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Purpose: To compare qualitative and quantitative computed tomography (CT) and magnetic resonance imaging (MRI) parameters for longitudinal disease monitoring of multiple myeloma (MM) of the axial skeleton.Materials and Methods: We included 31 consecutive patients (17 m; mean age 59.20 ± 8.08 years) with MM, who underwent all baseline (n = 31) and at least one or more (n = 47) follow-up examinations consisting of multi-parametric non-enhanced whole-body MRI (WBMRI) and non-enhanced whole-body reduced-dose thin-section MDCT (NEWBMDCT) between 06/2013 and 09/2016. We classified response according to qualitative CT criteria into progression (PD), stable(SD), partial/very good partial (PR/VGPR) and complete response(CR), grouping the latter three together for statistical analysis because CT cannot reliably assess PR and CR. Qualitative MR-response criteria were defined and grouped similarly to CT using longitudinal quantification of signal-intensity changes on T1w/STIR/ T2*w and calculating ADC-values. Standard of reference was the hematological laboratory (M-gradient).Results: Hematological response categories were CR (14/47, 29.7%), PR (2/47, 4.2%), SD (16/47, 34.0%) and PD (15/47, 29.9%). Qualitative-CT-evaluation showed PD in 12/47 (25.5%) and SD/PR/VGPR/CR in 35/47 (74.5%) cases. These results were confirmed by quantitative-CT in all focal lytic lesions (p < 0.001). Quantitative-CT at sites with diffuse bone involvement showed significant increase of maximum bone attenuation (p < 0.001*) and significant decrease of minimal bone (p < 0.002*) in the SD/PR/VGPR/CR group. Qualitative MRI showed PD in 14/47 (29.7%) and SD/PR/VGPR/CR in 33/47 (70.3%). Quantitative MRI diagnosis showed a statistically significant decrease in signal intensity on short tau inversion recovery sequences (STIR) in bone marrow in patients with diffuse bone marrow involvement achieving SD/PR/VGPR/CR (p < 0.001*).Conclusion: Imaging response monitoring using MRI is superior to CT only if qualitative parameters are used, whereas there was no definite benefit from using quantitative parameters with either CT or MRI. [ABSTRACT FROM AUTHOR]

Wolfgang M Thaiss1, Cornelius C Thaiss2, Christoph A Thaiss31Christian-Albrechts-Universty, Kiel, 2Ludwig-Maximilians-University, Munich, Germany; 3Yale University School of Medicine, New Haven, CT, USAAbstract: Tuberculosis is an ancient human disease that is still a major cause of death and one of the most challenging public health problems worldwide. After decades of stagnancy, new public–private partnerships to fight the disease and the increasing awareness of a vicious circle between the tuberculosis epidemic and the obstruction of economic development have fuelled recent progress in our understanding of the disease. As a result, new strategies to improve management and treatment of tuberculosis have been initiated. At the same time, however, the devastating effect of human immunodeficiency virus on tuberculosis susceptibility and the rapid expansion of multidrug-resistant (MDR) tuberculosis threaten to undermine the advances made by tuberculosis management programs. With an estimated 9 million new cases annually, tuberculosis affects a higher number of individuals worldwide than ever before. Here, recent developments in the epidemiology and management of tuberculosis are summarized and an overview is provided of emerging strategies to combat this ancient scourge.Keywords: tuberculosis, epidemiology, management, multidrug resistance, vaccine

