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Background iRECIST for the objective monitoring of immunotherapies was published by the official RECIST working group in 2017. Main body Immune-checkpoint inhibitors represent one of the most important therapy advancements in modern oncology. They are currently used for treatment of multiple malignant diseases especially at advanced, metastatic stages which were poorly therapeutically accessible in the past. Promising results of recent studies suggest that their application will further grow in the near future, particularly when used in combination with chemotherapy. A challenging aspect of these immunotherapies is that they may show atypical therapy response patterns such as pseudoprogression and demonstrate a different imaging spectrum of adverse reactions, both of which are crucial for radiologists to understand. In 2017 the RECIST working group published a modified set of response criteria, iRECIST, for immunotherapy, based on RECIST 1.1 which was developed for cytotoxic therapies and adapted for targeted agents. Conclusion This article provides guidance for response assessment of oncologic patients under immunotherapy based on iRECIST criteria.

Objectives To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to test different normalization approaches. Methods Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NIC PV :portal vein; NIC AA :abdominal aorta; NIC ALL :overall iodine load) were compared between the three DECT scanners for each patient. A longitudinal mixed effects analysis was conducted to elucidate the effect of the scanner type, scan order, inter-scan time, and contrast media amount on normalized iodine concentration. Results Variability of IC was highest in the liver (dsDECT vs. dlDECT 28.96 (14.28–46.87) %, dsDECT vs. rsDECT 29.08 (16.59–62.55) %, rsDECT vs. dlDECT 22.85 (7.52–33.49) %), and lowest in the kidneys (dsDECT vs. dlDECT 15.76 (7.03–26.1) %, dsDECT vs. rsDECT 15.67 (8.86–25.56) %, rsDECT vs. dlDECT 10.92 (4.92–22.79) %). NIC ALL yielded the best reduction of IC variability throughout all tissues and inter-scanner comparisons, yet did not reduce the variability between dsDECT vs. dlDECT and rsDECT, respectively, in the liver. The scanner type remained a significant determinant for NIC ALL in the pancreas and the liver ( F -values, 12.26 and 23.78; both, p < 0.0001). Conclusions We found tissue-specific intra-patient variability of IC across different DECT scanner types. Normalization mitigated variability by reducing physiological fluctuations in iodine distribution. After normalization, the scanner type still had a significant effect on iodine variability in the pancreas and liver. Clinical relevance statement Differences in iodine quantification between dual-energy CT scanners can partly be mitigated by normalization, yet remain relevant for specific tissues and inter-scanner comparisons, which should be taken into account at clinical routine imaging. Key Points • Iodine concentration showed the least variability between scanner types in the kidneys (range 10.92–15.76%) and highest variability in the liver (range 22.85–29.08%). • Normalizing tissue-specific iodine concentrations against the overall iodine load yielded the greatest reduction of variability between scanner types for 2/3 inter-scanner comparisons in the liver and for all (3/3) inter-scanner comparisons in the kidneys and pancreas, respectively. • However, even after normalization, the dual-energy CT scanner type was found to be the factor significantly influencing variability of iodine concentration in the liver and pancreas.

Objectives Dual-energy computed tomography allows for an accurate and reliable quantification of iodine. However, data on physiological distribution of iodine concentration (IC) is still sparse. This study aims to establish guidance for IC in abdominal organs and important anatomical landmarks using a large cohort of individuals without radiological tumor burden. Methods Five hundred seventy-one oncologic, portal venous phase dual-layer spectral detector CT studies of the chest and abdomen without tumor burden at time point of imaging confirmed by > 3-month follow-up were included. ROI were placed in parenchymatous organs ( n = 25), lymph nodes ( n = 6), and vessels ( n = 3) with a minimum of two measurements per landmark. ROI were placed on conventional images and pasted to iodine maps to retrieve absolute IC. Normalization to the abdominal aorta was conducted to obtain iodine perfusion ratios. Bivariate regression analysis, t tests, and ANOVA with Tukey-Kramer post hoc test were used for statistical analysis. Results Absolute IC showed a broad scatter and varied with body mass index, between different age groups and between the sexes in parenchymatous organs, lymph nodes, and vessels (range 0.0 ± 0.0 mg/ml–6.6 ± 1.3 mg/ml). Unlike absolute IC, iodine perfusion ratios did not show dependency on body mass index; however, significant differences between the sexes and age groups persisted, showing a tendency towards decreased perfusion ratios in elderly patients (e.g., liver 18–44 years/≥ 64 years: 0.50 ± 0.11/0.43 ± 0.10, p ≤ 0.05). Conclusions Distribution of IC obtained from a large-scale cohort is provided. As significant differences between sexes and age groups were found, this should be taken into account when obtaining quantitative iodine concentrations and applying iodine thresholds. Key Points • Absolute iodine concentration showed a broad variation and differed between body mass index, age groups, and between the sexes in parenchymatous organs, lymph nodes, and vessels. • The iodine perfusion ratios did not show dependency on body mass index while significant differences between sexes and age groups persisted. • Provided guidance values may serve as reference when aiming to differentiate healthy and abnormal tissue based on iodine perfusion ratios.

