Rare case of a chronic rhinocerebral mucormycosis.

We describe a case of rhino-orbital-cerebral mucormycosis (ROCM) in a diabetic patient. She presented with cavernous sinus syndrome and ischemia of the optic nerve. Initially unremarkable findings in the nasal cavity and paranasal sinus delayed early diagnosis. Within two weeks, a follow-up MRI showing progressive orbital inflammation, thrombosis of the cavernous sinus and erosive destruction of the left middle nasal concha together with necrotic black tissue in the left nasal cavity and destruction of the maxillary sinus demonstrated in a consecutively performed ethmoidectomy, finally gave way to diagnosis. Definite diagnosis was established by histopathology and culture. Treatment consisted of a combination of liposomal Amphotericin B, partial surgical resection and improved diabetes control. Despite insufficient surgical treatment, the progression of the disease was remarkably slow - a typical hallmark of chronic ROCM. With this case report we aim to underline the difficulties in establishing a prompt diagnosis of ROCM and to remind readers of its chronic form. 2012 Elsevier Ltd. All rights reserved.

The Monocle Sign on 18 F-FDG PET Indicates Contralateral Peripheral Facial Nerve Palsy.

BACKGROUND: The aim of our study was to retrospectively analyze FDG PET/CT data in patients with facial nerve palsy (FNP) for the presence of the monocle sign. PATIENTS AND METHODS: A total of 85 patients with unilateral FNP were included into our study, thereof 73 with peripheral FNP and 12 with central FNP. FDG uptake (SUV max , SUV mean , total lesion glycolysis) was measured in both orbicularis oculi muscles (OOMs). FDG uptake of paretic and nonparetic muscles was compared in patients with FNP (Wilcoxon test and Mann-Whitney U test) and was also compared with FDG uptake in 33 patients without FNP (Mann-Whitney U test). SUV max ratios of OOM were compared. A receiver operating characteristic curve and Youden Index were used to determine the optimal cutoff SUV max ratio for the prevalence of contralateral peripheral FNP. RESULTS: The SUV max ratio of OOM was significantly higher in patients with peripheral FNP compared with patients with central FNP and those without FNP (1.70 ± 0.94 vs 1.16 ± 0.09 vs 1.18 ± 0.21, respectively; P < 0.001). The SUV max ratio of OOM yielded an area under the curve (AUC) of 0.719 (95% confidence interval, 0.630-0.809), with an optimal cutoff of 1.41, yielding a specificity of 94.4% and a sensitivity of 44.1% for identifying contralateral peripheral FNP. One hundred percent specificity is achieved using a cutoff of 1.91 (sensitivity, 29.4%). CONCLUSIONS: Asymmetrically increased FDG uptake of the OOM (the "monocle sign") indicates contralateral peripheral FNP. A nearly 2-fold higher SUV max represents a practically useful cutoff.

Evaluating the biodistribution for [68Ga]Ga-PSMA-11 and [18F]F-PSMA-1007 PET/CT with an inter- and intrapatient based analysis.

BACKGROUND: Liver uptake in [68Ga]Ga-PSMA-11 PET is used as an internal reference in addition to clinical parameters to select patients for [177Lu]Lu-PSMA-617 radioligand therapy (RLT). Due to increased demand, [68Ga]Ga-PSMA-11 was replaced by [18F]F-PSMA-1007, a more lipophilic tracer with different biodistribution and splenic uptake was suggested as a new internal reference. We compared the intra-patient tracer distribution between [68Ga]Ga-PSMA-11 and [18F]F-PSMA-1007. METHODS: Fifty patients who underwent PET examinations in two centers with both [18F]F-PSMA-1007 and [68Ga]Ga-PSMA-11 within one year were included. Mean standardized uptake values (SUVmean) were obtained for liver, spleen, salivary glands, blood pool, and bone. Primary tumor, local recurrence, lymph node, bone or visceral metastasis were also assessed for intra- and inter-individual comparison. RESULTS: Liver SUVmean was significantly higher with [18F]F-PSMA-1007 (11.7 ± 3.9) compared to [68Ga]Ga-PSMA-11 (5.4 ± 1.7, p < .05) as well as splenic SUVmean (11.2 ± 3.5 vs.8.1 ± 3.5, p < .05). The blood pool was comparable between the two scans. Malignant lesions did not show higher SUVmean on [18F]F-PSMA-1007. Intra-individual comparison of liver uptake between the two scans showed a linear association for liver uptake with SUVmean [68Ga]Ga-PSMA-11 = 0.33 x SUVmean [18F]F-PSMA-1007 + 1.52 (r = .78, p < .001). CONCLUSION: Comparing biodistribution of [68Ga]Ga and [18F]F tracers, liver uptake on [68Ga]Ga-PSMA-11 PET is the most robust internal reference value. Liver uptake of [18F]F-PSMA-1007 was significantly higher, but so was the splenic uptake. The strong intra-individual association of hepatic accumulation between the two scans may allow using of a conversion factor for [18F]F-PSMA-1007 as a basis for RLT selection.

