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Background: Prolonged myelosuppression following CD19-directed CAR T-cell transfusion represents an important, yet underreported, adverse event. The resulting neutropenia and multifactorial immunosuppression can facilitate severe infectious complications.Case Presentation: We describe the clinical course of a 59-year-old patient with relapsed/refractory DLBCL who received Axicabtagene-Ciloleucel (Axi-cel). The patient developed ASTCT grade I CRS and grade IV ICANS, necessitating admission to the neurological ICU and prolonged application of high-dose corticosteroids and other immunosuppressive agents. Importantly, neutropenia was profound (ANC < 100/μl), G-CSF-refractory, and prolonged, lasting more than 50 days. The patient developed severe septic shock 3 weeks after CAR transfusion while receiving anti-fungal prophylaxis with micafungin. His clinical status stabilized with broad anti-infective treatment and intensive supportive measures. An autologous stem cell backup was employed on day 46 to support hematopoietic recovery. Although the counts of the patient eventually started to recover, he developed an invasive pulmonary aspergillosis, which ultimately lead to respiratory failure and death. Postmortem examination revealed signs of Candida glabrata pancolitis.Conclusions: This case highlights the increased risk for fatal infectious complications in patients who present with profound and prolonged cytopenia after CAR T-cell therapy. We describe a rare case of C. glabrata pancolitis associated with multifactorial immunosuppression. Although our patient succumbed to a fatal fungal infection, autologous stem cell boost was able to spur hematopoiesis and may represent an important therapeutic strategy for DLBCL patients with CAR T-cell associated bone marrow aplasia who have underwent prior stem cell harvest. [ABSTRACT FROM AUTHOR]

Crossed cerebellar diaschisis (CCD) is the phenomenon of hypoperfusion and hypometabolism of the contralateral cerebellar hemisphere caused by dysfunction of the related supratentorial region. Our aim was to analyze its influence on morphologic and functional outcome in acute ischemic stroke. Subjects with stroke caused by a large vessel occlusion of the anterior circulation were selected from an initial cohort of 1644 consecutive patients who underwent multiparametric CT including whole-brain CT perfusion. Two experienced readers evaluated the posterior fossa in terms of CCD absence (CCD-) or presence (CCDþ). A total of 156 patients formed the study cohort with 102 patients (65.4%) categorized as CCD- and 54 (34.6%) as CCDþ. In linear and logistic regression analyses, no significant association between CCD and final infarction volume (β=-0.440, p=0.972), discharge mRS≤2 (OR=1.897, p=0.320), or 90-day mRS≤2 (OR=0.531, p=0.492) was detected. CCDþ patients had larger supratentorial cerebral blood flow deficits (median: 164 ml vs. 115 ml; p=0.001) compared to CCD-patients. Regarding complications, CCD was associated with a higher rate of parenchymal hematomas (OR=4.793, p=0.035). In conclusion, CCD is frequently encountered in acute ischemic stroke caused by large vessel occlusion of the anterior circulation. CCD was associated with the occurrence of parenchymal hematoma in the ipsilateral cerebral infarction but did not prove to significantly influence patient outcome. [ABSTRACT FROM AUTHOR]

Background: Lesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standardised segmentation are critical but currently unavailable. Methods: A modified Delphi process initiated by the European Imaging Biomarker Alliance (EIBALL) of the European Society of Radiology (ESR) and the European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group was undertaken. Three multidisciplinary task forces addressed modality and image acquisition, segmentation methodology itself, and standards and logistics. Devised survey questions were fed via a facilitator to expert participants. The 58 respondents to Round 1 were invited to participate in Rounds 2–4. Subsequent rounds were informed by responses of previous rounds. Results/conclusions: Items with ≥ 75% consensus are considered a recommendation. These include system performance certification, thresholds for image signal-to-noise, contrast-to-noise and tumour-to-background ratios, spatial resolution, and artefact levels. Direct, iterative, and machine or deep learning reconstruction methods, use of a mixture of CE marked and verified research tools were agreed and use of specified reference standards and validation processes considered essential. Operator training and refreshment were considered mandatory for clinical trials and clinical research. Items with a 60–74% agreement require reporting (site-specific accreditation for clinical research, minimal pixel number within lesion segmented, use of post-reconstruction algorithms, operator training refreshment for clinical practice). Items with ≤ 60% agreement are outside current recommendations for segmentation (frequency of system performance tests, use of only CE-marked tools, board certification of operators, frequency of operator refresher training). Recommendations by anatomical area are also specified. [ABSTRACT FROM AUTHOR]

