Corrigendum to "Erdheim-Chester disease with tendon and muscle involvement: Reports of a rare presentation" [Radiology Case Reports 19 (2024) 1866-1871].

[This corrects the article DOI: 10.1016/j.radcr.2024.02.009.].

Erdheim-Chester disease with tendon and muscle involvement: Reports of a rare presentation.

Erdheim-Chester disease (ECD) is a rare histiocytic disease that affects multiple systems in the body. While it typically targets long bones, cardiovascular structures, the retroperitoneum, and the central nervous system, reports of tendon and skeletal muscle involvement are scarce. This review presents 2 cases: a case of ECD involving the left Achilles tendon and left abductor hallucis, as well as an unusual manifestation of ECD in the thigh musculature. In Case 1, studies involved a 39-year-old man who initially presented with bone and pituitary involvement. An order for 18F-FDG PET/CT imaging was placed by marked swelling in the patient's left ankle and observed soft tissue fullness on foot radiographs, which revealed a soft tissue mass involving the left Achilles tendon, which arose along the tendon-muscle junction and involved the left abductor hallucis muscle. In Case 2, studies involved a 41-year-old man who initially presented with involvement of the cardiovascular system and retroperitoneum. 18F-FDG PET/CT scan showed an infiltrative right atrial mass and hypermetabolic lesion in the left external obturator muscle, extending to the left pectineus and right quadratus femoris muscle. Involvement of the Achilles tendon and skeletal muscle involvement, including left abductor hallucis muscle and medial thigh muscles, is one of the rare manifestations of ECD. Diagnostic delays were frequent due to the condition's rarity and nonspecific multisystemic symptoms. This should be considered in patients who present with myositis, tendinopathy, and bone pain and have other unexplained multisystemic problems.

Magnetic resonance imaging in the evaluation and management of acute pancreatitis: a review of current practices and future directions.

Acute pancreatitis is a condition marked by inflammation of the pancreas and surrounding tissues. While the majority of cases of acute pancreatitis are mild, a minority of severe cases are the primary contributors to the morbidity and mortality attributed to this condition. Retroperitoneal morphologic changes can be detected by utilization of various imaging modalities, and their accurate evaluation is crucial for effective management. Acute pancreatitis is commonly diagnosed using computed tomography (CT). However, there are certain clinical scenarios where magnetic resonance imaging (MRI) may have superiority over CT. In particular, MRI is useful in cases where patients cannot receive iodinated CT contrast, or where there is a need to investigate the underlying cause of acute pancreatitis. Additionally, MRI can be utilized to evaluate ductal disconnection and guide interventions for necrotic collections. The unique features of MRI can be particularly useful, including its ability to provide superior contrast resolution and to offer greater functional information through techniques such as diffusion-weighted imaging. The aim of this review is to discuss the MRI assessment of individuals with acute pancreatitis. Additionally, the recent advances in MRI for evaluation of acute pancreatitis will also be introduced.

Skeletal involvement in Erdheim-Chester disease: Multimodality imaging features and association with the BRAFV600E mutation.

OBJECTIVE: The aim of this study was to characterize the distribution of skeletal involvement in Erdheim-Chester disease (ECD) by using radiography, computed tomography (CT), 18F-FDG positron emission tomography/computed tomography (PET/CT), and bone scans, as well as looking for associations with the BRAFV600E mutation. MATERIAL AND METHODS: Prospective study of 50 consecutive patients with biopsy-confirmed ECD who had radiographs, CT, 18F-FDG PET/CT, and Tc-99m MDP bone scans. At least two experienced radiologists with expertise in the relevant imaging studies analyzed the images. Summary statistics were expressed as the frequency with percentages for categorical data. Fisher's exact test, as well as odds ratios (OR) with 95 % confidence intervals (CI), were used to link imaging findings to BRAFV600E mutation. The probability for co-occurrence of bone involvement at different locations was calculated and graphed as a heat map. RESULTS: All 50 cases revealed skeletal involvement at different regions of the skeleton. The BRAFV600E mutation, which was found in 24 patients, was correlated with femoral and tibial involvement on 18F-FDG PET/CT and bone scan. The appearance of changes on the femoral, tibial, fibular, and humeral involvement showed correlation with each other based on heat maps of skeletal involvement on CT. CONCLUSION: This study reports the distribution of skeletal involvement in a cohort of patients with ECD. CT is able to detect the majority of ECD skeletal involvement. Considering the complementary nature of information from different modalities, imaging of ECD skeletal involvement is optimized by using a multi-modality strategy.

Virtual monoenergetic imaging in photon-counting CT of the head and neck.

