Diagnostic Performance of GPT-4o and Claude 3 Opus in Determining Causes of Death From Medical Histories and Postmortem CT Findings.

INTRODUCTION: This study evaluates the diagnostic performance of the latest large language models (LLMs), GPT-4o (OpenAI, San Francisco, CA, USA) and Claude 3 Opus (Anthropic, San Francisco, CA, USA), in determining causes of death from medical histories and postmortem CT findings. METHODS: We included 100 adult cases whose postmortem CT scans were diagnosable for the causes of death using the gold standard of autopsy results. Their medical histories and postmortem CT findings were compiled, and clinical and imaging diagnoses of both the underlying and immediate causes of death, as well as their personal information, were carefully separated from the database to be shown to the LLMs. Both GPT-4o and Claude 3 Opus generated the top three differential diagnoses for each of the underlying or immediate causes of death based on the following three prompts: 1) medical history only; 2) postmortem CT findings only; and 3) both medical history and postmortem CT findings. The diagnostic performance of the LLMs was compared using McNemar's test. RESULTS: For the underlying cause of death, GPT-4o achieved primary diagnostic accuracy rates of 78%, 72%, and 78%, while Claude 3 Opus achieved 72%, 56%, and 75% for prompts 1, 2, and 3, respectively. Including any of the top three differential diagnoses, GPT-4o's accuracy rates were 92%, 90%, and 92%, while Claude 3 Opus's rates were 93%, 69%, and 93% for prompts 1, 2, and 3, respectively. For the immediate cause of death, GPT-4o's primary diagnostic accuracy rates were 55%, 58%, and 62%, while Claude 3 Opus's rates were 60%, 62%, and 63% for prompts 1,2, and 3, respectively. For any of the top three differential diagnoses, GPT-4o's accuracy rates were 88% for prompt 1 and 91% for prompts 2 and 3, whereas Claude 3 Opus's rates were 92% for all three prompts. Significant differences between the models were observed for prompt two in diagnosing the underlying cause of death (p = 0.03 and <0.01 for the primary and top three differential diagnoses, respectively). CONCLUSION: Both GPT-4o and Claude 3 Opus demonstrated relatively high performance in diagnosing both the underlying and immediate causes of death using medical histories and postmortem CT findings.

Diagnostic performances of Claude 3 Opus and Claude 3.5 Sonnet from patient history and key images in Radiology's "Diagnosis Please" cases.

PURPOSE: The diagnostic performance of large language artificial intelligence (AI) models when utilizing radiological images has yet to be investigated. We employed Claude 3 Opus (released on March 4, 2024) and Claude 3.5 Sonnet (released on June 21, 2024) to investigate their diagnostic performances in response to the Radiology's Diagnosis Please quiz questions. MATERIALS AND METHODS: In this study, the AI models were tasked with listing the primary diagnosis and two differential diagnoses for 322 quiz questions from Radiology's "Diagnosis Please" cases, which included cases 1 to 322, published from 1998 to 2023. The analyses were performed under the following conditions: (1) Condition 1: submitter-provided clinical history (text) alone. (2) Condition 2: submitter-provided clinical history and imaging findings (text). (3) Condition 3: clinical history (text) and key images (PNG file). We applied McNemar's test to evaluate differences in the correct response rates for the overall accuracy under Conditions 1, 2, and 3 for each model and between the models. RESULTS: The correct diagnosis rates were 58/322 (18.0%) and 69/322 (21.4%), 201/322 (62.4%) and 209/322 (64.9%), and 80/322 (24.8%) and 97/322 (30.1%) for Conditions 1, 2, and 3 for Claude 3 Opus and Claude 3.5 Sonnet, respectively. The models provided the correct answer as a differential diagnosis in up to 26/322 (8.1%) for Opus and 23/322 (7.1%) for Sonnet. Statistically significant differences were observed in the correct response rates among all combinations of Conditions 1, 2, and 3 for each model (p < 0.01). Claude 3.5 Sonnet outperformed in all conditions, but a statistically significant difference was observed only in the comparison for Condition 3 (30.1% vs. 24.8%, p = 0.028). CONCLUSION: Two AI models demonstrated a significantly improved diagnostic performance when inputting both key images and clinical history. The models' ability to identify important differential diagnoses under these conditions was also confirmed.

Effect of deep learning reconstruction on the assessment of pancreatic cystic lesions using computed tomography.