A 54-year-old patient presented with progressive pain for one month in the second finger of the right hand with an emphasis on the proximal interphalangeal (PIP) joint. Subsequent magnetic resonance imaging (MRI) showed a diffuse intraosseous lesion at the base of the middle phalanx with destruction of the cortical bone and extraosseous soft tissue. An expansively growing chondromatous bone tumor, e.g., a chondrosarcoma, was suspected. After incisional biopsy, the pathologic findings finally revealed, surprisingly, a metastasis of a poorly differentiated non-small cell adenocarcinoma of the lung. This case illustrates a rare but important differential diagnosis for painful finger lesions. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) algorithms evaluating [supine] chest radiographs ([S]CXRs) have remarkably increased in number recently. Since training and validation are often performed on subsets of the same overall dataset, external validation is mandatory to reproduce results and reveal potential training errors. We applied a multicohort benchmarking to the publicly accessible (S)CXR analyzing AI algorithm CheXNet, comprising three clinically relevant study cohorts which differ in patient positioning ([S]CXRs), the applied reference standards (CT-/[S]CXR-based) and the possibility to also compare algorithm classification with different medical experts' reading performance. The study cohorts include [1] a cohort, characterized by 563 CXRs acquired in the emergency unit that were evaluated by 9 readers (radiologists and non-radiologists) in terms of 4 common pathologies, [2] a collection of 6,248 SCXRs annotated by radiologists in terms of pneumothorax presence, its size and presence of inserted thoracic tube material which allowed for subgroup and confounding bias analysis and [3] a cohort consisting of 166 patients with SCXRs that were evaluated by radiologists for underlying causes of basal lung opacities, all of those cases having been correlated to a timely acquired computed tomography scan (SCXR and CT within < 90 min). CheXNet non-significantly exceeded the radiology resident (RR) consensus in the detection of suspicious lung nodules (cohort [1], AUC AI/RR: 0.851/0.839, p = 0.793) and the radiological readers in the detection of basal pneumonia (cohort [3], AUC AI/reader consensus: 0.825/0.782, p = 0.390) and basal pleural effusion (cohort [3], AUC AI/reader consensus: 0.762/0.710, p = 0.336) in SCXR, partly with AUC values higher than originally published ("Nodule": 0.780, "Infiltration": 0.735, "Effusion": 0.864). The classifier "Infiltration" turned out to be very dependent on patient positioning (best in CXR, worst in SCXR). The pneumothorax SCXR cohort [2] revealed poor algorithm performance in CXRs without inserted thoracic material and in the detection of small pneumothoraces, which can be explained by a known systematic confounding error in the algorithm training process. The benefit of clinically relevant external validation is demonstrated by the differences in algorithm performance as compared to the original publication. Our multi-cohort benchmarking finally enables the consideration of confounders, different reference standards and patient positioning as well as the AI performance comparison with differentially qualified medical readers. [ABSTRACT FROM AUTHOR]