Fully automated computational measurement of noise in positron emission tomography.

OBJECTIVES: To introduce an automated computational algorithm that estimates the global noise level across the whole imaging volume of PET datasets. METHODS: [18F]FDG PET images of 38 patients were reconstructed with simulated decreasing acquisition times (15-120 s) resulting in increasing noise levels, and with block sequential regularized expectation maximization with beta values of 450 and 600 (Q.Clear 450 and 600). One reader performed manual volume-of-interest (VOI) based noise measurements in liver and lung parenchyma and two readers graded subjective image quality as sufficient or insufficient. An automated computational noise measurement algorithm was developed and deployed on the whole imaging volume of each reconstruction, delivering a single value representing the global image noise (Global Noise Index, GNI). Manual noise measurement values and subjective image quality gradings were compared with the GNI. RESULTS: Irrespective of the absolute noise values, there was no significant difference between the GNI and manual liver measurements in terms of the distribution of noise values (p = 0.84 for Q.Clear 450, and p = 0.51 for Q.Clear 600). The GNI showed a fair to moderately strong correlation with manual noise measurements in liver parenchyma (r = 0.6 in Q.Clear 450, r = 0.54 in Q.Clear 600, all p < 0.001), and a fair correlation with manual noise measurements in lung parenchyma (r = 0.52 in Q.Clear 450, r = 0.33 in Q.Clear 600, all p < 0.001). Classification performance of the GNI for subjective image quality was AUC 0.898 for Q.Clear 450 and 0.919 for Q.Clear 600. CONCLUSION: An algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. CLINICAL RELEVANCE STATEMENT: An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking of clinical PET imaging within and across institutions. KEY POINTS: • Noise is an important quantitative marker that strongly impacts image quality of PET images. • An automated computational noise measurement algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. • An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking as well as protocol harmonization.

Sinonasal mucosal melanoma treatment response assessment to immune checkpoint inhibitors using hybrid positron emission tomography imaging.

The purpose of this retrospective study was to investigate response of sinonasal mucosal melanoma (SMM) patients to treatment with immune checkpoint inhibitors (ICI), using hybrid PET imaging. Fifteen SMM patients underwent hybrid PET imaging before and three months after initiation of ICI. The disease-specific survival (DSS) was calculated. Quantitative PET parameters of the primary tumor and their association with DSS and therapy response were investigated. Nine of the fifteen (60%) patients responded to ICI therapy. Patients with therapy response depicted on hybrid PET imaging had better DSS than those without (p = 0.0058). Quantitative PET parameters of the initial PET harbored no association with DSS or therapy response. However, these findings lack of sufficient statistical power and must be interpreted with caution. The first restaging PET-imaging after ICI initiation can help stratify patients with regard to DSS.

Can We Predict Skeletal Lesion on Bone Scan Based on Quantitative PSMA PET/CT Features?

OBJECTIVE: The increasing use of PSMA-PET/CT for restaging prostate cancer (PCa) leads to a patient shift from a non-metastatic situation based on conventional imaging (CI) to a metastatic situation. Since established therapeutic pathways have been designed according to CI, it is unclear how this should be translated to the PSMA-PET/CT results. This study aimed to investigate whether PSMA-PET/CT and clinical parameters could predict the visibility of PSMA-positive lesions on a bone scan (BS). METHODS: In four different centers, all PCa patients with BS and PSMA-PET/CT within 6 months without any change in therapy or significant disease progression were retrospectively selected. Up to 10 non-confluent clear bone metastases were selected per PSMA-PET/CT and SUVmax, SUVmean, PSMAtot, PSMAvol, density, diameter on CT, and presence of cortical erosion were collected. Clinical variables (age, PSA, Gleason Score) were also considered. Two experienced double-board physicians decided whether a bone metastasis was visible on the BS, with a consensus readout for discordant findings. For predictive performance, a random forest was fit on all available predictors, and its accuracy was assessed using 10-fold cross-validation performed 10 times. RESULTS: A total of 43 patients were identified with 222 bone lesions on PSMA-PET/CT. A total of 129 (58.1%) lesions were visible on the BS. In the univariate analysis, all PSMA-PET/CT parameters were significantly associated with the visibility on the BS (p < 0.001). The random forest reached a mean accuracy of 77.6% in a 10-fold cross-validation. CONCLUSIONS: These preliminary results indicate that there might be a way to predict the BS results based on PSMA-PET/CT, potentially improving the comparability between both examinations and supporting decisions for therapy selection.