Objectives To evaluate the reduction of artifacts from cardiac implantable electronic devices (CIEDs) by virtual monoenergetic images (VMI), metal artifact reduction (MAR) algorithms, and their combination (VMI MAR ) derived from spectral detector CT (SDCT) of the chest compared to conventional CT images (CI). Methods In this retrospective study, we included 34 patients (mean age 74.6 ± 8.6 years), who underwent a SDCT of the chest and had a CIED in place. CI, MAR, VMI, and VMI MAR (10 keV increment, range: 100–200 keV) were reconstructed. Mean and standard deviation of attenuation (HU) among hypo- and hyperdense artifacts adjacent to CIED generator and leads were determined using ROIs. Two radiologists qualitatively evaluated artifact reduction and diagnostic assessment of adjacent tissue. Results Compared to CI, MAR and VMI MAR ≥ 100 keV significantly increased attenuation in hypodense and significantly decreased attenuation in hyperdense artifacts at CIED generator and leads ( p < 0.05). VMI ≥ 100 keV alone only significantly decreased hyperdense artifacts at the generator ( p < 0.05). Qualitatively, VMI ≥ 100 keV, MAR, and VMI MAR ≥ 100 keV provided significant reduction of hyper- and hypodense artifacts resulting from the generator and improved diagnostic assessment of surrounding structures ( p < 0.05). Diagnostic assessment of structures adjoining to the leads was only improved by MAR and VMI MAR 100 keV ( p < 0.05), whereas keV values ≥ 140 with and without MAR significantly worsened diagnostic assessment ( p < 0.05). Conclusions The combination of VMI and MAR as well as MAR as a standalone approach provides effective reduction of artifacts from CIEDs. Still, higher keV values should be applied with caution due to a loss of soft tissue and vessel contrast along the leads. Key Points • The combination of VMI and MAR as well as MAR as a standalone approach enables effective reduction of artifacts from CIEDs. • Higher keV values of both VMI and VMI MAR at CIED leads should be applied with caution since diagnostic assessment can be hampered by a loss of soft tissue and vessel contrast. • Recommended keV values for CIED generators are between 140 and 200 keV and for leads around 100 keV.

The latest advancement of artificial intelligence (AI) is generative pretrained transformer large language models (LLMs). They have been trained on massive amounts of text, enabling humanlike and semantical responses to text-based inputs and requests. Foreshadowing numerous possible applications in various fields, the potential of such tools for medical data integration and clinical decision-making is not yet clear. In this study, we investigate the potential of LLMs in report-based medical decision-making on the example of acute ischemic stroke (AIS), where clinical and image-based information may indicate an immediate need for mechanical thrombectomy (MT). The purpose was to elucidate the feasibility of integrating radiology report data and other clinical information in the context of therapy decision-making using LLMs. A hundred patients with AIS were retrospectively included, for which 50% (50/100) was indicated for MT, whereas the other 50% (50/100) was not. The LLM was provided with the computed tomography report, information on neurological symptoms and onset, and patients' age. The performance of the AI decision-making model was compared with an expert consensus regarding the binary determination of MT indication, for which sensitivity, specificity, and accuracy were calculated. The AI model had an overall accuracy of 88%, with a specificity of 96% and a sensitivity of 80%. The area under the curve for the report-based MT decision was 0.92. The LLM achieved promising accuracy in determining the eligibility of patients with AIS for MT based on radiology reports and clinical information. Our results underscore the potential of LLMs for radiological and medical data integration. This investigation should serve as a stimulus for further clinical applications of LLMs, in which this AI should be used as an augmented supporting system for human decision-making.