Desmoplastic small round blue cell tumor (DSRCT) is a highly aggressive fatal sarcoma without evidence-based therapeutic guidelines. We present here seven patients with DSRCT including immunohistochemistry combined with fluorescence in situ hybridization (FISH), next generation sequencing (NGS, n  = 6) as well as OncoScan array ( n  = 3) analyses and show consecutive therapeutic approaches. All seven DSRCT patients presented with an extended abdominal mass; median age at diagnosis was 24.8 years. NGS analyses revealed five class 4 or 5 sequence variants. Remarkably, OncoScan and targeted analyses by FISH identified genomic gains of CCND1 in two cases. Cyclin D1 expression was present in all seven tumors as shown by immunohistochemical staining. Multimodal therapeutic concepts included systemic therapies, resection, and radiation. Six patients were treated as first-line therapy with conventional chemotherapy. All except one patient had a dismal therapy response. Subsequent therapy lines consisted of chemotherapeutic combinations followed by targeted therapies. Due to Cyclin D1 expression, the CDK4/6 inhibitor palbociclib was applied to four patients. The median therapy duration until disease progression in these patients was 4.5 months (range, 1.5-5 months). So, CCND1 genomic gain and Cyclin D1 expression are common features pointing to cell-cycle deregulation as a possible therapeutic target., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2024 Verena I. Gaidzik et al.)

Hybrid positron emission tomography/magnetic resonance imaging (PET/MR) opens new possibilities in multimodal multiparametric (m2p) image analyses. But even the simultaneous acquisition of positron emission tomography (PET) and magnetic resonance imaging (MRI) does not guarantee perfect voxel-by-voxel co-registration due to organs and distortions, especially in diffusion-weighted imaging (DWI), which would be, however, crucial to derive biologically meaningful information. Thus, our aim was to optimize fusion and voxel-wise analyses of DWI and standardized uptake values (SUVs) using a novel software for m2p analyses. Using research software, we evaluated the precision of image co-registration and voxel-wise analyses including the rigid and elastic 3D registration of DWI and [18F]-Fluorodeoxyglucose (FDG)-PET from an integrated PET/MR system. We analyzed DWI distortions with a volume-preserving constraint in three different 3D-printed phantom models. A total of 12 PET/MR-DWI clinical datasets (bronchial carcinoma patients) were referenced to the T1 weighted-DIXON sequence. Back mapping of scatterplots and voxel-wise registration was performed and compared to the non-optimized datasets. Fusion was rated using a 5-point Likert scale. Using the 3D-elastic co-registration algorithm, geometric shapes were restored in phantom measurements; the measured ADC values did not change significantly (F = 1.12, p = 0.34). Reader assessment showed a significant improvement in fusion precision for DWI and morphological landmarks in the 3D-registered datasets (4.3 ± 0.2 vs. 4.6 ± 0.2, p = 0.009). Most pronounced differences were noted for the chest wall ( p = 0.006), tumor ( p = 0.007), and skin contour ( p = 0.014). Co-registration increased the number of plausible ADC and SUV combinations by 25%. The volume-preserving elastic 3D registration of DWI significantly improved the precision of fusion with anatomical sequences in phantom and clinical datasets. The research software allowed for a voxel-wise analysis and visualization of [18F]FDG-PET/MR data as a "combined diffusivity-metabolic index" (cDMI). The clinical value of the optimized PET/MR biomarker can thus be tested in future PET/MR studies.