Characterization of hypermetabolic lymph nodes after SARS-CoV-2 vaccination using PET-CT derived node-RADS, in patients with melanoma.

This study aimed to evaluate the diagnostic accuracy of Node Reporting and Data System (Node-RADS) in discriminating between normal, reactive, and metastatic axillary LNs in patients with melanoma who underwent SARS-CoV-2 vaccination. Patients with proven melanoma who underwent a 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[18F]-FDG PET/CT) between February and April 2021 were included in this retrospective study. Primary melanoma site, vaccination status, injection site, and 2-[18F]-FDG PET/CT were used to classify axillary LNs into normal, inflammatory, and metastatic (combined classification). An adapted Node-RADS classification (A-Node-RADS) was generated based on LN anatomical characteristics on low-dose CT images and compared to the combined classification. 108 patients were included in the study (54 vaccinated). HALNs were detected in 42 patients (32.8%), of whom 97.6% were vaccinated. 172 LNs were classified as normal, 30 as inflammatory, and 14 as metastatic using the combined classification. 152, 22, 29, 12, and 1 LNs were classified A-Node-RADS 1, 2, 3, 4, and 5, respectively. Hence, 174, 29, and 13 LNs were deemed benign, equivocal, and metastatic. The concordance between the classifications was very good (Cohen's k: 0.91, CI 0.86-0.95; p-value < 0.0001). A-Node-RADS can assist the classification of axillary LNs in melanoma patients who underwent 2-[18F]-FDG PET/CT and SARS-CoV-2 vaccination.

Whole-Body 18 F-FDG PET/CT Patlak Parametric Imaging of Hepatic Alveolar Echinococcosis.

ABSTRACT: We present dynamic 18 F-FDG PET/CT acquisition in a 52-year-old old woman with histologically proven hepatic alveolar echinococcosis (AE). Metabolic rate of FDG images generated with traditional and relative Patlak analysis show the AE manifestation in the liver significantly better the static SUV images. Dynamic PET may thus have the potential to increase sensitivity in the assessment of hepatic AE manifestations. Such parametric images may offer complementary qualitative information and quantification superior to SUV images.

A third of the radiotracer dose: two decades of progress in pediatric [18F]fluorodeoxyglucose PET/CT and PET/MR imaging.

OBJECTIVES: To assess the evolution of administered radiotracer activity for F-18-fluorodeoxyglucose (18F-FDG) PET/CT or PET/MR in pediatric patients (0-16 years) between years 2000 and 2021. METHODS: Pediatric patients (≤ 16 years) referred for 18F-FDG PET/CT or PET/MR imaging of the body during 2000 and 2021 were retrospectively included. The amount of administered radiotracer activity in megabecquerel (MBq) was recorded, and signal-to-noise ratio (SNR) was measured in the right liver lobe with a 4 cm3 volume of interest as an indicator for objective image quality. Descriptive statistics were computed. RESULTS: Two hundred forty-three children and adolescents underwent a total of 466 examinations. The median injected 18F-FDG activity in MBq decreased significantly from 296 MBq in 2000-2005 to 100 MBq in 2016-2021 (p < 0.001), equaling approximately one-third of the initial amount. The median SNR ratio was stable during all years with 11.7 (interquartile range [IQR] 10.7-12.9, p = 0.133). CONCLUSIONS: Children have benefited from a massive reduction in the administered 18F-FDG dose over the past 20 years without compromising objective image quality. CLINICAL RELEVANCE STATEMENT: Radiotracer dose was reduced considerably over the past two decades of pediatric F-18-fluorodeoxyglucose PET/CT and PET/MR imaging highlighting the success of technical innovations in pediatric PET imaging. KEY POINTS: • The evolution of administered radiotracer activity for F-18-fluorodeoxyglucose (18F-FDG) PET/CT or PET/MR in pediatric patients (0-16 years) between 2000 and 2021 was assessed. • The injected tracer activity decreased by 66% during the study period from 296 megabecquerel (MBq) to 100 MBq (p < 0.001). • The continuous implementation of technical innovations in pediatric hybrid 18F-FDG PET has led to a steady decrease in the amount of applied radiotracer, which is particularly beneficial for children who are more sensitive to radiation.