Objectives The aim of this study was to evaluate whether simple 2D measurements in axial slices of head and neck CT examinations correlate with generally established measurements of body composition in abdominal CT at the height of the third lumbar vertebra and thus allow for an estimation of muscle and fat masses. Methods One hundred twenty-two patients who underwent concurrent CT of the head and neck and the abdomen between July 2016 and July 2020 were retrospectively included. For a subset of 30 patients, additional bioelectrical impedance analysis (BIA) was available. Areas of paraspinal muscles at the height of the third (C3) and fifth cervical vertebrae (C5) as well as the total cross-sectional area at the height of C3 and at the submandibular level were correlated with the results of abdominal measurements and BIA. Furthermore, intra- and interreader variabilities of all measurements were assessed. Results Regarding adipose tissue, good correlations were found between the total cross-sectional area of the patient’s body at the submandibular level and at the height of C3 between both abdominal measurements and BIA results ( r = 0.8–0.92; all p < 0.001). Regarding muscle, the total paraspinal muscle area at the height of C3 and C5 showed strong correlations with abdominal measurements and moderate to strong correlations with BIA results ( r = 0.44–0.80; all p < 0.001), with the muscle area on C5 yielding slightly higher correlations. Conclusions Body composition information can be obtained with comparable reliability from head and neck CT using simple biplanar measurements as from abdominal CT. Key Points • The total paraspinal muscle area at the height of C3 and C5 correlates strongly with abdominal muscle mass. • The total cross-sectional area at the submandibular level and at the height of C3 shows good correlations with abdominal fat mass. • The described measurements facilitate a rapid, opportunistic assessment of relevant body composition parameters.

Dual-energy CT allows for the reconstruction of virtual non-contrast (VNC) images. VNC images have the potential to replace true non-contrast scans in various clinical applications. This study investigated the quantitative accuracy of VNC attenuation images considering different parameters for acquisition and reconstruction. An abdomen phantom with 7 different tissue types (different combinations of 3 base materials and 5 iodine concentrations) was scanned using a spectral detector CT (SDCT). Different phantom sizes (S, M, L), volume computed tomography dose indices (CTDIvol 10, 15, 20 mGy), kernel settings (soft, standard, sharp), and denoising levels (low, medium, high) were tested. Conventional and VNC images were reconstructed and analyzed based on regions of interest (ROI). Mean and standard deviation were recorded and differences in attenuation between corresponding base materials and VNC was calculated (VNCerror). Statistic analysis included ANOVA, Wilcoxon test and multivariate regression analysis. Overall, the VNC error was − 1.4 ± 6.1 HU. While radiation dose, kernel setting, and denoising level did not influence VNC error significantly, phantom size, iodine content and base material had a significant effect (e.g. S vs. M: − 1.2 ± 4.9 HU vs. − 2.1 ± 6.0 HU; 0.0 mg/ml vs. 5.0 mg/ml: − 4.0 ± 3.5 HU vs. 5.1 ± 5.0 HU and 35-HU-base vs. 54-HU-base: − 3.5 ± 4.4 HU vs. 0.7 ± 6.5; all p  ≤ 0.05). The overall accuracy of VNC images from SDCT is high and independent from dose, kernel, and denoising settings; however, shows a dependency on patient size, base material, and iodine content; particularly the latter results in small, yet, noticeable differences in VNC attenuation.