This study aimed to compare the image quality and detection performance of pancreatic cystic lesions between computed tomography (CT) images reconstructed by deep learning reconstruction (DLR) and filtered back projection (FBP). This retrospective study included 54 patients (mean age: 67.7 ± 13.1) who underwent contrast-enhanced CT from May 2023 to August 2023. Among eligible patients, 30 and 24 were positive and negative for pancreatic cystic lesions, respectively. DLR and FBP were used to reconstruct portal venous phase images. Objective image quality analyses calculated quantitative image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) using regions of interest on the abdominal aorta, pancreatic lesion, and pancreatic parenchyma. Three blinded radiologists performed subjective image quality assessment and lesion detection tests. Lesion depiction, normal structure illustration, subjective image noise, and overall image quality were utilized as subjective image quality indicators. DLR significantly reduced quantitative image noise compared with FBP (p < 0.001). SNR and CNR were significantly improved in DLR compared with FBP (p < 0.001). Three radiologists rated significantly higher scores for DLR in all subjective image quality indicators (p ≤ 0.029). Performance of DLR and FBP were comparable in lesion detection, with no statistically significant differences in the area under the receiver operating characteristic curve, sensitivity, specificity and accuracy. DLR reduced image noise and improved image quality with a clearer depiction of pancreatic structures. These improvements may have a positive effect on evaluating pancreatic cystic lesions, which can contribute to appropriate management of these lesions.

Longitudinal CT, MRI, and 18F-FDG PET/CT Imaging Findings of Peliosis Hepatis: A Case Report.

Peliosis hepatis (PH) is a rare benign vascular condition characterized by sinusoidal dilatation and the presence of blood-filled spaces within the liver. PH is often clinically asymptomatic and is discovered incidentally. It presents a clinical challenge as its imaging findings frequently mimic other pathologies, including primary or secondary malignancies and abscesses. In this article, we present a case of a 73-year-old woman with a history of recurrent tongue cancer treated by surgery and chemoradiotherapy, and concurrent multiple myeloma, in whom PH was incidentally discovered. Based on computed tomography, magnetic resonance imaging, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) imaging findings prior to biopsy, PH was diagnosed, and pathologically confirmed. Follow-up computed tomography five months after the discontinuation of raloxifene hydrochloride, a selective estrogen receptor modulator and a suspected drug causing PH, the regression of PH lesions was observed.

Diagnostic performances of GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro in "Diagnosis Please" cases.

PURPOSE: Large language models (LLMs) are rapidly advancing and demonstrating high performance in understanding textual information, suggesting potential applications in interpreting patient histories and documented imaging findings. As LLMs continue to improve, their diagnostic abilities are expected to be enhanced further. However, there is a lack of comprehensive comparisons between LLMs from different manufacturers. In this study, we aimed to test the diagnostic performance of the three latest major LLMs (GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro) using Radiology Diagnosis Please Cases, a monthly diagnostic quiz series for radiology experts. MATERIALS AND METHODS: Clinical history and imaging findings, provided textually by the case submitters, were extracted from 324 quiz questions originating from Radiology Diagnosis Please cases published between 1998 and 2023. The top three differential diagnoses were generated by GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro, using their respective application programming interfaces. A comparative analysis of diagnostic performance among these three LLMs was conducted using Cochrane's Q and post hoc McNemar's tests. RESULTS: The respective diagnostic accuracies of GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro for primary diagnosis were 41.0%, 54.0%, and 33.9%, which further improved to 49.4%, 62.0%, and 41.0%, when considering the accuracy of any of the top three differential diagnoses. Significant differences in the diagnostic performance were observed among all pairs of models. CONCLUSION: Claude 3 Opus outperformed GPT-4o and Gemini 1.5 Pro in solving radiology quiz cases. These models appear capable of assisting radiologists when supplied with accurate evaluations and worded descriptions of imaging findings.

Cutoff CT value can identify upper gastrointestinal bleeding on postmortem CT: Development and validation study.