Evolution of CT radiation dose in pediatric patients undergoing hybrid 2-[18F]FDG PET/CT between 2007 and 2021.

OBJECTIVES: To evaluate the evolution of CT radiation dose in pediatric patients undergoing hybrid 2-[18F]fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET/CT between 2007 and 2021. METHODS AND MATERIALS: Data from all pediatric patients aged 0-18 years who underwent hybrid 2-[18F]FDG PET/CT of the body between January 2007 and May 2021 were reviewed. Demographic and imaging parameters were collected. A board-certified radiologist reviewed all CT scans and measured image noise in the brain, liver, and adductor muscles. RESULTS: 294 scans from 167 children (72 females (43%); median age: 14 (IQR 10-15) years; BMI: median 17.5 (IQR 15-20.4) kg/m2) were included. CT dose index-volume (CTDIvol) and dose length product (DLP) both decreased significantly from 2007 to 2021 (both p < 0.001, Spearman's rho coefficients -0.46 and -0.35, respectively). Specifically, from 2007 to 2009 to 2019-2021 CTDIvol and DLP decreased from 2.94 (2.14-2.99) mGy and 309 (230-371) mGy*cm, respectively, to 0.855 (0.568-1.11) mGy and 108 (65.6-207) mGy*cm, respectively. From 2007 to 2021, image noise in the brain and liver remained constant (p = 0.26 and p = 0.06), while it decreased in the adductor muscles (p = 0.007). Peak tube voltage selection (in kilovolt, kV) of CT scans shifted from high kV imaging (140 or 120kVp) to low kV imaging (100 or 80kVp) (p < 0.001) from 2007 to 2021. CONCLUSION: CT radiation dose in pediatric patients undergoing hybrid 2-[18F]FDG PET/CT has decreased in recent years equaling approximately one-third of the initial amount. ADVANCES IN KNOWLEDGE: Over the past 15 years, CT radiation dose decreased considerably in pediatric patients undergoing hybrid imaging, while objective image quality may not have been compromised.

Automated F18-FDG PET/CT image quality assessment using deep neural networks on a latest 6-ring digital detector system.

To evaluate whether a machine learning classifier can evaluate image quality of maximum intensity projection (MIP) images from F18-FDG-PET scans. A total of 400 MIP images from F18-FDG-PET with simulated decreasing acquisition time (120 s, 90 s, 60 s, 30 s and 15 s per bed-position) using block sequential regularized expectation maximization (BSREM) with a beta-value of 450 and 600 were created. A machine learning classifier was fed with 283 images rated "sufficient image quality" and 117 images rated "insufficient image quality". The classification performance of the machine learning classifier was assessed by calculating sensitivity, specificity, and area under the receiver operating characteristics curve (AUC) using reader-based classification as the target. Classification performance of the machine learning classifier was AUC 0.978 for BSREM beta 450 and 0.967 for BSREM beta 600. The algorithm showed a sensitivity of 89% and 94% and a specificity of 94% and 94% for the reconstruction BSREM 450 and 600, respectively. Automated assessment of image quality from F18-FDG-PET images using a machine learning classifier provides equivalent performance to manual assessment by experienced radiologists.

Internal Thoracic Vein Tumor Thrombus From Sternal Melanoma Metastasis on 18 F-FDG PET/CT.

ABSTRACT: We present 18 F-FDG PET/CT findings of an internal thoracic vein tumor thrombus from melanoma in a 76-year-old woman. Restaging 18 F-FDG PET/CT shows a progressive disease with an internal thoracic vein tumor thrombus from a sternal bone metastasis. Although cutaneous malignant melanoma may metastasize to any body part, a direct tumor invasion of veins and the formation of a tumor thrombus represent an extremely rare complication.

Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging.

