Comprehensive analysis of body composition features in melanoma patients treated with tyrosine kinase inhibitors.

BACKGROUND: The introduction of tyrosine kinase inhibitors (TKI) has greatly improved the management of metastatic melanoma. Recent studies have uncovered a relationship between the body mass index (BMI) and outcome of patients with metastatic melanoma. However, conflicting results have challenged the relevance of this finding. In the current work, we aim to dissect body composition features of melanoma patients treated with TKI to evaluate their value as biomarkers. PATIENTS AND METHODS: We analyze body composition features via CT scans in a retrospective cohort of 57 patients with non-resectable stage III/IV melanoma receiving first-line treatment with TKI in our department, focusing on the impact of body composition on treatment efficacy and occurrence of adverse events. RESULTS: In uni- and multivariate analyses, we identify an association between the visceral adipose tissue gauge index (VATGI) and survival. We furthermore profile additional body composition features including sarcopenia, which was also associated with a shorter overall survival. Finally, we detected an enrichment of cases with fatigue in patients with low VATGI. CONCLUSIONS: Our study represents the first exploratory study evaluating the suitability of body composition measurements as biomarkers for melanoma patients treated with TKI. Our data suggest a putative use of VATGI as a biomarker predicting patient outcome.

Short-term mortality prediction in acute pulmonary embolism: Radiomics values of skeletal muscle and intramuscular adipose tissue.

BACKGROUND: Acute pulmonary embolism (APE) is a potentially life-threatening disorder, emphasizing the importance of accurate risk stratification and survival prognosis. The exploration of imaging biomarkers that can reflect patient survival holds the potential to further enhance the stratification of APE patients, enabling personalized treatment and early intervention. Therefore, in this study, we develop computed tomography pulmonary angiography (CTPA) radiomic signatures for the prognosis of 7- and 30-day all-cause mortality in patients with APE. METHODS: Diagnostic CTPA images from 829 patients with APE were collected. Two hundred thirty-four features from each skeletal muscle (SM), intramuscular adipose tissue (IMAT) and both tissues combined (SM + IMAT) were calculated at the level of thoracic vertebra 12. Radiomic signatures were derived using 10 times repeated three-fold cross-validation on the training data for SM, IMAT and SM + IMAT for predicting 7- and 30-day mortality independently. The performance of the radiomic signatures was then evaluated on held-out test data and compared with the simplified pulmonary embolism severity index (sPESI) score, a well-established biomarker for risk stratification in APE. Predictive accuracy was assessed by the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI), sensitivity and specificity. RESULTS: The radiomic signatures based on IMAT and a combination of SM and IMAT (SM + IMAT) achieved moderate performance for the prediction of 30-day mortality on test data (IMAT: AUC = 0.68, 95% CI [0.57-0.78], sensitivity = 0.57, specificity = 0.73; SM + IMAT: AUC = 0.70, 95% CI [0.60-0.79], sensitivity = 0.74, specificity = 0.54). Radiomic signatures developed for predicting 7-day all-cause mortality showed overall low performance. The clinical signature, that is, sPESI, achieved slightly better performance in terms of AUC on test data compared with the radiomic signatures for the prediction of both 7- and 30-day mortality on the test data (7 days: AUC = 0.73, 95% CI [0.67-0.79], sensitivity = 0.92, specificity = 0.16; 30 days: AUC = 0.74, 95% CI [0.66-0.82], sensitivity = 0.97, specificity = 0.16). CONCLUSIONS: We developed and tested radiomic signatures for predicting 7- and 30-day all-cause mortality in APE using a multicentric retrospective dataset. The present multicentre work shows that radiomics parameters extracted from SM and IMAT can predict 30-day all-cause mortality in patients with APE.

Low skeletal muscle mass predicts melanoma-specific survival in melanoma patients treated with adjuvant immune checkpoint blockade.