This study aimed to establish the diagnostic criteria for upper gastrointestinal bleeding (UGIB) using postmortem computed tomography (PMCT). This case-control study enrolled 27 consecutive patients with autopsy-proven UGIB and 170 of the 566 patients without UGIB who died in a university hospital in Japan after treatment and underwent both noncontrast PMCT and conventional autopsy between 2009 and 2020. Patients were randomly allocated to two groups: derivation and validation sets. Imaging findings of the upper gastrointestinal contents, including CT values, were recorded and evaluated for their power to diagnose UGIB in the derivation set and validated in the validation set. In the derivation set, the mean CT value of the upper gastrointestinal contents was 48.2 Hounsfield units (HU) and 22.8 HU in cases with and without UGIB. The optimal cutoff CT value for diagnosing UGIB was ≥27.7 HU derived from the receiver operating characteristic curve analysis (sensitivity, 91.7%; specificity, 81.2%; area under the curve, 0.898). In the validation set, the sensitivity and specificity in diagnosing UGIB for the CT cutoff value of ≥27.7 HU were 84.6% and 77.6%, respectively. In addition to the CT value of ≥27.7 HU, PMCT findings of solid-natured gastrointestinal content and intra/peri-content bubbles ≥4 mm, extracted from the derivation set, increased the specificity for UGIB (96.5% and 98.8%, respectively) but decreased the sensitivity (61.5% and 38.5%, respectively) in the validation set. In diagnosing UGIB on noncontrast PMCT, the cutoff CT value of ≥27.7 HU and solid gastrointestinal content were valid and reproducible diagnostic criteria.

Diffuse peritoneal dissemination of intracranial pure germinoma via ventriculoperitoneal shunt.

Germinomas frequently cause hydrocephalus, and ventriculoperitoneal shunts (VPS) have been commonly used for their management. Although VPS can potentially serve as a route for peritoneal dissemination of germinomas, the abdominal imaging characteristics of this rare yet important complication remain unknown. In this article, we report the computed tomography imaging findings of diffuse peritoneal dissemination of intracranial germinoma.

Neuroimaging Features of Cytokine-related Diseases.

Cytokines are small secreted proteins that have specific effects on cellular interactions and are crucial for functioning of the immune system. Cytokines are involved in almost all diseases, but as microscopic chemical compounds they cannot be visualized at imaging for obvious reasons. Several imaging manifestations have been well recognized owing to the development of cytokine therapies such as those with bevacizumab (antibody against vascular endothelial growth factor) and chimeric antigen receptor (CAR) T cells and the establishment of new disease concepts such as interferonopathy and cytokine release syndrome. For example, immune effector cell-associated neurotoxicity is the second most common form of toxicity after CAR T-cell therapy toxicity, and imaging is recommended to evaluate the severity. The emergence of COVID-19, which causes a cytokine storm, has profoundly impacted neuroimaging. The central nervous system is one of the systems that is most susceptible to cytokine storms, which are induced by the positive feedback of inflammatory cytokines. Cytokine storms cause several neurologic complications, including acute infarction, acute leukoencephalopathy, and catastrophic hemorrhage, leading to devastating neurologic outcomes. Imaging can be used to detect these abnormalities and describe their severity, and it may help distinguish mimics such as metabolic encephalopathy and cerebrovascular disease. Familiarity with the neuroimaging abnormalities caused by cytokine storms is beneficial for diagnosing such diseases and subsequently planning and initiating early treatment strategies. The authors outline the neuroimaging features of cytokine-related diseases, focusing on cytokine storms, neuroinflammatory and neurodegenerative diseases, cytokine-related tumors, and cytokine-related therapies, and describe an approach to diagnosing cytokine-related disease processes and their differentials. ©RSNA, 2024 Supplemental material is available for this article.

Transient interruption of contrast on CT pulmonary angiography: effect of mid-inspiratory vs. end-inspiratory respiration command.

PURPOSE: To investigate the effects of mid-inspiratory respiration commands and other factors on transient interruption of contrast (TIC) incidence on CT pulmonary angiography. METHODS: In this retrospective study, 824 patients (mean age, 66.1 ± 15.3 years; 342 males) who had undergone CT pulmonary angiography between January 2021 and February 2023 were included. Among them, 545 and 279 patients were scanned at end- and mid-inspiratory levels, respectively. By placing a circular region of interest, CT attenuation of the main pulmonary artery (CTMPA) was recorded. Associations between several factors, including patient age, body weight, sex, respiratory command vs. TIC and severe TIC incidence (defined as CTMPA < 200 and 150 HU, respectively), were assessed using logistic regression analyses with stepwise regression selection based on Akaike's information criterion. RESULTS: Mid-inspiratory respiration command, in addition to patient age and lighter body weight, had negative association with the incidence of TIC. Only patient age, lighter body weight, female sex, and larger cardiothoracic ratio were negatively associated with severe TIC incidence. Mid-inspiratory respiration commands helped reduce TIC incidence among patients aged < 65 years (p = 0.039) and those with body weight ≥ 75 kg (p = 0.005) who were at high TIC risk. CONCLUSION: Changing the respiratory command from end- to mid-inspiratory levels, as well as patient age and body weight, was significantly associated with TIC incidence.

