The Apparent Diffusion Coefficient of the Paraspinal and Psoas Muscles Are of Prognostic Relevance in Patients With Hepatocellular Carcinoma Undergoing Transarterial Radioembolization

Background/Aim

Transarterial radioembolization (TARE) is a treatment option for early or intermediate stage hepatocellular carcinoma (HCC). Sarcopenia is defined as loss of muscle strength and quality which can be estimated by imaging modalities and has been associated with prognosis and treatment response in HCC patients. Apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) can reflect the tissue composition and might be better to determine muscle changes of sarcopenia than the standard method of computed tomography (CT). The present study sought to elucidate ADC values of the abdominal wall muscles as a prognostic factor in patients undergoing TARE.

Patients and Methods

A retrospective analysis was performed between 2016 and 2020. Overall, 52 patients, 9 women (17.3%) and 43 men (82.7%), with a mean age of 69±8.5 years were included into the analysis. In every case, the first pre-interventional magnetic resonance imaging (MRI) including DWI was used to measure the ADC values of paraspinal and psoas muscle. The 12-month survival after TARE was used as the primary study outcome.

Results

Overall, 40 patients (76.9%) of the patient cohort died within the 12-month observation period. Mean overall survival was 10.9 months after TARE for all patients. Mean ADC values for all muscles were 1.31±0.13×10-3mm2/s. The ADC values of the paraspinal muscles were statistically significantly higher compared to the ADC values of the psoas muscles (p=0.0031). A positive correlation was identified between mean ADC and the thrombocyte count (r=0.37, p=0.005) and serum bilirubin (r=-0.30, p=0.03). In the multivariate Cox regression analysis, the mean ADC values of all muscles were associated with the survival after 12 months (HR=0.98, 95% CI=0.97-0.99, p=0.04).

Conclusion

ADC values of the abdominal wall muscles could be used as a prognostic biomarker in patients with HCC undergoing TARE. These preliminary results should be confirmed by further studies using external validation cohorts and other treatment modalities.

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.

Standardization of a CT Protocol for Imaging Patients with Suspected COVID-19-A RACOON Project

CT protocols that diagnose COVID-19 vary in regard to the associated radiation exposure and the desired image quality (IQ). This study aims to evaluate CT protocols of hospitals participating in the RACOON (Radiological Cooperative Network) project, consolidating CT protocols to provide recommendations and strategies for future pandemics. In this retrospective study, CT acquisitions of COVID-19 patients scanned between March 2020 and October 2020 (RACOON phase 1) were included, and all non-contrast protocols were evaluated. For this purpose, CT protocol parameters, IQ ratings, radiation exposure (CTDIvol), and central patient diameters were sampled. Eventually, the data from 14 sites and 534 CT acquisitions were analyzed. IQ was rated good for 81% of the evaluated examinations. Motion, beam-hardening artefacts, or image noise were reasons for a suboptimal IQ. The tube potential ranged between 80 and 140 kVp, with the majority between 100 and 120 kVp. CTDIvol was 3.7 ± 3.4 mGy. Most healthcare facilities included did not have a specific non-contrast CT protocol. Furthermore, CT protocols for chest imaging varied in their settings and radiation exposure. In future, it will be necessary to make recommendations regarding the required IQ and protocol parameters for the majority of CT scanners to enable comparable IQ as well as radiation exposure for different sites but identical diagnostic questions.

Pericardial Effusion Predicts Clinical Outcomes in Patients with COVID-19: A Nationwide Multicenter Study

RATIONALE AND OBJECTIVES

The prognostic role of pericardial effusion (PE) in Covid 19 is unclear. The aim of the present study was to estimate the prognostic role of PE in patients with Covid 19 in a large multicentre setting.

MATERIALS AND METHODS

This retrospective study is a part of the German multicenter project RACOON (Radiological Cooperative Network of the Covid 19 pandemic). The acquired sample comprises 1197 patients, 363 (30.3%) women and 834 (69.7%) men. In every case, chest computed tomography was analyzed for PE. Data about 30-day mortality, need for mechanical ventilation and need for intensive care unit (ICU) admission were collected. Data were evaluated by means of descriptive statistics. Group differences were calculated with Mann-Whitney test and Fisher exact test. Uni-and multivariable regression analyses were performed.

RESULTS

Overall, 46.4% of the patients were admitted to ICU, mechanical lung ventilation was performed in 26.6% and 30-day mortality was 24%. PE was identified in 159 patients (13.3%). The presence of PE was associated with 30-day mortality: HR= 1.54, CI 95% (1.05; 2.23), p = 0.02 (univariable analysis), and HR= 1.60, CI 95% (1.03; 2.48), p = 0.03 (multivariable analysis). Furthermore, density of PE was associated with the need for intubation (OR=1.02, CI 95% (1.003; 1.05), p = 0.03) and the need for ICU admission (OR=1.03, CI 95% (1.005; 1.05), p = 0.01) in univariable regression analysis. The presence of PE was associated with 30-day mortality in male patients, HR= 1.56, CI 95%(1.01-2.43), p = 0.04 (multivariable analysis). In female patients, none of PE values predicted clinical outcomes.