PURPOSE: Adjuvant immunotherapy with immune checkpoint blockade(ICB) has greatly reduced the risk of recurrence and metastatic spread in early and advanced melanoma. However, not all patients benefit from adjuvant treatment: many patients show disease recurrence despite therapy, while those without recurrence harbor the risk for potentially irreversible adverse events. Biomarkers to select patients benefitting most from adjuvant therapy are currently lacking. As body composition assessment using CT images has shown promising results as a prognostic biomarker in stage IV melanoma, we aim to study the applicability of body composition parameters also in adjuvant melanoma treatment. METHODS: We analyze body composition features via CT scans in a retrospective cohort of 109 patients with resected stage IIB-IV melanoma receiving an adjuvant first-line treatment with ICB in our department. In this analysis, we focus on the impact of body composition, especially the presence of low skeletal muscle mass (LSMM), on patients' survival and occurrence of adverse events (AEs). RESULTS: In uni- and multivariate analyses, we identify an association between CT-measured LSMM and melanoma-specific survival in patients treated with adjuvant ICB. Furthermore, LSMM is associated with a lower risk for therapy-related AEs, especially hypothyroidism, fatigue, and xerostomia. Conventional serological biomarkers e.g. S100 and LDH and measures of adipose tissue compartments did not show a correlation with survival or the occurrence of AEs. CONCLUSIONS: LSMM constitutes a novel biomarker for melanoma-specific survival in patients treated with adjuvant ICB.

Low subcutaneous adipose tissue and myosteatosis are prognostic factors after allogeneic hematopoietic stem cell transplantation.

OBJECTIVE: Allogeneic hematopoietic stem cell transplantation (allo-HSCT) represents the only curative treatment option for several hematological neoplasms. This study aimed to assess the parameters of body composition as predictors of post-transplant overall survival (OS) and adverse events in patients with leukemia, myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPN). METHODS: This was a retrospective study of 122 adult patients who underwent their first allo-HSCT. The CT-based semi-automated measurement of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), visceral-to-subcutaneous fat ratio (VSR), sarcopenia in terms of skeletal muscle index (SMI), and myosteatosis based on the skeletal muscle radiation attenuation (SM-RA) was performed. Cox regression analysis was used to assess the association of body composition parameters with OS. RESULTS: In the univariate analysis, low SAT and myosteatosis were associated with lower OS (hazard ratio [HR] 2.02, 95% confidence interval [CI] 1.16-3.51, p = 0.01) and (HR 2.50, 95% CI 1.48-4.25, p =< 0.001), respectively. This association remained significant after adjusting for relevant covariates, with HR 2.32, 95% CI 1.23-4.38, p = 0.01 and HR 2.86, 95% CI 1.51-5.43, p =< 0.001, respectively. On the contrary, VAT, VSR, sarcopenia, and sarcopenic obesity were not statistically significant in OS. Severe post-transplant adverse events were more common in the low SAT group (odds ratio [OR] 3.12, 95% CI 1.32-7.40, p = 0.01) and OR 3.17, 95% CI 1.31-7.70, p =< 0.01 in the age- and sex-adjusted analysis. CONCLUSION: Low SAT and myosteatosis may contribute to an increased risk of post-transplant mortality, while low SAT appears to increase the risk of severe post-transplant adverse events.

Fat tissue quantity, waist circumference or waist-to-hip ratio in patients with chronic kidney disease: A systematic review and meta-analysis.

