Thomas C. Kwee’s research while affiliated with University of Groningen Medical Center and other places

Objective To evaluate the repeatability of AI-based automatic measurement of vertebral and cardiovascular markers on low-dose chest CT. Methods We included participants of the population-based Imaging in Lifelines (ImaLife) study with low-dose chest CT at baseline and 3–4 month follow-up. An AI system (AI-Rad Companion chest CT prototype) performed automatic segmentation and quantification of vertebral height and density, aortic diameters, heart volume (cardiac chambers plus pericardial fat), and coronary artery calcium volume (CACV). A trained researcher visually checked segmentation accuracy. We evaluated the repeatability of adequate AI-based measurements at baseline and repeat scan using Intraclass Correlation Coefficient (ICC), relative differences, and change in CACV risk categorization, assuming no physiological change. Results Overall, 632 participants (63 ± 11 years; 56.6% men) underwent short-term repeat CT (mean interval, 3.9 ± 1.8 months). Visual assessment showed adequate segmentation in both baseline and repeat scan for 98.7% of vertebral measurements, 80.1–99.4% of aortic measurements (except for the sinotubular junction (65.2%)), and 86.0% of CACV. For heart volume, 53.5% of segmentations were adequate at baseline and repeat scans. ICC for adequately segmented cases showed excellent agreement for all biomarkers (ICC > 0.9). Relative difference between baseline and repeat measurements was < 4% for vertebral and aortic measurements, 7.5% for heart volume, and 28.5% for CACV. There was high concordance in CACV risk categorization (81.2%). Conclusion In low-dose chest CT, segmentation accuracy of AI-based software was high for vertebral, aortic, and CACV evaluation and relatively low for heart volume. There was excellent repeatability of vertebral and aortic measurements and high concordance in overall CACV risk categorization. Key Points Question Can AI algorithms for opportunistic screening in chest CT obtain an accurate and repeatable result when applied to multiple CT scans of the same participant? Findings Vertebral and aortic analysis showed accurate segmentation and excellent repeatability; coronary calcium segmentation was generally accurate but showed modest repeatability due to a non-electrocardiogram-triggered protocol. Clinical relevance Opportunistic screening for diseases outside the primary purpose of the CT scan is time-consuming. AI allows automated vertebral, aortic, and coronary artery calcium (CAC) assessment, with highly repeatable outcomes of vertebral and aortic biomarkers and high concordance in overall CAC categorization.

Bladder cancer is the 10th most common and 13th most deadly cancer worldwide, with urothelial carcinomas being the most common type. Distinguishing between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is essential due to significant differences in management and prognosis. MRI may play an important diagnostic role in this setting. The Vesical Imaging Reporting and Data System (VI-RADS), a multiparametric MRI (mpMRI)-based consensus reporting platform, allows for standardized preoperative muscle invasion assessment in BCa with proven diagnostic accuracy. However, post-treatment assessment using VI-RADS is challenging because of anatomical changes, especially in the interpretation of the muscle layer. MRI techniques that provide tumor tissue physiological information, including diffusion-weighted (DW)- and dynamic contrast-enhanced (DCE)-MRI, combined with derived quantitative imaging biomarkers (QIBs), may potentially overcome the limitations of BCa evaluation when predominantly focusing on anatomic changes at MRI, particularly in the therapy response setting. Delta-radiomics, which encompasses the assessment of changes (Δ) in image features extracted from mpMRI data, has the potential to monitor treatment response. In comparison to the current Response Evaluation Criteria in Solid Tumors (RECIST), QIBs and mpMRI-based radiomics, in combination with artificial intelligence (AI)-based image analysis, may potentially allow for earlier identification of therapy-induced tumor changes. This review provides an update on the potential of QIBs and mpMRI-based radiomics and discusses the future applications of AI in BCa management, particularly in assessing treatment response. Critical relevance statement Incorporating mpMRI-based quantitative imaging biomarkers, radiomics, and artificial intelligence into bladder cancer management has the potential to enhance treatment response assessment and prognosis prediction. Key Points Quantitative imaging biomarkers (QIBs) from mpMRI and radiomics can outperform RECIST for bladder cancer treatments. AI improves mpMRI segmentation and enhances radiomics feature extraction effectively. Predictive models integrate imaging biomarkers and clinical data using AI tools. Multicenter studies with strict criteria validate radiomics and QIBs clinically. Consistent mpMRI and AI applications need reliable validation in clinical practice. Graphical Abstract

The proposed deep learning model based on MRI and clinical characteristics showed good performance in predicting progression from low-risk prostate cancer to clinically significant prostate cancer.