BACKGROUND: To assess the accuracy of fully automated deep learning (DL) based coronary artery calcium scoring (CACS) from non-contrast computed tomography (CT) as acquired for attenuation correction (AC) of cardiac single-photon-emission computed tomography myocardial perfusion imaging (SPECT-MPI). METHODS AND RESULTS: Patients were enrolled in this study as part of a larger prospective study (NCT03637231). In this study, 56 Patients who underwent cardiac SPECT-MPI due to suspected coronary artery disease (CAD) were prospectively enrolled. All patients underwent non-contrast CT for AC of SPECT-MPI twice. CACS was manually assessed (serving as standard of reference) on both CT datasets (n = 112) and by a cloud-based DL tool. The agreement in CAC scores and CAC score risk categories was quantified. For the 112 scans included in the analysis, interscore agreement between the CAC scores of the standard of reference and the DL tool was 0.986. The agreement in risk categories was 0.977 with a reclassification rate of 3.6%. Heart rate, image noise, body mass index (BMI), and scan did not significantly impact (p=0.09 - p=0.76) absolute percentage difference in CAC scores. CONCLUSION: A DL tool enables a fully automated and accurate estimation of CAC scores in patients undergoing non-contrast CT for AC of SPECT-MPI.

Left ventricular function and volumes from gated [13N]-ammonia positron emission tomography myocardial perfusion imaging: A prospective head-to-head comparison against CMR using a hybrid PET/MR device.

BACKGROUND: Positron emission tomography (PET) myocardial perfusion imaging (MPI) can be used to evaluate left ventricular (LV) volumes and function. We performed a head-to-head comparison of LV function and volumes obtained simultaneously using [13N]-ammonia-PET and cardiac magnetic resonance (CMR), with the latter serving as the reference standard. METHODS AND RESULTS: In this prospective study, 51 patients underwent [13N]-ammonia-PET MPI and CMR using a hybrid PET/MR device. Left ventricular end-systolic volumes (LVESV), end-diastolic volumes (LVEDV), stroke volumes (LVSV), ejection fractions (LVEF), and segmental wall motion were analyzed for both methods and were compared using correlational and Bland-Altman (BA) analysis; segmental wall motion was compared using ANOVA. The agreement between [13N]-ammonia-PET and CMR for LVEF was good, with minimal bias (- .6%) and narrow BA limits of agreement (- 7.9% to 6.8%), but [13N]-ammonia-PET systematically underestimated LV volumes, with high bias in LVESV (- 11.2 ml), LVEDV (- 28.9 ml), and LVSV (- 17.5 ml). Mean segmental wall motion in [13N]-ammonia-PET differed significantly among the corresponding normokinetic (6.6 ± 2 mm), hypokinetic (5.1 ± 2 mm), and akinetic (3.3 ± 2 mm) segments in CMR (P < .01). CONCLUSION: LVEF and LV wall motion can be accurately assessed using [13N]-ammonia-PET MPI, although LV volumes are significantly underestimated compared to CMR.

Impact of deep learning image reconstructions (DLIR) on coronary artery calcium quantification.

BACKGROUND: Deep learning image reconstructions (DLIR) have been recently introduced as an alternative to filtered back projection (FBP) and iterative reconstruction (IR) algorithms for computed tomography (CT) image reconstruction. The aim of this study was to evaluate the effect of DLIR on image quality and quantification of coronary artery calcium (CAC) in comparison to FBP. METHODS: One hundred patients were consecutively enrolled. Image quality-associated variables (noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR)) as well as CAC-derived parameters (Agatston score, mass, and volume) were calculated from images reconstructed by using FBP and three different strengths of DLIR (low (DLIR_L), medium (DLIR_M), and high (DLIR_H)). Patients were stratified into 4 risk categories according to the Coronary Artery Calcium - Data and Reporting System (CAC-DRS) classification: 0 Agatston score (very low risk), 1-99 Agatston score (mildly increased risk), Agatston 100-299 (moderately increased risk), and ≥ 300 Agatston score (moderately-to-severely increased risk). RESULTS: In comparison to standard FBP, increasing strength of DLIR was associated with a significant and progressive decrease of image noise (p < 0.001) alongside a significant and progressive increase of both SNR and CNR (p < 0.001). The use of incremental levels of DLIR was associated with a significant decrease of Agatston CAC score and CAC volume (p < 0.001), while mass score remained unchanged when compared to FBP (p = 0.232). The underestimation of Agatston CAC led to a CAC-DRS misclassification rate of 8%. CONCLUSION: DLIR systematically underestimates Agatston CAC score. Therefore, DLIR should be used cautiously for cardiovascular risk assessment. KEY POINTS: • In coronary artery calcium imaging, the implementation of deep learning image reconstructions improves image quality, by decreasing the level of image noise. • Deep learning image reconstructions systematically underestimate Agatston coronary artery calcium score. • Deep learning image reconstructions should be used cautiously in clinical routine to measure Agatston coronary artery calcium score for cardiovascular risk assessment.