The BMI predicts mortality and cardiovascular disease (CVD) in the general population, while in patients with end-stage chronic kidney disease (CKD) a high BMI is associated with improved survival, a phenomenon referred to as the "obesity paradox". While BMI is easy to determine and helps to categorize patients, it does not differentiate between fat tissue, lean tissue and bone mass. As the BMI may be altered in CKD, e.g. by muscle wasting, we determined in this meta-analysis (i) the association of mortality with fat tissue quantity in CKD and (ii) the association of mortality with abdominal obesity (as measured by waist circumference (WC) or waist-to-hip ratio (WHR)) in CKD. We systematically reviewed databases for prospective or retrospective cohort studies. In eleven studies with 23,523 patients the association between mortality and high fat tissue quantity in CKD was calculated. The pooled hazard ratio (HR) for this association in the CKD group in the dialysis group 0.91 (CI 0.84- 0.98, p = 0.01) which is comparable to the HR for the association with BMI. The HR in patients without dialysis was 0.7 (95% CI 0.53- 0.93, p = 0.01), suggesting a better risk prediction of high fat tissue content with mortality as compared to higher BMI with mortality in patients with CKD without dialysis. Importantly, both BMI and fat tissue quantity in CKD are described by the "obesity paradox": the higher the fat tissue content or BMI, the lower the mortality risk. In thirteen studies with 55,175 patients the association between mortality and high WC or WHR in CKD (with or without dialysis) was calculated. We observed, that the HR in the WHR group was 1.31 (CI 1.08-1.58, p = 0.007), whereas the overall hazard ratio of both groups was 1.09 (CI 1.01-1.18, p = 0.03), indicating that a higher abdominal obesity as measured by WHR is associated with higher mortality in CKD. Our analysis suggests gender-specific differences, which need larger study numbers for validation. This meta-analysis confirms the obesity paradox in CKD using fat tissue quantity as measure and further shows that using abdominal obesity measurements in the routine in obese CKD patients might allow better risk assessment than using BMI or fat tissue quantity. Comparable to the overall population, here, the higher the WHR, the higher the mortality risk.

Diagnostic value of apparent diffusion coefficient of psoas muscles for evaluating complications in patients with Crohn's disease.

Aim: To assess the association of the apparent diffusion coefficient (ADC) of the psoas muscles and psoas muscle index (PMI) with the activity and behaviour of Crohn's disease (CD). Material and methods: This was a retrospective study of 88 CD patients who underwent magnetic resonance enterography. Patients were classified according to the Montreal Classification in uncomplicated (non-stricturing, non-penetrating, B1), and complicated (structuring [B2] and penetrating disease [B3]). At the level of the third lumbar vertebra, the ADC and PMI were estimated. CD activity was analysed using the Magnetic Resonance Index of Activity (MaRIA), and depending on its values patients were categorized as high or low activity. Additionally, the presence of creeping fat (CrF) was used to evaluate activity. ADC and PMI were using Student's t-test. Results: Our study included 47 males and 41 females (mean age of 38.69 ±14.4 years). The ADC in uncomplicated (B1, n = 45) and complicated disease (B2 + B3, n = 43) were 1.11 ±0.19 and 1.03 ±0.10 (10-3*mm2/s), respectively, (p = 0.02). ADC was significantly lower in patients with stricturing disease than in patients without strictures (1.02 ±0.11 and 1.10 ±0.18 [10-3 mm2/s], respectively, p = 0.01). The group with non-penetrating disease showed higher PMI than those with penetrating disease (5.71 ±1.88 vs. 4.42 ±1.55 cm2/m2, respectively, p = 0.10). There was no significant difference in PMI and ADC between patients with low and high MaRIA or positive and negative CrF. Conclusions: The ADC of the psoas muscles is significantly lower in CD patients with uncomplicated disease, particularly those with stricturing disease. Therefore, ADC can be considered as an imaging biomarker of myopathic changes in CD patients.

Photon counting computed tomography of in-stent-stenosis in a phantom: Optimal virtual monoenergetic imaging in ultra high resolution.