The combination of positron-emission tomography (PET) with cross-sectional imaging in particular is becoming increasingly important in the diagnosis of head and neck tumors because, in addition to pure anatomy, the metabolic activity of tissue can be visualized and assessed. The combination of PET and computed tomography (CT) is already an established procedure in head and neck tumor patients in some indications, e.g., for primary tumor detection in cancer of unknown primary (CUP) syndrome or also after completed primary radio(chemo)therapy for evaluation of response, especially also with regard to nodal status. In some cases, salvage neck dissection can thus be avoided in the case of PET-negative findings. In the context of primary diagnosis, PET/CT imaging can be used primarily to evaluate distant metastasis. According to current guidelines, PET-based imaging is not (yet) of value in determining the local extent at initial diagnosis. A challenge is the still limited reimbursement by health insurance companies, which currently allow only certain indications, and the still lack of nationwide coverage., (© 2023. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Accurate prediction of lymph node metastasis (LNM) in patients with testicular cancer is highly relevant for treatment decision-making and prognostic evaluation. Our study aimed to develop and validate clinical radiomics models for individual preoperative prediction of LNM in patients with testicular cancer. We enrolled 91 patients with clinicopathologically confirmed early-stage testicular cancer, with disease confined to the testes. We included five significant clinical risk factors (age, preoperative serum tumour markers AFP and B-HCG, histotype and BMI) to build the clinical model. After segmenting 273 retroperitoneal lymph nodes, we then combined the clinical risk factors and lymph node radiomics features to establish combined predictive models using Random Forest (RF), Light Gradient Boosting Machine (LGBM), Support Vector Machine Classifier (SVC), and K-Nearest Neighbours (KNN). Model performance was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Finally, the decision curve analysis (DCA) was used to evaluate the clinical usefulness. The Random Forest combined clinical lymph node radiomics model with the highest AUC of 0.95 (±0.03 SD; 95% CI) was considered the candidate model with decision curve analysis, demonstrating its usefulness for preoperative prediction in the clinical setting. Our study has identified reliable and predictive machine learning techniques for predicting lymph node metastasis in early-stage testicular cancer. Identifying the most effective machine learning approaches for predictive analysis based on radiomics integrating clinical risk factors can expand the applicability of radiomics in precision oncology and cancer treatment.

Aim: The aim of this study was to derive prognostic parameters from 2-[ 18 F]fluoro-2-deoxy-D-glucose ([ 18 F]FDG-PET/CT) in patients with low-risk NSCLC and determine their prognostic value., Methods: 81 (21 female, mean age 66 a) therapy-naive patients that underwent [18F]FDG-PET/CT before histologic confirmation of NSCLC with stadium I and II between 2008-2016 were included. A mean follow-up time of 58 months (13-176), overall and progression free survival (OS, PFS) were registered. A volume of interest for the primary tumor was defined on PET and CT images. Parameters SUV max , PET-solidity, PET-circularity, and CT-volume were analyzed. To evaluate the prognostic value of each parameter for OS, a minimum p-value approach was used to define cutoff values, survival analysis, and log-rank tests were performed, including subgroup analysis for combinations of parameters., Results: Mean OS was 58±28 months. Poor OS was associated with a tumor CT-volume >14.3 cm 3 (p=0.02, HR=7.0, CI 2.7-17.7), higher SUV max values >12.2 (p=0.003; HR=3.0, CI 1.3-6.7) and PET-solidity >0.919 (p=0.004; HR=3.0, CI 1.0-8.9). Combined parameter analysis revealed worse prognosis in larger volume/high SUV max tumors compared to larger volume/lower SUV max (p=0.028; HR=2.5, CI 1.1-5.5), high PET-solidity/low volume (p=0.01; HR=2.4, CI 0.8-6.6) and low SUV max /high PET-solidity (p=0.02, HR=4.0, CI 0.8-19.0)., Conclusion: Even in this group of low-risk NSCLC patients, we identified a subgroup with a significantly worse prognosis by combining morphologic-metabolic biomarkers from [18F]FDG-PET/CT. The combination of SUV max and CT-volume performed best. Based on these preliminary data, future prospective studies to validate this combined morphologic-metabolic imaging biomarker for potential therapeutic decisions seem promising., Competing Interests: Beer AJ: AAA GmbH - Honorar Vortragstätigkeit Advisory Board Meeting Janssen-Cilag - Honorar Vortragstätigkeit VSRN Baden-Baden über KelCon - Honorar Vortragstätigkeit AAA GmbH - Honorar Vortragstätigkeit Fa. NVision Imaging Technologies GmbH Ulm - Mitglied Scientific Advisory Board - Ärztlicher Direktor Klinik für Nuklearmedizin, Universitätsklinikum Ulm - Präsident Südwestdeutsche Gesellschaft für Nuklearmedizin SWDGN - Forschungskooperation PET/MRT mit Siemens Healthcare GmbH Erlangen, (Thieme. All rights reserved.)