Prediction of extranodal extension in oropharyngeal cancer patients and carcinoma of unknown primary: value of metabolic tumor imaging with hybrid PET compared with MRI and CT.

OBJECTIVES: The aim of this study was to investigate the value of metabolic tumor imaging using hybrid PET for the preoperative detection of extranodal extension (ENE) in lymph node metastases of oropharyngeal squamous cell carcinoma (OPSCC). METHODS: We performed a retrospective analysis of a consecutive cohort of patients with OPSCC treated with primary surgery with or without adjuvant (chemo-) radiotherapy at the Kantonsspital Sankt-Gallen and the University Hospital Zurich, Switzerland, from 2010 until 2019. Hybrid PET was compared to conventional cross-sectional imaging with MRI and CT. Histopathological presence of ENE of neck dissection specimen served as gold standard. RESULTS: A total number of 234 patients were included in the study, 95 (40.6%) of which had pathological ENE (pENE). CT has a good specificity with 93.7%; meanwhile, MRI was the most sensitive diagnostic method (72.0%). The nodal metabolic tumor parameters (SUVmax, TLG, MTV) were significantly higher in patients with positive ENE (p < 0.001 for all three parameters) than in patients with negative ENE (p < 0.001, for all three parameters). CONCLUSIONS: CT achieved the best specificity, while MRI had the best sensitivity to detect ENE. Nodal metabolic tumor parameters differed significantly between ENE-positive/negative and p16-positive/negative patients. Hence, quantitative data obtained by metabolic imaging might predict presence of ENE and, therefore, could be helpful in customizing therapy management.

Frequency and temporal evolution of COVID-19 vaccination rate among oncological patients undergoing 18F-FDG-PET.

PURPOSE: To evaluate the temporal evolution of vaccination against COVID-19 in a Swiss oncological cohort. METHODS: History of complete vaccination (i.e. at least two vaccine doses) against COVID-19 of patients undergoing oncological 18F-FDG PET/CT between February and September 2021 (n = 2613) was taken. Vaccination rate was compared with age-matched national data from the Swiss Federal Office of Public Health. Subgroup differences in temporal evolution of vaccination rate were analyzed by fitting a generalized linear model and determined by significant interaction between, sex, oncological diagnosis, and month of examination. RESULTS: Rate of complete vaccination against COVID-19 steadily increased and reached 81 % in September 2021. The fraction of vaccinated patients in the oncological cohort was higher in the beginning and approached the fraction in the age-matched general Swiss population at the end of the study period. Month of exam (p < 0.001) was the only significant predictor of the vaccination rate. CONCLUSION: Vaccination rate against COVID-19 in a Swiss oncological cohort increased steadily from February to September 2021. Compared to the age-matched general population it was higher in the beginning and similar by the end of the study period. Ethics approval: Trial registration: BASEC 2021-00444, Ethikkommission Zürich (Cantonal Ethics Committee Zurich), Switzerland, registered February 24th 2021.

Opportunistic deep learning powered calcium scoring in oncologic patients with very high coronary artery calcium (≥ 1000) undergoing 18F-FDG PET/CT.