Rationale and objectives: Coronary computed tomography angiography (CCTA) is becoming increasingly important for the diagnostic workup of coronary artery disease, nevertheless, imaging of in-stent stenosis remains challenging. For the first time, spectral imaging in Ultra High Resolution (UHR) is now possible in clinically available photon counting CT. The aim of this work is to determine the optimal virtual monoenergetic image (VMI) for imaging in-stent stenoses in cardiac stents. Materials and methods: 6 stents with inserted hypodense stenoses were scanned in an established phantom in UHR mode. Images were reconstructed with 3 different kernels for spectral data (Qr56, Qr64, Qr72) with varying levels of sharpness. Based on region of interest (ROI) measurements image quality parameters including contrast-to-noise ratio (CNR) were analyzed for all available VMI (40 keV-190 keV). Finally, based on quantitative results and VMI used in clinical routine, a set of VMI was included in a qualitative reading. Results: CNR showed significant variations across different keV levels (p < 0.001). Due to reduced noise there was a focal maximum in the VMI around 65 keV. The peak values were observed for kernel Qr56 at 116 keV with 19.47 ± 8.67, for kernel Qr64 at 114 keV with 13.56 ± 6.58, and for kernel Qr72 at 106 keV with 12.19 ± 3.25. However, in the qualitative evaluation the VMI with lower keV (55 keV) performed best. Conclusions: Based on these experimental results, a photon counting CCTA in UHR with stents should be reconstructed with the Qr72 kernel for the assessment of in-stent stenoses, and a VMI 55 keV should be computed for the evaluation.

Association between sacroiliac joint forms and subchondral changes in patients with Crohn's disease.

AIM: To assess the relationship between anatomical variants of sacroiliac joint (SIJ) and subchondral changes detected in magnetic resonance enterography (MRE) in patients with Crohn's disease (CD). METHODS: This was a retrospective study of 60 CD patients, who were divided into two groups: with (n = 16) and without SIJ (n = 44) involvement, depending on the presence of inflammatory (bone marrow edema) and structural changes (sclerosis and erosions) in MRE. Anatomical variants of SIJ were assessed in CT of the abdomen and/or pelvis, distinguishing typical form with convex iliac surface and atypical forms. Univariate and multivariate analyses were performed to reveal an association between joint changes and forms. RESULTS: Our study included 60 patients (38 males; mean age 38.72 years ± 13.33). Patients with SIJ changes were older (p = .044). No significant differences in CD localization and behavior were found. The most common SIJ lesions were structural changes (in 75% of patients); the main atypical form was the iliosacral complex. The univariate and multivariate analyses showed a significant association of atypical forms with total subchondral changes (odds ratio [OR]: 3.429, 95% confidence interval [CI] 1.043-11.268; p = .042; OR: 5.066, 95% CI: 1.273-20.167; p = .021, respectively), and with structural changes (OR: 4.185, 95% CI: 1.155-15.160; p = .029; OR: 5.986, 95% CI: 1.293-27.700; p = .022, respectively). CONCLUSION: Atypical forms of SIJ are a risk factor for the occurrence of structural joint changes in CD patients. An association between bone marrow edema and atypical forms was not found.

Imaging of intracranial hemorrhage in photon counting computed tomography using virtual monoenergetic images.

PURPOSE: To determine the optimal virtual monoenergetic image (VMI) for detecting and assessing intracranial hemorrhage in unenhanced photon counting CT of the head based on the evaluation of quantitative and qualitative image quality parameters. METHODS: Sixty-three patients with acute intracranial hemorrhage and unenhanced CT of the head were retrospectively included. In these patients, 35 intraparenchymal, 39 intraventricular, 30 subarachnoidal, and 43 subdural hemorrhages were selected. VMIs were reconstructed using all available monoenergetic reconstruction levels (40-190 keV). Multiple regions of interest measurements were used for evaluation of the overall image quality, and signal, noise, signal-to-noise-ratio (SNR), and contrast-to-noise-ratio (CNR) of intracranial hemorrhage. Based on the results of the quantitative analysis, specific VMIs were rated by five radiologists on a 5-point Likert scale. RESULTS: Signal, noise, SNR, and CNR differed significantly between different VMIs (p < 0.001). Maximum CNR for intracranial hemorrhage was reached in VMI with keV levels > 120 keV (intraparenchymal 143 keV, intraventricular 164 keV, subarachnoidal 124 keV, and subdural hemorrhage 133 keV). In reading, no relevant superiority in the detection of hemorrhage could be demonstrated using VMIs above 66 keV. CONCLUSION: For the detection of hemorrhage in unenhanced CT of the head, the quantitative analysis of the present study on photon counting CT is generally consistent with the findings from dual-energy CT, suggesting keV levels just above 120 keV and higher depending on the location of the hemorrhage. However, on the basis of the qualitative analyses, no reliable statement can yet be made as to whether an additional VMI with higher keV is truly beneficial in everyday clinical practice.