Radiological Imaging Findings of Adrenal Abnormalities in TAFRO Syndrome: A Systematic Review.

This systematic review article aims to investigate the clinical and radiological imaging characteristics of adrenal abnormalities in patients with thrombocytopenia, anasarca, fever, reticulin fibrosis, renal dysfunction, and organomegaly (TAFRO) syndrome. We searched the literature in PubMed, the Cochrane Library, and the Web of Science Core Collection. Ultimately, we analyzed 11 studies with 22 patients plus our 1 patient, totaling 23 patients. The mean age was 47.0 ± 12.6 years. There were 20 male and 3 female patients, respectively. The histopathological analysis of lymph nodes was conducted in 15 patients (65.2%), and the diagnosis was consistent with TAFRO syndrome in all 15 patients. Among the 23 patients, 11 patients (18 adrenal glands) showed adrenal ischemia/infarction, 9 patients (13 adrenal glands) showed adrenal hemorrhage, and 4 patients (7 adrenal glands) showed adrenomegaly without evidence of concurrent ischemia/infarction or hemorrhage. One patient demonstrated unilateral adrenal hemorrhage and contralateral adrenomegaly. In patients with adrenal ischemia/infarction, the adrenal glands displayed poor enhancement through contrast-enhanced computed tomography (CT). In patients with adrenal hemorrhage, the adrenal glands revealed high attenuation through non-enhanced CT and hematoma through magnetic resonance imaging. Adrenomegaly, with or without adrenal ischemia/infarction or hemorrhage, was observed in all patients (23/23, 100%). The subsequent calcification of the affected adrenal glands was frequently observed (9/14, 64.3%) when a follow-up CT was performed. Abdominal pain was frequent (15/23, 65.2%), all of which occurred after the disease's onset, suggesting the importance of considering TAFRO syndrome as a cause of acute abdomen. Given the absence of evidence of adrenal abnormalities in non-TAFRO-idiopathic multicentric Castleman disease (iMCD), they may serve as diagnostic clues for differentiating TAFRO syndrome from non-TAFRO-iMCD.

Apparent diffusion coefficient for differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck: a systematic review and meta-analysis.

BACKGROUND: Radiological differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck is often difficult due to their similarities. PURPOSE: To evaluate the diagnostic benefit of apparent diffusion coefficient (ADC) calculated from diffusion-weighted imaging (DWI) in differentiating the two. MATERIAL AND METHODS: A systematic review was performed by searching the MEDLINE, Scopus, and Embase databases in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. Forest plots and the pooled mean difference of ADC values were calculated to describe the relationship between extra-nodal lymphoma and squamous cell carcinoma in the head and neck. Heterogeneity among studies was evaluated using the Cochrane Q test and I2 statistic. RESULTS: The review identified eight studies with 440 patients (441 lesions) eligible for meta-analysis. Among all studies, the mean ADC values of squamous cell carcinoma was 0.88 × 10-3mm2/s and that of lymphoma was 0.64 × 10-3mm2/s. In the meta-analysis, the ADC value of lymphoma was significantly lower than that of squamous cell carcinoma (pooled mean difference = 0.235, 95% confidence interval [CI] = 0.168-0.302, P <0.0001). The Cochrane Q test (chi-square = 55.7, P <0.0001) and I2 statistic (I2 = 87.4%, 95% CI = 77.4-93.0%) revealed significant heterogeneity. CONCLUSION: This study highlights the value of quantitative assessment of ADC for objective and reliable differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck. Conclusions should be interpreted with caution due to heterogeneity in the study data.

Deep-Learning Reconstruction of High-Resolution CT Improves Interobserver Agreement for the Evaluation of Pulmonary Fibrosis.