(1) Background: CT perfusion (CTP) is used to quantify cerebral hypoperfusion in acute ischemic stroke. Conventional attenuation curve analysis is not standardized and might require input from expert users, hampering clinical application. This study aims to bypass conventional tracer-kinetic analysis with an end-to-end deep learning model to directly categorize patients by stroke core volume from raw, slice-reduced CTP data. (2) Methods: In this retrospective analysis, we included patients with acute ischemic stroke due to proximal occlusion of the anterior circulation who underwent CTP imaging. A novel convolutional neural network was implemented to extract spatial and temporal features from time-resolved imaging data. In a classification task, the network categorized patients into small or large core. In ten-fold cross-validation, the network was repeatedly trained, evaluated, and tested, using the area under the receiver operating characteristic curve (ROC-AUC). A final model was created in an ensemble approach and independently validated on an external dataset. (3) Results: 217 patients were included in the training cohort and 23 patients in the independent test cohort. Median core volume was 32.4 mL and was used as threshold value for the binary classification task. Model performance yielded a mean (SD) ROC-AUC of 0.72 (0.10) for the test folds. External independent validation resulted in an ensembled mean ROC-AUC of 0.61. (4) Conclusions: In this proof-of-concept study, the proposed end-to-end deep learning approach bypasses conventional perfusion analysis and allows to predict dichotomized infarction core volume solely from slice-reduced CTP images without underlying tracer kinetic assumptions. Further studies can easily extend to additional clinically relevant endpoints. [ABSTRACT FROM AUTHOR]

Intrahepatic cholangiocarcinoma is a highly aggressive malignancy with an increasing incidence in recent years. Prognosis is poor and most patients are not eligible for resection at the time of initial diagnosis due to the anatomic location, inadequate hepatic reserve, limiting comorbidities or metastatic disease. Several locoregional therapies from the field of interventional radiology exist for patients who are not amenable for surgery, or in case of local recurrence as a single treatment modality or combined with systemic treatment. To date, evidence is limited, with most conclusions drawn from single-center studies with small patient cohorts, often treated in the salvage situation or for local recurrence after initial resection. Nevertheless, the results are promising and suggest a survival benefit in selected patients. This narrative review focuses on the use of different locoregional treatment options for intrahepatic cholangiocarcinoma. [ABSTRACT FROM AUTHOR]

Background: Characteristics of COVID-19 patients have mainly been reported within confirmed COVID-19 cohorts. By analyzing patients with respiratory infections in the emergency department during the first pandemic wave, we aim to assess differences in the characteristics of COVID-19 vs. Non-COVID-19 patients. This is particularly important regarding the second COVID-19 wave and the approaching influenza season.Methods: We prospectively included 219 patients with suspected COVID-19 who received radiological imaging and RT-PCR for SARS-CoV-2. Demographic, clinical and laboratory parameters as well as RT-PCR results were used for subgroup analysis. Imaging data were reassessed using the following scoring system: 0 - not typical, 1 - possible, 2 - highly suspicious for COVID-19.Results: COVID-19 was diagnosed in 72 (32,9%) patients. In three of them (4,2%) the initial RT-PCR was negative while initial CT scan revealed pneumonic findings. 111 (50,7%) patients, 61 of them (55,0%) COVID-19 positive, had evidence of pneumonia. Patients with COVID-19 pneumonia showed higher body temperature (37,7 ± 0,1 vs. 37,1 ± 0,1 °C; p = 0.0001) and LDH values (386,3 ± 27,1 vs. 310,4 ± 17,5 U/l; p = 0.012) as well as lower leukocytes (7,6 ± 0,5 vs. 10,1 ± 0,6G/l; p = 0.0003) than patients with other pneumonia. Among abnormal CT findings in COVID-19 patients, 57 (93,4%) were evaluated as highly suspicious or possible for COVID-19. In patients with negative RT-PCR and pneumonia, another third was evaluated as highly suspicious or possible for COVID-19 (14 out of 50; 28,0%). The sensitivity in the detection of patients requiring isolation was higher with initial chest CT than with initial RT-PCR (90,4% vs. 79,5%).Conclusions: COVID-19 patients show typical clinical, laboratory and imaging parameters which enable a sensitive detection of patients who demand isolation measures due to COVID-19. [ABSTRACT FROM AUTHOR]