Pancreatic cancer in photon-counting CT: Low keV virtual monoenergetic images improve tumor conspicuity.

PURPOSE OF THE STUDY: The aim of the study was to identify differences in the tumor conspicuity of pancreatic adenocarcinomas in different monoenergetic or polyenergetic reconstructions and contrast phases in photon-counting CT (PCCT). MATERIAL AND METHODS: 34 patients were retrospectively enrolled in this study. Quantitative image analysis was performed with region of interest (ROI) measurements in different monoenergetic levels ranging from 40 up to 70 keV (5-point steps) and polyenergetic series. Tumor-parenchyma attenuation differences and contrast-to-noise-ratio (CNR) were calculated. A qualitative image analysis was accomplished by 4 radiologists using a 5-point Likert scale (1 = "not recognizable" up to 5 = "easy recognizable"). Differences between groups were evaluated for statistical significance using the Friedman test and in case of significant differences pair-wise post-hoc testing with Bonferroni correction was applied. RESULTS: Tumor-parenchyma attenuation difference was significantly different between the different image reconstructions for both arterial- and portal-venous-phase-images (p < 0.001). Tumor-parenchyma attenuation difference was significantly higher on arterial-phase-images at mono40keV compared to polyenergetic images (p < 0.001) and mono55keV images or higher (p < 0.001). For portal-venous-phase-images tumor-parenchyma attenuation difference was significantly higher on mono40keV images compared to polyenergetic images (p < 0.001) and mono50keV images (p = 0.03) or higher (p < 0.001). The same trend was seen for CNR. Tumor conspicuity was rated best on mono40keV images with 4.3 ± 0.9 for arterial-phase-images and 4.3 ± 1.1 for portal-venous-phase-images. In contrast, overall image quality was rated best on polyenergetic-images with 4.8 ± 0.5 for arterial-phase-images and 4.7 ± 0.6 for portal-venous-phase-images. CONCLUSION: Low keV virtual monoenergetic images significantly improve the tumor conspicuity of pancreatic adenocarcinomas in PCCT based on quantitative and qualitative results. On the other hand, readers prefer polyenergetic images for overall image quality.

Parameters of body composition do not predict survival in patients with multiple myeloma undergoing autologous stem cell transplantation.

Studies regarding the influence of body composition parameters as predictors on overall survival (OS) in patients with multiple myeloma (MM) are scarce. OS and progression-free survival (PFS) were retrospectively assessed in 129 patients with MM undergoing autologous stem cell transplantation (ASCT) after a follow-up of 2 years. A computed tomography (CT) based semi-automated assessment of body composition was performed. No statistically significant differences were noted in 2-year OS, PFS, or post-transplant adverse events in the body composition groups of subcutaneous adipose tissue (SAT) (low vs. high-SAT), visceral adipose tissue (VAT) (low vs. high-VAT), visceral-to-subcutaneous fat ratio (VSR) (low vs. high VSR), and sarcopenia in terms of skeletal muscle index (SMI) (non-sarcopenic vs. sarcopenic). In conclusion, adipose and muscle tissue do not limit OS or affect the PFS in patients with MM undergoing ASCT.