Objective: This study aimed to investigate whether deep-learning reconstruction (DLR) improves interobserver agreement in the evaluation of honeycombing for patients with interstitial lung disease (ILD) who underwent high-resolution computed tomography (CT) compared with hybrid iterative reconstruction (HIR). Methods: In this retrospective study, 35 consecutive patients suspected of ILD who underwent CT including the chest region were included. High-resolution CT images of the unilateral lung with DLR and HIR were reconstructed for the right and left lungs. A radiologist placed regions of interest on the lung and measured standard deviation of CT attenuation (i.e., quantitative image noise). In the qualitative image analyses, 5 blinded readers assessed the presence of honeycombing and reticulation, qualitative image noise, artifacts, and overall image quality using a 5-point scale (except for artifacts which was evaluated using a 3-point scale). Results: The quantitative and qualitative image noise in DLR was remarkably reduced compared to that in HIR (P < .001). Artifacts and overall DLR quality were significantly improved compared to those of HIR (P < .001 for 4 out of 5 readers). Interobserver agreement in the evaluations of honeycombing and reticulation for DLR (0.557 [0.450-0.693] and 0.525 [0.470-0.541], respectively) were higher than those for HIR (0.321 [0.211-0.520] and 0.470 [0.354-0.533], respectively). A statistically significant difference was found for honeycombing (P = .014). Conclusions: DLR improved interobserver agreement in the evaluation of honeycombing in patients with ILD on CT compared to HIR.

Diffusion histogram profiles predict molecular features of grade 4 in histologically lower-grade adult diffuse gliomas following WHO classification 2021.

OBJECTIVES: In the latest World Health Organization classification 2021, grade 4 adult diffuse gliomas can be diagnosed with several molecular features even without histological evidence of necrosis or microvascular proliferation. We aimed to explore whole tumor histogram-derived apparent diffusion coefficient (ADC) histogram profiles for differentiating between the presence (Mol-4) and absence (Mol-2/3) of grade 4 molecular features in histologically lower-grade gliomas. METHODS: Between June 2019 and October 2022, 184 adult patients with diffuse gliomas underwent MRI. After excluding 121 patients, 18 (median age, 64.5 [range, 37-84 years]) Mol-4 and 45 (median 40 [range, 18-73] years) Mol-2/3 patients with histologically lower-grade gliomas were enrolled. Whole tumor volume-of-interest-derived ADC histogram profiles were calculated and compared between the two groups. Stepwise logistic regression analysis with Akaike's information criterion using the ADC histogram profiles with p values < 0.01 and age at diagnosis was used to identify independent variables for predicting the Mol-4 group. RESULTS: The 90th percentile (p < 0.001), median (p < 0.001), mean (p < 0.001), 10th percentile (p = 0.014), and entropy (p < 0.001) of normalized ADC were lower, and kurtosis (p < 0.001) and skewness (p = 0.046) were higher in the Mol-4 group than in the Mol-2/3 group. Multivariate logistic regression analysis revealed that the entropy of normalized ADC and age at diagnosis were independent predictive parameters for the Mol-4 group with an area under the curve of 0.92. CONCLUSION: ADC histogram profiles may be promising preoperative imaging biomarkers to predict molecular grade 4 among histologically lower-grade adult diffuse gliomas. CLINICAL RELEVANCE STATEMENT: This study highlighted the diagnostic usefulness of ADC histogram profiles to differentiate histologically lower grade adult diffuse gliomas with the presence of molecular grade 4 features and those without. KEY POINTS: • ADC histogram profiles to predict molecular CNS WHO grade 4 status among histologically lower-grade adult diffuse gliomas were evaluated. • Entropy of ADC and age were independent predictive parameters for molecular grade 4 status. • ADC histogram analysis is useful for predicting molecular grade 4 among histologically lower-grade gliomas.

Quality assessment of routine brain imaging at 0.55 T: initial experience in a clinical workflow.

