The aims of this study were to evaluate spectral detector CT (SDCT)-derived iodine concentration (IC) of lymph nodes diagnosed as metastatic and benign in prostate-specific membrane antigen (PSMA) PET/CT and to assess its potential use for lymph node assessment in prostate cancer.Thirty-four prostate cancer patients were retrospectively included: 16 patients with and 18 without lymph node metastases as determined by PSMA PET/CT. Patients underwent PSMA PET/CT as well as portal venous phase abdominal SDCT for clinical cancer follow-up. Only scan pairs with a stable nodal status indicated by constant size as well as comparable prostate-specific antigen (PSA) levels were included. One hundred benign and 96 suspected metastatic lymph nodes were annotated and correlated between SDCT and PSMA PET/CT. Iodine concentration in SDCT-derived iodine maps and SUVmax in ultra-high definition reconstructions from PSMA PET/CT were acquired based on the region of interest.Metastatic lymph nodes as per PSMA PET/CT showed higher IC than nonmetastatic nodes (1.9 ± 0.6 mg/mL vs 1.5 ± 0.5 mg/mL, P < 0.05) resulting in an AUC of 0.72 and sensitivity/specificity of 81.3%/58.5%. The mean short axis diameter of metastatic lymph nodes was larger than that of nonmetastatic nodes (6.9 ± 3.6 mm vs 5.3 ± 1.3 mm; P < 0.05); a size threshold of 1 cm short axis diameter resulted in a sensitivity/specificity of 12.8%/99.0%. There was a significant yet weak positive correlation between SUVmax and IC (rs = 0.25; P < 0.001).Spectral detector CT-derived IC was increased in lymph nodes diagnosed as metastatic in PSMA PET/CT yet showed considerable data overlap. The correlation between IC and SUVmax was weak, highlighting the role of PSMA PET/CT as important reference imaging modality for detection of lymph node metastases in prostate cancer patients.
Objectives To investigate whether virtual monoenergetic images (VMI) and iodine maps derived from spectral detector computed tomography (SDCT) improve early assessment of technique efficacy in patients who underwent microwave ablation (MWA) for hepatocellular carcinoma (HCC) in liver cirrhosis. Methods This retrospective study comprised 39 patients with 49 HCC lesions treated with MWA. Biphasic SDCT was performed 7.7±4.0 days after ablation. Conventional images (CI), VMI and IM were reconstructed. Signal- and contrast-to-noise ratio (SNR, CNR) in the ablation zone (AZ), hyperemic rim (HR) and liver parenchyma were calculated using regions-of-interest analysis and compared between CI and VMI between 40–100 keV. Iodine concentration and perfusion ratio of HR and residual tumor (RT) were measured. Two readers evaluated subjective contrast of AZ and HR, technique efficacy (complete vs. incomplete ablation) and diagnostic confidence at determining technique efficacy. Results Attenuation of liver parenchyma, HR and RT, SNR of liver parenchyma and HR, CNR of AZ and HR were significantly higher in low-keV VMI compared to CI (all p<0.05). Iodine concentration and perfusion ratio differed significantly between HR and RT (all p<0.05; e.g. iodine concentration, 1.6±0.5 vs. 2.7±1.3 mg/ml). VMI 50keV improved subjective AZ-to-liver contrast, HR-to-liver contrast, visualization of AZ margin and vessels adjacent to AZ compared to CI (all p<0.05). Diagnostic accuracy for detection of incomplete ablation was slightly higher in VMI 50keV compared to CI (0.92 vs. 0.89), while diagnostic confidence was significantly higher in VMI 50keV (p<0.05). Conclusions Spectral detector computed tomography derived low-keV virtual monoenergetic images and iodine maps provide superior early assessment of technique efficacy of MWA in HCC compared to CI.
BACKGROUND The latest advancement of artificial intelligence (AI) is generative pretrained transformer large language models (LLMs). They have been trained on massive amounts of text, enabling humanlike and semantical responses to text-based inputs and requests. Foreshadowing numerous possible applications in various fields, the potential of such tools for medical data integration and clinical decision-making is not yet clear. OBJECTIVE In this study, we investigate the potential of LLMs in report-based medical decision-making on the example of acute ischemic stroke (AIS), where clinical and image-based information may indicate an immediate need for mechanical thrombectomy (MT). The purpose was to elucidate the feasibility of integrating radiology report data and other clinical information in the context of therapy decision-making using LLMs. METHODS A hundred patients with AIS were retrospectively included, for which 50% (50/100) was indicated for MT, whereas the other 50% (50/100) was not. The LLM was provided with the computed tomography report, information on neurological symptoms and onset, and patients’ age. The performance of the AI decision-making model was compared with an expert consensus regarding the binary determination of MT indication, for which sensitivity, specificity, and accuracy were calculated. RESULTS The AI model had an overall accuracy of 88%, with a specificity of 96% and a sensitivity of 80%. The area under the curve for the report-based MT decision was 0.92. CONCLUSIONS The LLM achieved promising accuracy in determining the eligibility of patients with AIS for MT based on radiology reports and clinical information. Our results underscore the potential of LLMs for radiological and medical data integration. This investigation should serve as a stimulus for further clinical applications of LLMs, in which this AI should be used as an augmented supporting system for human decision-making.