Photon Counting Computed Tomography in Rectal Cancer: Associations Between Iodine Concentration, Histopathology and Treatment Response: A Pilot Study.

RATIONALE AND OBJECTIVES: Common computed tomography (CT) investigation plays a limited role in characterizing and assessing the response of rectal cancer (RC) to neoadjuvant radiochemotherapy (NARC). Photon counting computed tomography (PCCT) improves the imaging quality and can provide multiparametric spectral image information including iodine concentration (IC). Our purpose was to analyze associations between IC and histopathology in RC and to evaluate the role of IC in response prediction to NARC. MATERIALS AND METHODS: Overall, 41 patients were included into the study, 14 women and 27 men, mean age, 65.5 years. PCCT in a portal venous phase of the abdomen was performed. In every case, a polygonal region of interest (ROI) was manually drawn on iodine maps. Normalized IC (NIC) was also calculated. Tumor stage, grade, lymphovascular invasion, circumferential resection margin, and tumor markers were analyzed. Tumor regression grade (absence/presence of tumor cells) after NARC was analyzed. NIC values in groups were compared to Mann-Whitney-U tests. Sensitivity, specificity, and area under the curve values were calculated. Intraclass correlation coefficient (ICC) was calculated. RESULTS: ICC was 0.93, 95%CI= (0.88; 0.96). Tumors with lymphovascular invasion showed higher NIC values in comparison to those without (p = 0.04). Tumors with response grade 2-4 showed higher pretreatment NIC values in comparison to lesions with response grade 0-1 (p = 0.01). A NIC value of 0.36 and higher can predict response grade 2-4 (sensitivity, 73.9%; specificity, 91.7%; area under the curve, 0.85). CONCLUSION: NIC values showed an excellent interreader agreement in RC. NIC can predict treatment response to NARC.

Myosteatosis predicts short-term mortality in patients with COVID-19: A multicenter analysis.

OBJECTIVES: Body composition on computed tomography can predict prognosis in patients with COVID-19. The reported data are based on small retrospective studies. The aim of the present study was to analyze the prognostic relevance of skeletal muscle parameter derived from chest computed tomography for prediction of 30-d mortality in patients with COVID-19 in a multicenter setting. METHODS: The clinical databases of three centers were screened for patients with COVID-19 between 2020 and 2022. Overall, 447 patients (142 female; 31.7%) were included into the study. The mean age at the time of computed tomography acquisition was 63.8 ± 14.7 y and median age was 65 y. Skeletal muscle area and skeletal muscle density were defined on level T12 of the chest. RESULTS: Overall, 118 patients (26.3%) died within the 30-d observation period. Of the patient sample, 255 patients (57.0%) were admitted to an intensive care unit and 122 patients needed mechanical ventilation (27.3%). The mean skeletal muscle area of all patients was 96.1 ± 27.2 cm² (range = 23.2-200.7 cm²). For skeletal muscle density, the mean was 24.3 ± 11.1 Hounsfield units (range = -5.6 to 55.8 Hounsfield units). In survivors, the mean skeletal muscle density was higher compared with the lethal cases (mean 25.8 ± 11.2 versus 20.1 ± 9.6; P < 0.0001). Presence of myosteatosis was independently associated with 30-d mortality: odds ratio = 2.72 (95% CI, 1.71-4.32); P = 0.0001. CONCLUSIONS: Myosteatosis is strongly associated with 30-d mortality in patients COVID-19. Patients with COVID-19 with myosteatosis should be considered a risk group.

Automated Patient Registration in Magnetic Resonance Imaging Using Deep Learning-Based Height and Weight Estimation with 3D Camera: A Feasibility Study.