CONCLUSION

The prevalence of PE in Covid 19 is 13.3%. PE is an independent predictor of 30-day mortality in male patients with Covid 19. In female patients, PE plays no predictive role.

Analysis of Periprocedural X-ray Exposure in Transarterial Radioembolization with Glass or Resin Microspheres

Background: Transarterial Radioembolization (TARE) is an effective treatment option for both primary and secondary liver malignancies. However, challenging anatomical conditions can lead to prolonged fluoroscopy times (FT), elevated doses of periprocedural X-radiation (DAP), and increased use of contrast agents (CAs). In this study, we examined the influence of our radiologists' experience and the choice of microspheres on X-ray exposure and CA doses in TARE. Material and Methods: Datasets comprising 161 TARE and 164 preprocedural evaluation angiographies (TARE-EVA) were analyzed. Our study focused on assessing DAP, FT, and CA concerning both microsphere types, the radiologist's experience, and whether the same radiologist performed both the TARE-EVA and the actual TARE. Results: In TARE, the use of resin microspheres resulted in significantly higher FT and CA compared to glass microspheres (14.3 ± 1.6 min vs. 10.6 ± 1.1 min and 43 ± 2.2 mL vs. 33.6 ± 2.1 mL, p < 0.05), with no notable differences in DAP (p = 0.13). Experienced radiologists demonstrated reduced FT/DAP, with a 19% decrease in DAP and 53% in FT during the evaluation angiography (p < 0.05) and a 49% reduction in DAP during the actual TARE (p < 0.05), with no statistical differences in FT. Performing TARE and TARE-EVA under the same radiologist led to a 43% reduction in DAP and a 25% decrease in FT (p < 0.05, respectively). Conclusions: To mitigate X-radiation exposure, it is advisable for radiologists to undergo thorough training, and, ideally, the same radiologist should conduct both the TARE and the TARE-EVA. While the use of glass spheres may decrease intraarterial CA, it does not significantly impact periprocedural X-ray exposure.

Benefits of Dual-Layer Spectral CT Imaging in Staging and Preoperative Evaluation of Pancreatic Ductal Adenocarcinoma

Imaging of pancreatic malignancies is challenging but has a major impact on the patients therapeutic approach and outcome. In particular with pancreatic ductal adenocarcinoma (PDAC), usually a hypovascularized tumor, conventional CT imaging can be prone to errors in determining tumor extent and presence of metastatic disease. Dual-layer spectral detector CT (SDCT) is an emerging technique for acquiring spectral information without the need for prospective patient selection or specific protocols, with a detector capable of differentiating high- and low-energy photons to acquire full spectral images. In this review, we present the diagnostic benefits and capabilities of modern SDCT imaging with a focus on PDAC. We highlight the most useful virtual reconstructions in oncologic imaging and their benefits in staging and assessment of resectability in PDAC, including the assessment of tumor extent, vascular infiltration, and metastatic disease. We present imaging examples on a latest-generation SDCT scanner.

Challenges in Implementing the Local Node Infrastructure for a National Federated Machine Learning Network in Radiology

Data-driven machine learning in medical research and diagnostics needs large-scale datasets curated by clinical experts. The generation of large datasets can be challenging in terms of resource consumption and time effort, while generalizability and validation of the developed models significantly benefit from variety in data sources. Training algorithms on smaller decentralized datasets through federated learning can reduce effort, but require the implementation of a specific and ambitious infrastructure to share data, algorithms and computing time. Additionally, it offers the opportunity of maintaining and keeping the data locally. Thus, data safety issues can be avoided because patient data must not be shared. Machine learning models are trained on local data by sharing the model and through an established network. In addition to commercial applications, there are also numerous academic and customized implementations of network infrastructures available. The configuration of these networks primarily differs, yet adheres to a standard framework composed of fundamental components. In this technical note, we propose basic infrastructure requirements for data governance, data science workflows, and local node set-up, and report on the advantages and experienced pitfalls in implementing the local infrastructure with the German Radiological Cooperative Network initiative as the use case example. We show how the infrastructure can be built upon some base components to reflect the needs of a federated learning network and how they can be implemented considering both local and global network requirements. After analyzing the deployment process in different settings and scenarios, we recommend integrating the local node into an existing clinical IT infrastructure. This approach offers benefits in terms of maintenance and deployment effort compared to external integration in a separate environment (e.g., the radiology department). This proposed groundwork can be taken as an exemplary development guideline for future applications of federated learning networks in clinical and scientific environments.