The prognosis for patients with metastatic melanoma is poor and treatment options are limited. Genetically-engineered T cell therapy targeting chondroitin sulfate proteoglycan 4 (CSPG4), however, represents a promising treatment option, especially as both primary melanoma cells as well as metastases uniformly express CSPG4. Aiming to prevent off-tumor toxicity while maintaining a high cytolytic potential, we combined a chimeric co-stimulatory receptor (CCR) and a CSPG4-directed second-generation chimeric antigen receptor (CAR) with moderate potency. CCRs are artificial receptors similar to CARs, but lacking the CD3ζ activation element. Thus, T cells expressing solely a CCR, do not induce any cytolytic activity upon target cell binding, but are capable of boosting the CAR T cell response when both CAR and CCR engage their target antigens simultaneously. Here we demonstrate that co-expression of a CCR can significantly enhance the anti-tumor response of CSPG4-CAR T cells in vitro as well as in vivo . Importantly, this boosting effect was not dependent on co-expression of both CCR- and CAR-target on the very same tumor cell, but was also achieved upon trans activation. Finally, our data support the idea of using a CCR as a powerful tool to enhance the cytolytic potential of CAR T cells, which might open a novel therapeutic window for the treatment of metastatic melanoma.

Background Patients with Congenital heart disease (CHD) require repetitive imaging of the pulmonary vasculature throughout their life. In this study, we compared a novel Compressed SENSE accelerated (factor 9) electrocardiogram (ECG)- and respiratory-triggered 3D modified Relaxation-Enhanced Angiography without Contrast and Triggering (modified REACT-non-contrast-enhanced magnetic resonance angiography (modified REACT-non-CE-MRA)) with standard non-ECG-triggered time-resolved 4D CE-MRA for imaging of the pulmonary arteries and veins in patients with CHD. Methods This retrospective analysis of 25 patients (June 2018–April 2019) with known or suspected CHD was independently conducted by two radiologists executing measurements on modified REACT-non-CE-MRA and 4D CE-MRA on seven dedicated points (inner edge): Main pulmonary artery (MPA), right and left pulmonary artery, right superior and inferior pulmonary vein, left superior (LSPV) and inferior pulmonary vein. Image quality for arteries and veins was evaluated on a four-point scale in consensus. Results Twenty-three of the 25 included patients presented a CHD. There was a high interobserver agreement for both methods of imaging at the pulmonary arteries (ICC ≥ 0.96); at the pulmonary veins, modified REACT-non-CE-MRA showed a slightly higher agreement, pronounced at LSPV (ICC 0.946 vs. 0.895). Measurements in 4D CE-MRA showed higher diameter values compared to modified REACT-non-CE-MRA, at the pulmonary arteries reaching significant difference (e.g. MPA: mean 0.408 mm, p  = 0.002). Modified REACT-non-CE-MRA (average acquisition time 07:01 ± 02:44 min) showed significant better image quality than 4D CE-MRA at the pulmonary arteries (3.84 vs. 3.32, p  < 0.001) and veins (3.32 vs. 2.72, p  = 0.015). Conclusions Compressed SENSE accelerated (factor 9) ECG- and respiratory-triggered 3D modified REACT-non-CE-MRA allows for reliable and fast imaging of the pulmonary arteries and veins with higher image quality and slightly higher interobserver agreement than 4D CE-MRA without contrast agent and associated disadvantages. Therefore, it represents a clinically suitable technique for patients requiring repetitive imaging of the pulmonary vasculature, e.g. patients with CHD.

Intra-arterial nimodipine administration is a widely used rescue therapy for cerebral vasospasm. Although it is known that its effect sets in with delay, there is little evidence in current literature. Our aim was to prove that the maximal vasodilatory effect is underestimated in direct angiographic controls. We reviewed all cases of intra-arterial nimodipine treatment for subarachnoid hemorrhage-related cerebral vasospasm between January 2021 and December 2022. Inclusion criteria were availability of digital subtraction angiography runs before and after nimodipine administration and a delayed run for the most affected vessel at the end of the procedure to decide on further escalation of therapy. We evaluated nimodipine dose, timing of administration and vessel diameters. Delayed runs were performed in 32 cases (19 patients) with a mean delay of 37.6 (± 16.6) min after nimodipine administration and a mean total nimodipine dose of 4.7 (± 1.2) mg. Vessel dilation was more pronounced in delayed vs. immediate controls, with greater changes in spastic vessel segments (n = 31: 113.5 (± 78.5%) vs. 32.2% (± 27.9%), p < 0.0001) vs. non-spastic vessel segments (n = 32: 23.1% (± 13.5%) vs. 13.3% (± 10.7%), p < 0.0001). In conclusion intra-arterially administered nimodipine seems to exert a delayed vasodilatory effect, which should be considered before escalation of therapy.