Our aim was to identify and quantify high coronary artery calcium (CAC) with deep learning (DL)-powered CAC scoring (CACS) in oncological patients with known very high CAC (≥ 1000) undergoing 18F-FDG-PET/CT for re-/staging. 100 patients were enrolled: 50 patients with Agatston scores ≥ 1000 (high CACS group), 50 patients with Agatston scores < 1000 (negative control group). All patients underwent oncological 18F-FDG-PET/CT and cardiac SPECT myocardial perfusion imaging (MPI) by 99mTc-tetrofosmin within 6 months. CACS was manually performed on dedicated non-contrast ECG-gated CT scans obtained from SPECT-MPI (reference standard). Additionally, CACS was performed fully automatically with a user-independent DL-CACS tool on non-contrast, free-breathing, non-gated CT scans from 18F-FDG-PET/CT examinations. Image quality and noise of CT scans was assessed. Agatston scores obtained by manual CACS and DL tool were compared. The high CACS group had Agatston scores of 2200 ± 1620 (reference standard) and 1300 ± 1011 (DL tool, average underestimation of 38.6 ± 26%) with an intraclass correlation of 0.714 (95% CI 0.546, 0.827). Sufficient image quality significantly improved the DL tool's capability of correctly assigning Agatston scores ≥ 1000 (p = 0.01). In the control group, the DL tool correctly assigned Agatston scores < 1000 in all cases. In conclusion, DL-based CACS performed on non-contrast free-breathing, non-gated CT scans from 18F-FDG-PET/CT examinations of patients with known very high (≥ 1000) CAC underestimates CAC load, but correctly assigns an Agatston scores ≥ 1000 in over 70% of cases, provided sufficient CT image quality. Subgroup analyses of the control group showed that the DL tool does not generate false-positives.

Left atrial appendage occlusion in ventricular assist device patients to decrease thromboembolic events: A computer simulation study.

Atrial fibrillation (AF) is a common comorbidity in left ventricular assist device (LVAD) patients and has been identified as a risk factor for thromboembolic stroke. Blood stagnation within the left atrial appendage (LAA) is considered a possible major source of thrombosis and clinical studies have shown reduced thromboembolic risk after LAA occlusion (LAAO). Therefore, this study aims to investigate the effect of LAAO on thrombosis-related parameters using patient-specific simulations. Left ventricular and left atrial geometries of an LVAD patient were obtained from computed tomography and combined with hemodynamic data with either sinus rhythm (SR) or AF generated by a lumped parameter model. In four simulations applying contractile walls, stagnation volume and blood residence times were evaluated with or without AF and with or without LAAO. Reduced atrial contraction in AF resulted in unfavorable flow dynamics within the left atrium. The average atrial velocity was lower for the AF simulation when compared to SR, resulting in a 55% increase in the atrial stagnation volume (from 4.2 to 6.5 cm3). Moreover, blood remained in the LAA for more than 8 cardiac cycles. After LAAO the atrial stagnation decreased from 4.2 to 1.4 cm3 for SR and from 6.5 to 2.3 cm3 for the AF simulation. A significant stagnation volume was found in the LAA for both SR and AF, with larger values occurring with AF. These regions are known as potential sources for thrombus formation and can be diminished by LAAO. This significantly improved the thrombus-related flow parameters and may also lower the risk of thromboembolic events from the appendage.

Can Dynamic Whole-Body FDG PET Imaging Differentiate between Malignant and Inflammatory Lesions?

Background: Investigation of the clinical feasibility of dynamic whole-body (WB) [18F]FDG PET, including standardized uptake value (SUV), rate of irreversible uptake (Ki), and apparent distribution volume (Vd) in physiologic tissues, and comparison between inflammatory/infectious and cancer lesions. Methods: Twenty-four patients were prospectively included to undergo dynamic WB [18F]FDG PET/CT for clinically indicated re-/staging of oncological diseases. Parametric maps of Ki and Vd were generated using Patlak analysis alongside SUV images. Maximum parameter values (SUVmax, Kimax, and Vdmax) were measured in liver parenchyma and in malignant or inflammatory/infectious lesions. Lesion-to-background ratios (LBRs) were calculated by dividing the measurements by their respective mean in the liver tissue. Results: Seventy-seven clinical target lesions were identified, 60 malignant and 17 inflammatory/infectious. Kimax was significantly higher in cancer than in inflammatory/infections lesions (3.0 vs. 2.0, p = 0.002) while LBRs of SUVmax, Kimax, and Vdmax did not differ significantly between the etiologies: LBR (SUVmax) 3.3 vs. 2.9, p = 0.06; LBR (Kimax) 5.0 vs. 4.4, p = 0.05, LBR (Vdmax) 1.1 vs. 1.0, p = 0.18). LBR of inflammatory/infectious and cancer lesions was higher in Kimax than in SUVmax (4.5 vs. 3.2, p < 0.001). LBRs of Kimax and SUVmax showed a strong correlation (Spearman's rho = 0.83, p < 0.001). Conclusions: Dynamic WB [18F]FDG PET/CT is feasible in a clinical setting. LBRs of Kimax were higher than SUVmax. Kimax was higher in malignant than in inflammatory/infectious lesions but demonstrated a large overlap between the etiologies.