Testicular cancer is a rare disease; however, cure rates are high for all tumor stages. Mostly, the disease is diagnosed in an early (local) stage. We report the case of a 47-year-old male patient with a giant nonseminomatous germ cell tumor. At the time of diagnosis, the patient demonstrated a necrotizing and ulcerating growing mass in the left scrotum with an approximate size of 22 × 18 cm. According to the prognostic classification of the International Germ Cell Cancer Collaborative Group (IGCCCG 1997), the patient exhibited a high-risk profile due to alpha-fetoprotein >10,000 ng/mL and lactate dehydrogenase >10× the upper limit of normal in serum. Primary orchiectomy was infeasible due to the tumor's size, the patient's poor general condition and initial intensive care unit treatment. Primary systemic chemotherapy was applied. After 3 cycles of cisplatin, etoposide and bleomycin, along with 1 cycle of cisplatin, etoposide and ifosfamide, tumor resection with histomorphological examination showed a complete pathological response. Despite the delayed initiation of the therapy, primary chemotherapy was completed timely and showed promising results. Reasons for the late hospitalization were personal responsibilities regarding his family. Better awareness and knowledge of testicular cancer among young men might prevent the here reported delay of medical consultation and avoid testicular tumors of such enormous size. Psychosocial assessment and distress management is important as an integral part of comprehensive care of testicular cancer patients. [ABSTRACT FROM AUTHOR]

Objectives: Stroke triage using CT perfusion (CTP) or MRI gained importance after successful application in recent trials on late-window thrombectomy but is often unavailable and time-consuming. We tested the clinical value of software-based analysis of cerebral attenuation on Single-phase CT angiography source images (CTASI) as CTP surrogate in stroke patients. Methods: Software-based automated segmentation and Hounsfield unit (HU) measurements for all regions of the Alberta Stroke Program Early CT Score (ASPECTS) on CTASI were performed in patients with large vessel occlusion stroke who underwent thrombectomy. To normalize values, we calculated relative HU (rHU) as ratio of affected to unaffected hemisphere. Ischemic regions, regional ischemic core and final infarction were determined on simultaneously acquired CTP and follow-up imaging as ground truth. Receiver operating characteristics analysis was performed to calculate the area-under-the-curve (AUC). Resulting cut-off values were used for comparison with visual analysis and to calculate an 11-point automated CTASI ASPECTS. Results: Seventy-nine patients were included. rHU values enabled significant classification of ischemic involvement on CTP in all ten regions of the ASPECTS (each p<0.001, except M4-cortex p = 0.002). Classification of ischemic core and prediction of final infarction had best results in subcortical regions but produced lower AUC values with significant classification for all regions except M1, M3 and M5. Relative total hemispheric attenuation provided strong linear correlation with CTP total ischemic volume. Automated classification of regional ischemia on CTASI was significantly more accurate in most regions and provided better agreement with CTP cerebral blood flow ASPECTS than visual assessment. Conclusions: Automated attenuation measurements on CTASI provide excellent performance in detecting acute ischemia as identified on CTP with improved accuracy compared to visual analysis. However, value for the approximation of ischemic core and morphologic outcome in large vessel occlusion stroke after thrombectomy was regionally dependent and limited. This technique has the potential to facilitate stroke imaging as sensitive surrogate for CTP-based ischemia. [ABSTRACT FROM AUTHOR]

Background: Red blood cells (RBC) scintigraphy can be used not only for detection of bleeding sites, but also of spleen tissue. However, there is no established quantitative readout. Therefore, we investigated uptake in suspected splenic lesions in direct quantitative correlation to sites of physiologic uptake in order to objectify the readout. Methods: 20 patients with Tc-99m-labelled RBC scintigraphy and SPECT/low-dose CT for assessment of suspected splenic tissue were included. Lesions were rated as vital splenic or non-splenic tissue, and uptake and physiologic uptake of bone marrow, pancreas, and spleen were then quantified using a volume-of-interest based approach. Hepatic uptake served as a reference. Results: The median uptake ratio was significantly higher in splenic (2.82 (range, 0.58–24.10), n = 47) compared to other lesions (0.49 (0.01–0.83), n = 7), p < 0.001, and 5 lesions were newly discovered. The median pancreatic uptake was 0.09 (range 0.03–0.67), bone marrow 0.17 (0.03–0.45), and orthotopic spleen 14.45 (3.04–29.82). Compared to orthotopic spleens, the pancreas showed lowest uptake (0.09 vs. 14.45, p = 0.004). Based on pancreatic uptake we defined a cutoff (0.75) to distinguish splenic from other tissues. Conclusion: As the uptake in extra-splenic regions is invariably low compared to splenules, it can be used as comparator for evaluating suspected splenic tissues. [ABSTRACT FROM AUTHOR]