Spinal implant infections are a serious complications of instrumented spinal fusion surgeries, carrying high morbidity and complex management challenges. Early postoperative infections may manifest with wound-healing issues, back pain, and fevers. Magnetic resonance imaging (MRI) is the preferred imaging modality, but can be limited by metal artifacts. For cases with stable implants, surgical debridement with implant retention combined with at least 12 weeks of antibiotics is currently considered appropriate treatment. Staphylococcal infections are ideally treated with biofilm-active antibiotics. Suppressive antibiotic therapy can be considered when surgical debridement has been delayed or is incomplete, and for those who are poor surgical candidates for another surgery. Chronic infections may present insidiously with implant failure or pseudarthrosis; implant removal or revision is generally pursued. As current guidance is heavily based on the periprosthetic joint infection literature and low-level studies on spinal implant infections, further research on optimizing diagnostic and treatment approaches is needed.

Purpose The aims of this study were to determine the publication pressure perceived by nuclear medicine scientists and to identify associated determinants. Patients and Methods Corresponding authors who published in Clinical Nuclear Medicine , Journal of Nuclear Medicine , or European Journal of Nuclear Medicine and Molecular Imaging between 2021 and 2023 were invited to participate in this survey study. Publication pressure was assessed using the revised Publication Pressure Questionnaire in the domains of “publication stress” (stress due to perceived pressure to publish), “publication attitude” (attitude regarding current publication culture), and “publication resources” (resources when working on publications or experiencing stress when working on publishing), with 5-point Likert scales. Results A total of 181 individuals participated. Median Publication Pressure Questionnaire scores in the domains “publication stress,” “publication attitude,” and “publication resources” were 3.33, 3.33, and 2.17, respectively. None of the researchers’ characteristics were significantly associated with publication stress. Age >65 years was significantly associated with a more positive view on the publication climate (β coefficient of −0.552, P = 0.007). Several variables were significantly associated with a perception of fewer factors available to alleviate publication pressure: age 45–54 years (β coefficient of 0.249, P = 0.030), age 55–64 years (β coefficient of 0.421, P = 0.002), associate professor position (β coefficient of 0.398, P < 0.001), fellow/resident position (β coefficient of 0.355, P = 0.007), <5 years of research experience (β coefficient of 0.410, P = 0.026), and 5–10 years of research experience (β coefficient of 0.361, P = 0.003). Conclusions Publication pressure among nuclear medicine scientists is appreciable. Several researcher characteristics appear to be associated with vulnerability to publication pressure.

Background Spine is the most common location for bone metastases. Microwave ablation (MWA) is a technique for minimally invasive tumor treatment. The aim of the current study was to determine whether MWA is a safe option for treatment in vertebral bodies and to gain data on the amount of cortical insulation in the spine. Method MWA was applied with different settings for power and time in both in- and ex-vivo sheep vertebral bodies. Safety was evaluated by temperature measurements at critical surrounding structures (e.g. spinal cord, nerve root). Furthermore, the distribution of heat through the bone at 5 mm from the ablation needle was measured and compared to the temperature at the posterior wall. Results An effect of cortical insulation in the spine was found, for ablations with 20–30 and 50 W (p < 0.01). Ablations with wattage levels of 40–50 W almost instantly led to temperatures over 60 °C at the posterior wall. The temperature remained below 60 °C for 4 min in ex-vivo ablations with 20 and 30 W. However, in the in-vivo experiment paralysis was frequently seen (10/12 sheep) in lower wattages (20–30 W) as well and the experiment was therefore terminated. Conclusion MWA is an effective approach for local bone destruction in the spine. However, given the high risk of complications, caution is advised for treatment in vertebral bodies without better local distribution accuracy. Since cortical insulation appears insufficient to protect the spinal canal from excess heat, MWA involves a risk of paralysis.