RATIONALE AND OBJECTIVES: Accurate and efficient estimation of patient height and weight is crucial to ensure patient safety and optimize the quality of magnetic resonance imaging (MRI) procedures. Several height and weight estimation methods have been proposed for use in adult patient management, but none is widely established. Estimation by the medical technologists for radiology (MTR) based on personal experience remains to be the most common method. This study aimed to compare a novel deep learning (DL)-based 3-dimensional (3D) camera estimation method to MTR staff in terms of estimation accuracy. METHODS: A retrospective study was conducted to compare the accuracy of height and weight estimation with a DL-based 3D camera algorithm to the accuracy of height and weight estimation by the MTR. Depth images of the patients were captured during the regular imaging workflow on a low field 0.55 T MRI scanner (MAGNETOM Free.Max, Siemens Healthineers, Erlangen, Germany) and then processed retrospectively. Depth images of a total of 161 patients were used to validate the accuracy of the height and weight estimation algorithm. The accuracy of each estimation method was evaluated by computing the proportions of the estimates within 5% and 15% of actual height (PH05, PH15) and within 10% and 20% of actual weight (PW10, PW20). An acceptable accuracy for height estimation was predetermined to be PH05 = 95% and PH15 = 99% and an acceptable accuracy for weight estimation was predetermined to be PW10 = 70% and PW20 = 95%. The bias in height and weight estimation was measured by the mean absolute percentage error (MAPE). RESULTS: The retrospective study included 161 adult patients. For 148/161 patients complying with inclusion criteria, DL-based 3D camera algorithm outperformed the MTR in estimating the patient's height and weight in term of accuracy (3D camera: PH05 =98.6%, PH15 =100%, PW10 =85.1%, PW20 =95.9%; MTR: PH05 =92.5%, PH15 =100%, PW10 =75.0%, PW20 =93.2%). MTR had a slightly higher bias in their estimates compared to the DL-based 3D camera algorithm (3D camera: MAPE height=1.8%, MAPE weight=5.6%, MTR: MAPE height=2.2%, MAPE weight=7.5%) CONCLUSION: This study has demonstrated that the estimation of the patient's height and weight by a DL-based 3D camera algorithm is accurate and robust. It has the potential to complement the regular MRI workflows, by providing further automation during patient registration.

Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction.

We investigated the effect of deep learning-based image reconstruction (DLIR) compared to iterative reconstruction on image quality in CT pulmonary angiography (CTPA) for suspected pulmonary embolism (PE). For 220 patients with suspected PE, CTPA studies were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASiR-V 30%, 60% and 90%) and DLIR (low, medium and high strength). Contrast-to-noise ratio (CNR) served as the primary parameter of objective image quality. Subgroup analyses were performed for normal weight, overweight and obese individuals. For patients with confirmed PE (n = 40), we further measured PE-specific CNR. Subjective image quality was assessed independently by two experienced radiologists. CNR was lowest for FBP and enhanced with increasing levels of ASiR-V and, even more with increasing strength of DLIR. High strength DLIR resulted in an additional improvement in CNR by 29-67% compared to ASiR-V 90% (p < 0.05). PE-specific CNR increased by 75% compared to ASiR-V 90% (p < 0.05). Subjective image quality was significantly higher for medium and high strength DLIR compared to all other image reconstructions (p < 0.05). In CT pulmonary angiography, DLIR significantly outperforms iterative reconstruction for increasing objective and subjective image quality. This may allow for further reductions in radiation exposure in suspected PE.

Diffusion-weighted MRI (DWI) for assessment of response to high-dose-rate CT-guided brachytherapy (HDR-BT) of hepatocellular carcinoma.