(1) Background: Respiratory insufficiency with acute respiratory distress syndrome (ARDS) and multi-organ dysfunction leads to high mortality in COVID-19 patients. In times of limited intensive care unit (ICU) resources, chest CTs became an important tool for the assessment of lung involvement and for patient triage despite uncertainties about the predictive diagnostic value. This study evaluated chest CT-based imaging parameters for their potential to predict in-hospital mortality compared to clinical scores. (2) Methods: 89 COVID-19 ICU ARDS patients requiring mechanical ventilation or continuous positive airway pressure mask ventilation were included in this single center retrospective study. AI-based lung injury assessment and measurements indicating pulmonary hypertension (PA-to-AA ratio) on admission CT, oxygenation indices, lung compliance and sequential organ failure assessment (SOFA) scores on ICU admission were assessed for their diagnostic performance to predict in-hospital mortality. (3) Results: CT severity scores and PA-to-AA ratios were not significantly associated with in-hospital mortality, whereas the SOFA score showed a significant association (p < 0.001). In ROC analysis, the SOFA score resulted in an area under the curve (AUC) for in-hospital mortality of 0.74 (95%-CI 0.63–0.85), whereas CT severity scores (0.53, 95%-CI 0.40–0.67) and PA-to-AA ratios (0.46, 95%-CI 0.34–0.58) did not yield sufficient AUCs. These results were consistent for the subgroup of more critically ill patients with moderate and severe ARDS on admission (oxygenation index <200, n = 53) with an AUC for SOFA score of 0.77 (95%-CI 0.64–0.89), compared to 0.55 (95%-CI 0.39–0.72) for CT severity scores and 0.51 (95%-CI 0.35–0.67) for PA-to-AA ratios. (4) Conclusions: Severe COVID-19 disease is not limited to lung (vessel) injury but leads to a multi-organ involvement. The findings of this study suggest that risk stratification should not solely be based on chest CT parameters but needs to include multi-organ failure assessment for COVID-19 ICU ARDS patients for optimized future patient management and resource allocation. [ABSTRACT FROM AUTHOR]

Simple Summary: Finding prognostic biomarkers and associated models with high accuracy in patients with pancreatic cancer remains a challenge. The aim of this study was to analyze whether the combination of quantitative imaging biomarkers based on geometric and radiomics analysis of whole liver tumor burden and established clinical parameters improves the prediction of survival in patients with metastatic pancreatic cancer. In this retrospective study a total of 75 patients with pancreatic cancer and liver metastases were analyzed. Segmentations of whole liver tumor burden from baseline contrast-enhanced CT images were used to derive different quantitative imaging biomarkers. For comparison, we chose two clinical prognostic models from the literature. We found that a combined clinical and imaging-based model has a significantly higher predictive performance to discriminate survival than the underlying clinical models alone (p < 0.003). Finding prognostic biomarkers with high accuracy in patients with pancreatic cancer (PC) remains a challenging problem. To improve the prediction of survival and to investigate the relevance of quantitative imaging biomarkers (QIB) we combined QIB with established clinical parameters. In this retrospective study a total of 75 patients with metastatic PC and liver metastases were analyzed. Segmentations of whole liver tumor burden (WLTB) from baseline contrast-enhanced CT images were used to derive QIBs. The benefits of QIBs in multivariable Cox models were analyzed in comparison with two clinical prognostic models from the literature. To discriminate survival, the two clinical models had concordance indices of 0.61 and 0.62 in a statistical setting. Combined clinical and imaging-based models achieved concordance indices of 0.74 and 0.70 with WLTB volume, tumor burden score (TBS), and bilobar disease being the three WLTB parameters that were kept by backward elimination. These combined clinical and imaging-based models have significantly higher predictive performance in discriminating survival than the underlying clinical models alone (p < 0.003). Radiomics and geometric WLTB analysis of patients with metastatic PC with liver metastases enhances the modeling of survival compared with models based on clinical parameters alone. [ABSTRACT FROM AUTHOR]