The loss of salivary gland function caused by radiation therapy of the head and neck is a serious condition and it affects a patient's quality of life. The current lack of effective therapies demands new options to be explored. This study tested whether human salivary gland epithelial cells (SGECs) could be successfully cultured on a decellularized porcine gut matrix (SIS-muc) in both mono- and coculture with microvascular endothelial cells (mvECs). By performing immunofluorescence imaging, transmission as well as scanning electron microscopy (SEM), quantitative polymerase chain reaction (qPCR), and an amylase enzyme assay, it was investigated as to what extent the three-dimensional (3D)-cultured cells could maintain their molecular differentiation and the production of working α-amylase (α-AMY) compared with two-dimensional (2D) culture. In both 3D mono- and coculture, SGECs were successfully cultured and formed acinar-like structures. Those findings were confirmed by SEM imaging. Immunofluorescence imaging revealed that 3D-cultured cells expressed α-AMY, Claudin-1 (CL-1), and water channel protein aquaporin-5 (AQP-5). Two-dimensional-cultured cells only were positive for α-AMY. Real time (RT)-qPCR analysis showed that α-AMY relative gene expression was higher in both 3D mono- and coculture than in 2D culture. In α-AMY enzyme assay, cocultured SGECs showed about 25 times increased enzyme activity compared with 2D-cultured cells. In conclusion, the SIS-muc combined with endothelial coculture seems a suitable culture setting for the tissue engineering of functional human salivary gland tissue.
Zielsetzung Von der Dual-Layer-Dual-Energy-CT (dlDECT) abgeleitete virtuell native (VUE) Bilder sind in verschiedenen Studien zur Differenzierung von Nebennierenläsionen untersucht worden, und unterschiedliche Grenzwerte zur Differenzierung wurden vorgeschlagen. Ziel der Studie war es, frühere VUE-Schwellenwerte zur Bestimmung von lipidreichen Adenomen auf der Grundlage von dlDECT in einer großen retrospektiven Kohorte zu validieren und zu untersuchen, ob der zugrunde liegende Primärtumor von Patienten mit Nebennierenmetastasen die DECT-basierte Differenzierung von Nebennierenläsionen beeinflusst.
Zielsetzung Die Differenzierung zwischen benignen und metastatischen Lungenrundherden bei onkologischen Patienten bedarf häufig zusätzlicher Nachuntersuchungen. Ziel war daher, den Nutzen von Radiomics für diese Differenzierung zu untersuchen.
We sought to determine relative utilization of abdominal imaging modalities in coronavirus disease 2019 (COVID-19) patients at a single institution during the first surge and evaluate whether abdominal magnetic resonance imaging (MRI) changed diagnosis and management. 1107 COVID-19 patients who had abdominal imaging were analyzed for modality and imaging setting. Patients who underwent abdominal MRI were reviewed to determine impact on management. Of 2259 examinations, 80% were inpatient, 14% were emergency, and 6% were outpatient consisting of 55% radiograph (XR), 31% computed tomography (CT), 13% ultrasound (US), and 0.6% MRI. Among 1107 patients, abdominal MRI was performed in 12 within 100 days of positive SARS-CoV-2 PCR. Indications were unrelated to COVID-19 in 75% while MRI was performed for workup of acute liver dysfunction in 25%. In 1 of 12 patients, MRI resulted in change to management unrelated to COVID-19 diagnosis. During the first surge of COVID-19 at one institution, the most common abdominal imaging examinations were radiographs and CT followed by ultrasound with the majority being performed as inpatients. Future COVID-19 surges may place disproportionate demands on inpatient abdominal radiography and CT resources. Abdominal MRI was rarely performed and did not lead to change in diagnosis or management related to COVID-19 but needs higher patient numbers for accurate assessment of utility.
To compare immune response evaluation criteria in solid tumors (iRECIST) and response evaluation criteria in solid tumors (RECIST) 1.1 for response assessment of immune checkpoint inhibitor (ICI) therapy in a real-world setting in patients with melanoma and non-small cell lung cancer (NSCLC).