BACKGROUND: High-dose-rate computed tomography (CT)-guided brachytherapy (HDR-BT) has shown promising results in patients with hepatocellular carcinoma (HCC). While growing evidence shows clear limitations of mRECIST, diffusion-weighted imaging (DWI) has relevant potential in improving the response assessment. PURPOSE: To assess whether DWI allows evaluation of short- and long-term tumor response in patients with HCC after HDR-BT. MATERIAL AND METHODS: A total of 22 patients with 11 non-responding HCCs (NR-HCC; local tumor recurrence within two years) and 24 responding HCCs (R-HCC; follow-up at least two years) were included in this retrospective bi-center study. HCCs were treated with HDR-BT and patients underwent pre- and post-interventional magnetic resonance imaging (MRI). Analyses of DWI were evaluated and compared between pre-interventional MRI, 1.follow-up after 3 months and 2.follow-up at the time of the local tumor recurrence (in NR-HCC) or after 12 months (in R-HCC). RESULTS: ADCmean of R-HCC increased significantly after HDR-BT on the first and second follow-up (ADCmean: 0.87 ± 0.18 × 10-3 mm2/s [pre-interventional]: 1.14 ± 0.23 × 10-3 mm2/s [1. post-interventional]; 1.42 ± 0.32 × 10-3 mm2/s [2. post-interventional]; P < 0.001). ADCmean of NR-HCC did not show a significant increase from pre-intervention to 1. post-interventional MRI (ADCmean: 0.85 ± 0.24 × 10-3 mm2/s and 1.00 ± 0.30 × 10-3 mm2/s, respectively; P = 0.131). ADCmean increase was significant between pre-intervention and 2. follow-up (ADCmean: 1.03 ± 0.19 × 10-3 mm2/s; P = 0.018). There was no significant increase of ADCmean between the first and second follow-up. There was, however, a significant increase of ADCmin after 12 months (ADCmin: 0.87 ± 0.29 × 10-3 mm2/s) compared to pre-interventional MRI and first follow-up (P < 0.005) only in R-HCC. CONCLUSION: The tumor response after CT-guided HDR-BT was associated with a significantly higher increase in ADCmean and ADCmin in short- and long-term follow-up.

CT-defined sarcopenia predicts treatment response in primary central nervous system lymphomas.

OBJECTIVE: Body composition assessment derived from cross-sectional imaging has shown promising results as a prognostic biomarker in several tumor entities. Our aim was to analyze the role of low skeletal muscle mass (LSMM) and fat areas for prognosis of dose-limiting toxicity (DLT) and treatment response in patients with primary central nervous system lymphoma (PCNSL). METHODS: Overall, 61 patients (29 female patients, 47.5%) with a mean age of 63.8 ± 12.2 years, range 23-81 years, were identified in the data base between 2012 and 2020 with sufficient clinical and imaging data. Body composition assessment, comprising LSMM and visceral and subcutaneous fat areas, was performed on one axial slice on L3-height derived from staging computed tomography (CT) images. DLT was assessed during chemotherapy in clinical routine. Objective response rate (ORR) was measured on following magnetic resonance images of the head accordingly to the Cheson criteria. RESULTS: Twenty-eight patients had DLT (45.9%). Regression analysis revealed that LSMM was associated with objective response, OR = 5.19 (95% CI 1.35-19.94, p = 0.02) (univariable regression), and OR = 4.23 (95% CI 1.03- 17.38, p = 0.046) (multivariable regression). None of the body composition parameters could predict DLT. Patients with normal visceral to subcutaneous ratio (VSR) could be treated with more chemotherapy cycles compared to patients with high VSR (mean, 4.25 vs 2.94, p = 0.03). Patients with ORR had higher muscle density values compared to patients with stable and/or progressive disease (34.46 ± vs 28.18 ± HU, p = 0.02). CONCLUSIONS: LSMM is strongly associated with objective response in patients with PCNSL. Body composition parameters cannot predict DLT. CLINICAL RELEVANCE STATEMENT: Low skeletal muscle mass on computed tomography (CT) is an independent prognostic factor of poor treatment response in central nervous system lymphoma. Analysis of the skeletal musculature on staging CT should be implemented into the clinical routine in this tumor entity. KEY POINTS: • Low skeletal muscle mass is strongly associated with the objective response rate. • No body composition parameters could predict dose-limiting toxicity.