Background: Neurologic symptom severity and deterioration at 24 hours (h) predict long-term outcomes in patients with acute large vessel occlusion (LVO) stroke of the anterior circulation. We aimed to examine the association of baseline multiparametric CT imaging and clinical factors with the course of neurologic symptom severity in the first 24 h after endovascular treatment (EVT). Methods: Patients with LVO stroke of the anterior circulation were selected from a prospectively acquired consecutive cohort of patients who underwent multiparametric CT, including non-contrast CT, CT angiography and CT perfusion before EVT. The symptom severity was assessed on admission and after 24 h using the 42-point National Institutes of Health Stroke Scale (NIHSS). Clinical and imaging data were compared between patients with and without early neurological deterioration (END). END was defined as an increase in ≥4 points, and a significant clinical improvement as a decrease in ≥4 points, compared to NIHSS on admission. Multivariate regression analyses were used to determine independent associations of imaging and clinical parameters with NIHSS score increase or decrease in the first 24 h. Results: A total of 211 patients were included, of whom 38 (18.0%) had an END. END was significantly associated with occlusion of the internal carotid artery (odds ratio (OR), 4.25; 95% CI, 1.90–9.47) and the carotid T (OR, 6.34; 95% CI, 2.56–15.71), clot burden score (OR, 0.79; 95% CI, 0.68–0.92) and total ischemic volume (OR, 1.01; 95% CI, 1.00–1.01). In a comprehensive multivariate analysis model including periprocedural parameters and complications after EVT, carotid T occlusion remained independently associated with END, next to reperfusion status and intracranial hemorrhage. Favorable reperfusion status and small ischemic core volume were associated with clinical improvement after 24 h. Conclusions: The use of imaging parameters as a surrogate for early NIHSS progression in an acute LVO stroke after EVT reached limited performance with only carotid T occlusion as an independent predictor of END. Reperfusion status and early complications in terms of intracranial hemorrhage are critical factors that influence patient outcome in the acute stroke phase after EVT. [ABSTRACT FROM AUTHOR]

(1) Background: Extracorporeal membrane oxygenation (ECMO) therapy in intensive care units (ICUs) remains the last treatment option for Coronavirus disease 2019 (COVID-19) patients with severely affected lungs but is highly resource demanding. Early risk stratification for the need of ECMO therapy upon admission to the hospital using artificial intelligence (AI)-based computed tomography (CT) assessment and clinical scores is beneficial for patient assessment and resource management; (2) Methods: Retrospective single-center study with 95 confirmed COVID-19 patients admitted to the participating ICUs. Patients requiring ECMO therapy (n = 14) during ICU stay versus patients without ECMO treatment (n = 81) were evaluated for discriminative clinical prediction parameters and AI-based CT imaging features and their diagnostic potential to predict ECMO therapy. Reported patient data include clinical scores, AI-based CT findings and patient outcomes; (3) Results: Patients subsequently allocated to ECMO therapy had significantly higher sequential organ failure (SOFA) scores (p < 0.001) and significantly lower oxygenation indices on admission (p = 0.009) than patients with standard ICU therapy. The median time from hospital admission to ECMO placement was 1.4 days (IQR 0.2–4.0). The percentage of lung involvement on AI-based CT assessment on admission to the hospital was significantly higher in ECMO patients (p < 0.001). In binary logistic regression analyses for ECMO prediction including age, sex, body mass index (BMI), SOFA score on admission, lactate on admission and percentage of lung involvement on admission CTs, only SOFA score (OR 1.32, 95% CI 1.08–1.62) and lung involvement (OR 1.06, 95% CI 1.01–1.11) were significantly associated with subsequent ECMO allocation. Receiver operating characteristic (ROC) curves showed an area under the curve (AUC) of 0.83 (95% CI 0.73–0.94) for lung involvement on admission CT and 0.82 (95% CI 0.72–0.91) for SOFA scores on ICU admission. A combined parameter of SOFA on ICU admission and lung involvement on admission CT yielded an AUC of 0.91 (0.84–0.97) with a sensitivity of 0.93 and a specificity of 0.84 for ECMO prediction; (4) Conclusions: AI-based assessment of lung involvement on CT scans on admission to the hospital and SOFA scoring, especially if combined, can be used as risk stratification tools for subsequent requirement for ECMO therapy in patients with severe COVID-19 disease to improve resource management in ICU settings. [ABSTRACT FROM AUTHOR]

