUFIT showed a moderate correlation for GGO (r=0.5, p<0.02) and RE (r=0.6, p<0.003). Conclusions: In IPF patients, LUFIT analysis identified typical changes during AE successfully and provided quantification of acute inflammation (GGO) and fibrosis (RE). Fully automated quantification of CT is easy to perform, time effective, correct, and reliable in patients suffering from IPF.