The purpose of this study was to assess the quality of clinical brain imaging in healthy subjects and patients on an FDA-approved commercial 0.55 T MRI scanner, and to provide information about the feasibility of using this scanner in a clinical workflow. In this IRB-approved study, brain examinations on the scanner were prospectively performed in 10 healthy subjects (February-April 2022) and retrospectively derived from 44 patients (February-July 2022). Images collected using the following pulse sequences were available for assessment: axial DWI (diffusion-weighted imaging), apparent diffusion coefficient maps, 2D axial fluid-attenuated inversion recovery images, axial susceptibility-weighted images (both magnitude and phase), sagittal T1 -weighted (T1w) Sampling Perfection with Application Optimized Contrast images, sagittal T1w MPRAGE (magnetization prepared rapid gradient echo) with contrast enhancement, axial T1w turbo spin echo (TSE) with and without contrast enhancement, and axial T2 -weighted TSE. Two readers retrospectively and independently evaluated image quality and specific anatomical features in a blinded fashion on a four-point Likert scale, with a score of 1 being unacceptable and 4 being excellent, and determined the ability to answer the clinical question in patients. For each category of image sequences, the mean, standard deviation, and percentage of unacceptable quality images (<2) were calculated. Acceptable (rating ≥ 2) image quality was achieved at 0.55 T in all sequences for patients and 85% of the sequences for healthy subjects. Radiologists were able to answer the clinical question in all patients scanned. In total, 50% of the sequences used in patients and about 60% of the sequences used in healthy subjects exhibited good (rating ≥ 3) image quality. Based on these findings, we conclude that diagnostic quality clinical brain images can be successfully collected on this commercial 0.55 T scanner, indicating that the routine brain imaging protocol may be deployed on this system in the clinical workflow.

Performance of Neck Imaging Reporting and Data System (NI-RADS) for Diagnosis of Recurrence of Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-analysis.

BACKGROUND: The Neck Imaging Reporting and Data System (NI-RADS) is a reporting template used in head and neck cancer posttreatment follow-up imaging. PURPOSE: Our aim was to evaluate the pooled detection rates of the recurrence of head and neck squamous cell carcinoma based on each NI-RADS category and to compare the diagnostic accuracy between NI-RADS 2 and 3 cutoffs. DATA SOURCES: The MEDLINE, Scopus, and EMBASE databases were searched. STUDY SELECTION: This systematic review identified 7 studies with a total of 694 patients (1233 lesions) that were eligible for the meta-analysis. DATA ANALYSIS: The meta-analysis of pooled recurrence detection rate estimates for each NI-RADS category and the diagnostic accuracy of recurrence with NI-RADS 3 or 2 as the cutoff was performed. DATA SYNTHESIS: The estimated recurrence rates in each category for primary lesions were 74.4% for NI-RADS 3, 29.0% for NI-RADS 2, and 4.2% for NI-RADS 1. The estimated recurrence rates in each category for cervical lymph nodes were 73.3% for NI-RADS 3, 14.3% for NI-RADS 2, and 3.5% for NI-RADS 1. The area under the curve of the summary receiver operating characteristic for recurrence detection with NI-RADS 3 as the cutoff was 0.887 and 0.983, respectively, higher than 0.869 and 0.919 for the primary sites and cervical lymph nodes, respectively, with NI-RADS 2 as the cutoff. LIMITATIONS: Given the heterogeneity of the data of the studies, the conclusions should be interpreted with caution. CONCLUSIONS: This meta-analysis revealed estimated recurrence rates for each NI-RADS category for primary lesions and cervical lymph nodes and showed that NI-RADS 3 has a high diagnostic performance for detecting recurrence.

Dural and Leptomeningeal Diseases: Anatomy, Causes, and Neuroimaging Findings.

Meningeal lesions can be caused by various conditions and pose diagnostic challenges. The authors review the anatomy of the meninges in the brain and spinal cord to provide a better understanding of the localization and extension of these diseases and summarize the clinical and imaging features of various conditions that cause dural and/or leptomeningeal enhancing lesions. These conditions include infectious meningitis (bacterial, tuberculous, viral, and fungal), autoimmune diseases (vasculitis, connective tissue diseases, autoimmune meningoencephalitis, Vogt-Koyanagi-Harada disease, neuro-Behçet syndrome, Susac syndrome, and sarcoidosis), primary and secondary tumors (meningioma, diffuse leptomeningeal glioneuronal tumor, melanocytic tumors, and lymphoma), tumorlike diseases (histiocytosis and immunoglobulin G4-related diseases), medication-induced diseases (immune-related adverse effects and posterior reversible encephalopathy syndrome), and other conditions (spontaneous intracranial hypotension, amyloidosis, and moyamoya disease). Although meningeal lesions may manifest with nonspecific imaging findings, correct diagnosis is important because the treatment strategy varies among these diseases. ©RSNA, 2023 Online supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article. Quiz questions for this article are available through the Online Learning Center.

Dynamic contrast-enhanced MRI parameters and apparent diffusion coefficient as treatment response markers of skull base osteomyelitis: a preliminary study.