The sarcoid-like reaction represents an autoinflammatory cause of mediastinal and hilar lymphadenopathy but may also involve other lymph node regions and organs. This rare phenomenon has mainly been reported in patients with Hodgkin's lymphoma (HL) or solid tumors (particularly melanoma) undergoing immunotherapy and chemotherapy. Cases in non-Hodgkin's lymphoma (NHL) are very uncommon. We present an uncommon case of a patient with primarily mediastinal diffuse large B-cell lymphoma (DLBCL) who showed a CT-based partial response in interim staging, whereas at end-of-treatment multiple newly enlarged and hypermetabolic mediastinal and bilateral hilar lymph nodes were detected by 18F-FDG PET/CT imaging. A subsequent histological workup determined a sarcoid-like reaction without any lymphomatous tissue. Therefore, sarcoid-like reactions should be considered as a potential pitfall in Deauville staging with 18F-FDG PET/CT imaging for patients with NHL. [ABSTRACT FROM AUTHOR]

Simple Summary: Colorectal cancer is among the most prevalent cancers worldwide, with every second patient developing liver metastasis during their illness. For treatment of oligometastatic patients, there are several alternatives such as surgery, microwave ablation (MWA) and radiofrequency ablation (RFA). Our aim was to evaluate the cost-effectiveness for each strategy, accounting for short- and long-term costs and efficacy. The analysis demonstrated that MWA and surgery offer a comparable efficacy. MWA was the most cost-effective strategy in intermediate resource settings, and can be considered a cost-effective alternative to surgery in high resource settings. Background: Colorectal cancer is among the most prevalent cancer entities worldwide, with every second patient developing liver metastases during their illness. For local treatment of liver metastases, a surgical approach as well as ablative treatment options, such as microwave ablation (MWA) and radiofrequency ablation (RFA), are available. The aim of this study is to evaluate the cost-effectiveness of RFA, MWA and surgery in the treatment of liver metastases of oligometastatic colorectal cancer (omCRC) that are amenable for all investigated treatment modalities. Methods: A decision analysis based on a Markov model assessed lifetime costs and quality-adjusted life years (QALY) related to the treatment strategies RFA, MWA and surgical resection. Input parameters were based on the best available and most recent evidence. Probabilistic sensitivity analyses (PSA) were performed with Monte Carlo simulations to evaluate model robustness. The percentage of cost-effective iterations was determined for different willingness-to-pay (WTP) thresholds. Results: The base-case analysis showed that surgery led to higher long-term costs compared to RFA and MWA (USD 41,848 vs. USD 36,937 vs. USD 35,234), while providing better long-term outcomes than RFA, yet slightly lower than MWA (6.80 vs. 6.30 vs. 6.95 QALYs for surgery, RFA and MWA, respectively). In PSA, MWA was the most cost-effective strategy for all WTP thresholds below USD 80,000 per QALY. Conclusions: In omCRC patients with liver metastases, MWA and surgery are estimated to provide comparable efficacy. MWA was identified as the most cost-effective strategy in intermediate resource settings and should be considered as an alternative to surgery in high resource settings. [ABSTRACT FROM AUTHOR]