Magnetic Resonance Imaging of Peritoneal Carcinomatosis: Evaluation of High b-Value Computed Diffusion-Weighted Imaging

Over the last few years, diffusion-weighted imaging (DWI) has become increasingly relevant in the diagnostic assessment of peritoneal carcinomatosis. The aim of this study was to investigate the benefits of high-b DWI (c-DWI) compared to standard DWI in patients with peritoneal carcinomatosis. A cohort of 40 patients with peritoneal carcinomatosis were included in this retrospective study. DWI was performed with b-values of 50, 400, and 800 or 1000 s/mm² on a 1.5-T magnetic resonance imaging (MRI) scanner. C-DWI was calculated using a mono-exponential model with high b-values of 1000, 2000, 3000, 4000, and 5000 s/mm². All c-DWI images with high b-values were compared in terms of volume, detectability of peritoneal lesions, and image quality with the DWI sequence acquired with a b-value of 800 or 1000 s/mm² by two readers. In the group with a b-value of 800 s/mm², there was no statistically significant difference in terms of lesion volume. In the second group with a b-value of 1000 s/mm², peritoneal carcinomatosis lesions were statistically significantly larger than in the c-DWI with a- high b-value of 2000 s/mm² (median 7 cm³, range 1−26 cm³vs. median 6 cm³, range 1−83 cm³, p < 0.05). In both groups, there was a marked decrease in the detectability of peritoneal lesions starting at b = 2000 s/mm². In addition, image quality decreased noticeably from c-DWI at b = 3000 s/mm². In both groups, all images with high b-values at b = 4000 s/mm² and 5000 s/mm² were not diagnostically valuable due to poor image quality. The c-DWI technique offers good diagnostic performance without additional scanning time. High c-DWI b-values up to b = 1000 s/mm² provide comparable detectability of peritoneal carcinomatosis compared to standard DWI. Higher b-values over 1500 s/mm² result in lower image quality, which might lead to misdiagnosis.

[Thoracolumbar back pain as the leading symptom of a marked COVID-19 pneumonia]

HISTORY

 A 49-year-old male patient visited the surgical outpatient clinic with new onset low back pain. The pain was increasing for nine days and he did not have any signs of a respiratory infection, in particular neither fever nor cough.

INVESTIGATIONS

 During the further examination and unclothing, mild dyspnea was apparent. According to the patient, the dyspnea was also progressive in the last days but would not affect everyday life. Furthermore, the patient reported a significant and unintended weight loss. Outpatient chest X-ray revealed bilateral, peripheral, fine-speckled infiltrates that became increasingly confluent. Polymerase chain reaction analysis of the nasopharyngeal swab was positive for SARS-CoV-2 (wild type).

TREATMENT AND COURSE

 Due to progressive dyspnea, the patient was referred to inpatient treatment within the day, where he rapidly developed severe acute respiratory failure. To provide respiratory support, a combined intermittent non-invasive ventilation and nasal high flow-therapy was started. Moreover, a probatory antiviral therapy with remdesivir was initiated. Since a bacterial superinfection was suspected, additional antibiotic therapy was ordered. After 13 days of inpatient treatment, the patient was discharged. The low back pain receded completely during inpatient treatment without any specific therapy.

CONCLUSIONS

 Low back pain can be a symptom of COVID-19. In our case report, it was the only complain that led to the outpatient consultation. Even though back pain is a very common symptom in everyday practice, one should keep unusual causes in mind.

Restructuring of a Hospital Radiology Department: Subspecialization Between Man, Machine, and Multidisciplinary Board

BACKGROUND

 Radiology, like almost no other discipline, is faced with a rapid increase in information and technology. This and the growing demands regarding referring medicine, quality requirements, and personnel efficiency increasingly require subspecialization in terms of content. There is already an established move towards radiological subspecialization in the Anglo-American region. In this review article, the content and possibilities of restructuring a hospital radiology department are presented in order to support acceptance in German-speaking countries.

METHOD

 Based on the current literature, the aspects of subspecialized radiology as well as its necessity, advantages, and disadvantages are discussed and the challenges to hospital management with respect to strategic implementation in the individual phases are presented based on the example of a university radiology department. The viewpoints also take into account the education regulations and integrate a modern learning concept.

RESULTS AND CONCLUSION

 Modern restructuring of hospital radiology departments is faced with increasing demands on a traditionally technically organized radiology department with regard to the complexity of referring medicine, subspecialization pressure (including in certified boards), and staff efficiency. The restructuring of a radiology department must be aligned with the clinical requirements and discussed in the overall concept of radiology including its environment.

KEY POINTS

  · The tremendous expansion of knowledge requires a content-based subspecialization of modern radiology as a cross-sectional discipline.. · Proactive radiology meets the increasing demands of its clinical partners and offers great potential for improving quality and efficiency.. · The restructuring of a hospital radiology department requires well-planned strategic management taking into account all involved processes, resources, and personnel qualifications..

CITATION FORMAT

· Henkelmann J, Ehrengut C, Denecke T. Restructuring of a Hospital Radiology Department: Subspecialization Between Man, Machine, and Multidisciplinary Board. Fortschr Röntgenstr 2021; DOI: 10.1055/a-1545-4713.