Purpose: Currently, there is no definitive consensus on the optimal imaging modality for determining the treatment response in patients with skull base osteomyelitis (SBO). This study aimed to investigate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and apparent diffusion coefficient (ADC) as treatment response markers of SBO. Material and methods: This study included 6 patients with SBO, who underwent both pre- and post-treatment DCE-MRI and diffusion-weighted imaging (DWI). Quantitative DCE-MRI parameters and ADC of the region-of-interest were analysed. These normalized parameters were calculated by dividing the region-of-interest by the reference region. The Wilcoxon signed rank test was used to compare these parameters between pre- and post-treatment periods. Results: The normalized fraction of the extravascular extracellular space (Ve) and ADC of the post-treatment status of SBO was significantly lower than those of pre-treatment measures (p = 0.03). The normalized fraction of blood plasma (Vp), normalized rate of transfer from the blood plasma into the extravascular extracellular space (Ktrans), and normalized backflow leakage of material from the extravascular extracellular space into the blood plasma (Kep) demonstrated no significant differences between pre- and post-treatment. Conclusions: DCE-MRI parameters Ve and ADC demonstrated a significant reduction when comparing measures across the pre- and post-treatment periods. These parameters may potentially serve as a valuable surrogate treatment response marker for SBO activity.

Performance of axial diameter on MR imaging for identification of retropharyngeal lymph node metastases in head and neck cancer: a systematic review and meta-analysis.

PURPOSE: To summarize previous studies' data and to calculate the diagnostic performance of minimum axial diameter (MIAD) and maximum axial diameter (MAAD) on each of the cutoff values in retropharyngeal lymph node (RPLNs) metastases in head and neck cancer. METHODS: MEDLINE, Scopus, and Embase databases were searched for systematic review. Meta-analysis was performed to summarize estimates of sensitivity, specificity, and diagnostic odds ratio (DOR) and generate summary recipient operator characteristic (sROC). RESULTS: The review identified 5 studies with a total of 634 patients (971 lesions) that were eligible for the meta-analysis. The estimated sensitivity, specificity, and DOR at MIAD 5 mm cutoff and MIAD 6 mm cutoff were 89.8% and 74.3%, 82.7% and 92.7%, and 39.1 and 57.9, respectively. The estimated sensitivity, specificity, and DOR at MAAD 7 mm cutoff and MAAD 8 mm cutoff were 90.3% and 84.7%, 62.7% and 79.9%, and 17.8 and 21.7, respectively. The AUCs of sROC at MIAD 5 mm cutoff and MIAD 6 mm cutoff were 0.922 and 0.943. At MAAD 7 mm and MAAD 8 mm, they were 0.840 and 0.888. CONCLUSION: The diagnostic performance of the MIAD 6 mm cutoff in RPLN metastases from head and neck cancer was 2% higher than the MIAD 5 mm cutoff. The diagnostic performance of MIAD was higher than that of MAAD.

Dynamic susceptibility contrast perfusion-weighted and diffusion-weighted magnetic resonance imaging findings in pilocytic astrocytoma and H3.3 and H3.1 variant diffuse midline glioma, H3K27-altered.

OBJECTIVE: This study compared the dynamic susceptibility contrast (DSC) magnetic resonance imaging parameters and apparent diffusion coefficient (ADC) between pilocytic astrocytoma (PA) and diffuse midline glioma, H3K27-altered (DMG) variants. METHODS: The normalized relative cerebral blood volume (nrCBV), normalized relative flow (nrCBF), percentile signal recovery (PSR), and normalized mean ADC (nADCmean) of 23 patients with midline PAs (median age, 13 years [range, 1-71 years]; 13 female patients) and 40 patients with DMG (8.5 years [1-35 years]; 19 female patients), including 35 patients with H3.3- and five patients with H3.1-mutant tumors, treated between January 2016 and May 2022 were statistically compared. RESULTS: DMG had a significantly lower nADCmean (median: 1.48 vs. 1.96; p = 0.00075) and lower PSR (0.97 vs. 1.23, p = 0.13) but higher nrCBV and nrCBF (1.66 vs. 1.17, p = 0.058, respectively, and 1.87 vs. 1.19, p = 0.028, respectively) than PA. The H3.3 variant had a lower nADCmean than the H3.1 variant (1.46 vs. 1.80, p = 0.10). CONCLUSION: DMG had lower ADC and PSR and higher rCBV and rCBF than PA. The H3.3 variant had a lower ADC than the H3.1 variant. Recognizing the differences and similarities in the DSC parameters and ADC between these tumors may help presurgical diagnosis.