We present a 71-year-old female patient who underwent 18F-PSMA-1007 PET/CT for suspected metastatic renal cell carcinoma (RCC), as RCC also shows high PSMA-expression in tumor neovascularization. 18F-PSMA-1007 PET/CT showed a high PSMA-avidity in the renal tumor, enlarged intra-abdominal and mediastinal lymph nodes. Moreover, PSMA-positive pleural, pulmonal and osseous lesions were found. However, histopathology revealed an immature plasma cell myeloma with an endothelial PSMA-expression of the neovasculature. This case illustrates the increased PSMA-avidity in multiple myeloma and highlights PSMA as a potential theragnostic target in multiple myeloma. For clinical routine, lymphatic diseases such as extramedullary myeloma should be considered as differential diagnosis in PSMA-avid renal masses on PET/CT. [ABSTRACT FROM AUTHOR]

(1) Background: Time-consuming SARS-CoV-2 RT-PCR suffers from limited sensitivity in early infection stages whereas fast available chest CT can already raise COVID-19 suspicion. Nevertheless, radiologists' performance to differentiate COVID-19, especially from influenza pneumonia, is not sufficiently characterized. (2) Methods: A total of 201 pneumonia CTs were identified and divided into subgroups based on RT-PCR: 78 COVID-19 CTs, 65 influenza CTs and 62 Non-COVID-19-Non-influenza (NCNI) CTs. Three radiology experts (blinded from RT-PCR results) raised pathogen-specific suspicion (separately for COVID-19, influenza, bacterial pneumonia and fungal pneumonia) according to the following reading scores: 0—not typical/1—possible/2—highly suspected. Diagnostic performances were calculated with RT-PCR as a reference standard. Dependencies of radiologists' pathogen suspicion scores were characterized by Pearson's Chi2 Test for Independence. (3) Results: Depending on whether the intermediate reading score 1 was considered as positive or negative, radiologists correctly classified 83–85% (vs. NCNI)/79–82% (vs. influenza) of COVID-19 cases (sensitivity up to 94%). Contrarily, radiologists correctly classified only 52–56% (vs. NCNI)/50–60% (vs. COVID-19) of influenza cases. The COVID-19 scoring was more specific than the influenza scoring compared with suspected bacterial or fungal infection. (4) Conclusions: High-accuracy COVID-19 detection by CT might expedite patient management even during the upcoming influenza season. [ABSTRACT FROM AUTHOR]

(1) Background: To assess the value of chest CT imaging features of COVID-19 disease upon hospital admission for risk stratification of invasive ventilation (IV) versus no or non-invasive ventilation (non-IV) during hospital stay. (2) Methods: A retrospective single-center study was conducted including all patients admitted during the first three months of the pandemic at our hospital with PCR-confirmed COVID-19 disease and admission chest CT scans (n = 69). Using clinical information and CT imaging features, a 10-point ordinal risk score was developed and its diagnostic potential to differentiate a severe (IV-group) from a more moderate course (non-IV-group) of the disease was tested. (3) Results: Frequent imaging findings of COVID-19 pneumonia in both groups were ground glass opacities (91.3%), consolidations (53.6%) and crazy paving patterns (31.9%). Characteristics of later stages such as subpleural bands were observed significantly more often in the IV-group (52.2% versus 26.1%, p = 0.032). Using information directly accessible during a radiologist's reporting, a simple risk score proved to reliably differentiate between IV- and non-IV-groups (AUC: 0.89 (95% CI 0.81–0.96), p < 0.001). (4) Conclusions: Information accessible from admission CT scans can effectively and reliably be used in a scoring model to support risk stratification of COVID-19 patients to improve resource and allocation management of hospitals. [ABSTRACT FROM AUTHOR]

A 16-year-old male patient underwent 18F-FDG PET/CT staging after multiple surgical resections and radiotherapy of an uncommon metastatic pediatric sebaceous carcinoma of the parotid gland. Initial PET/CT imaging exhibited a recurrent paravertebral metastasis (C4) as well as a metabolically active tumor tissue at the primary site. Follow-up PET/CT after radiotherapy of the cervical spine (C4) and four cycles of chemotherapy with cisplatin and palbociclib revealed complete functional remission in the cervical spine and partial remission at the primary site. This case illustrates the 18F-FDG-uptake behavior and the disease course of a very rare malignant epithelial tumor of the salivary glands. [ABSTRACT FROM AUTHOR]