To investigate temporal trends in the individual workload of nuclear medicine physicians at a large tertiary care academic center between 2008 and 2023. This study analyzed the reporting workload of nuclear medicine physicians in a large tertiary care academic center in The Netherlands on 36 unique (randomly sampled) calendar days, for each year between 2008 and 2023. The average daily departmental workload (measured with relative value units) was calculated for each year between 2008 and 2023. The individual workload was calculated by dividing the average daily departmental workload in each year by the available full-time equivalent nuclear medicine physicians in each year. Mann–Kendall tests were used to assess for any temporal monotonic trends in individual workload and types of nuclear medicine procedures performed. Individual workload increased significantly between 2008 and 2023 (Mann–Kendall tau of 0.611, P = 0.001). Individual workload in 2023 was 86% higher than in 2008. The use of positron emission tomography (PET) increased significantly (Mann–Kendall tau of 0.912, P < 0.001) between 2008 and 2023. The use of diagnostic scintigraphy decreased significantly in the same period (Mann–Kendall tau of -0.817, P < 0.001). The use of DEXA also showed a significant decrease (Mann–Kendall tau of -0.467, P = 0.013), but this decrease was negligible on a relative scale. The number of therapeutic procedures (Mann–Kendall tau of -0.100, P = 0.626) remained statistically stable in this period. Our single-center study showed that the individual workload of nuclear medicine physicians has increased significantly between 2008 and 2023, driven by the rise in PET scans. The demand for both diagnostic and therapeutic nuclear medicine procedures and associated workload is expected to keep on increasing in the foreseeable future. This workload trend should be taken into account by policymakers involved in nuclear medicine staffing planning. A healthy balance between the nuclear medicine workforce and workload is necessary to maintain the quality of care, to be able to perform other important (academic) tasks such as research, educating and training medical students and residents, and management, and to prevent physician burnout and dropout.

Background: The workload of musculoskeletal radiologists has come under pressure. Our objective was to estimate the reading times of common musculoskeletal MRI examinations. Methods: A total of 144 radiologists were asked to estimate reading times (including interpretation and reporting) for MRI of the shoulder, elbow, wrist, hip, knee, and ankle. Multivariate linear regression analyses were performed. Results: Reported median reading times with interquartile range (IQR) for the shoulder, elbow, wrist, hip, knee, and ankle were 10 (IQR 6-14), 10 (IQR 6-14), 11 (IQR 7.5-14.5), 10 (IQR 6.6-13.4), 8 (IQR 4.6-11.4), and 10 (IQR 6.5-13.5) min, respectively. Radiologists aged 35-44 years reported shorter reading times for the shoulder (β coefficient [β] = B-3.412, p = 0.041), hip (β = -3.596, p = 0.023), and knee (β = -3.541, p = 0.013) than radiologists aged 45-54 years. Radiologists not working in an academic/teaching hospital reported shorter reading times for the hip (β = -3.611, p = 0.025) and knee (β = -3.038, p = 0.035). Female radiologists indicated longer reading times for all joints (β of 2.592 to 5.186, p ≤ 0.034). Radiologists without musculoskeletal fellowship training indicated longer reading times for the shoulder (β = 4.604, p = 0.005), elbow (β = 3.989, p = 0.038), wrist (β = 4.543, p = 0.014), and hip (β = 2.380, p = 0.119). Radiologists with <5 years of post-residency experience indicated longer reading times for all joints (β of 5.355 to 6.984, p ≤ 0.045), and radiologists with 5-10 years of post-residency experience reported longer reading time for the knee (β = 3.660, p = 0.045) than those with >10 years of post-residency experience. Conclusions: There is substantial variation among radiologists in reported reading times for common musculoskeletal MRI examinations. Several radiologist-related determinants appear to be associated with reading speed, including age, gender, hospital type, training, and experience.