PURPOSE: Advantages of virtual monoenergetic images (VMI) have been reported for dual energy CT of the head and neck, and more recently VMIs derived from photon-counting (PCCT) angiography of the head and neck. We report image quality metrics of VMI in a PCCT angiography dataset, expanding the anatomical regions evaluated and extending observer-based qualitative methods further than previously reported. METHODS: In a prospective study, asymptomatic subjects underwent contrast enhanced PCCT of the head and neck using an investigational scanner. Image sets of low, high, and full spectrum (Threshold-1) energies; linear mix of low and high energies (Mix); and 23 VMIs (40-150 keV, 5 keV increments) were generated. In 8 anatomical locations, SNR and radiologists' preferences for VMI energy levels were measured using a forced-choice rank method (4 observers) and ratings of image quality using visual grading characteristic (VGC) analysis (2 observers) comparing VMI to Mix and Threshold-1 images. RESULTS: Fifteen subjects were included (7 men, 8 women, mean 57 years, range 46-75). Among all VMIs, SNRs varied by anatomic location. The highest SNRs were observed in VMIs. Radiologists preferred 50-60 keV VMIs for vascular structures and 75-85 keV for all other structures. Cumulative ratings of image quality averaged across all locations were higher for VMIs with areas under the curve of VMI vs Mix and VMI vs Threshold-1 of 0.67 and 0.68 for the first reader and 0.72 and 0.76 for the second, respectively. CONCLUSION: Preferred keV level and quality ratings of VMI compared to mixed and Threshold-1 images varied by anatomical location.

Impact of the confluence of cardiac motion and high spatial resolution on performance of ECG-gated imaging with an investigational photon-counting CT system: A phantom study.

PURPOSE: Photon-counting CT (PCCT) has higher spatial resolution that conventional EID CT which improves imaging of stationary coronary plaques and stents.. In this work, we evaluated the relationship between higher spatial resolution and motion acquisition on an investigational PCCT system. METHODS: An investigational photon-counting CT scanner (Siemens CounT) with ECG gating was used to image a coronary tree phantom with models of healthy, stenotic, and stented arteries using a motion simulator. Images were acquired with matched clinical parameters at rest and 60 beats per minute. An additional set of high dose stationary images were averaged to generate a motion-free, reduced noise reference. Scans were completed at standard (0.5 mm2) and high-resolution (0.25 mm2). Motion images were reconstructed at multiple phases. Regions of interest were drawn around vessels and segmented. Percentage difference from the reference standard was evaluated for vessel diameter and circularity. Mutual information between the reference and stationary and motion datasets was used as a measure of volumetric similarity. RESULTS: The stenotic vessel showed the most variation from the reference when compared to healthy or stented vessels. Compared to standard resolution, high-resolution images had lower bias for diameter (-0.012 ± 0.19% vs -0.052 ± 0.14%) and lower variability for circularity (-0.13 ± 0.138% vs -0.12 ± 0.144%). Both differences were found to be statistically significant. High-resolution images had a slightly lower mutual information (1.28) than standard resolution (1.31). CONCLUSION: The higher spatial resolution enabled by photon-counting CT can be harnessed for cardiac imaging as the benefits of high spatial resolution acquisitions remain relevant in the presence of motion.

Role of Artificial Intelligence in PET/CT Imaging for Management of Lymphoma.

Our review shows that AI-based analysis of lymphoma whole-body FDG-PET/CT can inform all phases of clinical management including staging, prognostication, treatment planning, and treatment response evaluation. We highlight advancements in the role of neural networks for performing automated image segmentation to calculate PET-based imaging biomarkers such as the total metabolic tumor volume (TMTV). AI-based image segmentation methods are at levels where they can be semi-automatically implemented with minimal human inputs and nearing the level of a second-opinion radiologist. Advances in automated segmentation methods are particularly apparent in the discrimination of lymphomatous vs non-lymphomatous FDG-avid regions, which carries through to automated staging. Automated TMTV calculators, in addition to automated calculation of measures such as Dmax are informing robust models of progression-free survival which can then feed into improved treatment planning.

Multi-Scale Temporal Imaging: From Micro- and Meso- to Macro-scale-time Nuclear Medicine.

Time provides a common frame of reference for understanding different processes of change. Within the context of medical imaging, time has three different time scales to be considered: (i) microtime, (ii) mesotime, and (iii) macrotime, respectively, which span a single imaging session, distinct imaging sessions within a short period, and scans with large time gaps spanning months of even years. There has commonly been greater emphasis on the microtime and mesotime scales in both clinical practice and research, with less focus on questions that are at the macrotime scale.

Artificial Intelligence in Medical Imaging and its Impact on the Rare Disease Community: Threats, Challenges and Opportunities.

Almost 1 in 10 individuals can suffer from one of many rare diseases (RDs). The average time to diagnosis for an RD patient is as high as 7 years. Artificial intelligence (AI)-based positron emission tomography (PET), if implemented appropriately, has tremendous potential to advance the diagnosis of RDs. Patient advocacy groups must be active stakeholders in the AI ecosystem if we are to avoid potential issues related to the implementation of AI into health care. AI medical devices must not only be RD-aware at each stage of their conceptualization and life cycle but also should be trained on diverse and augmented datasets representative of the end-user population including RDs. Inability to do so leads to potential harm and unsustainable deployment of AI-based medical devices (AIMDs) into clinical practice.

Evaluation of Coronary Plaques and Stents with Conventional and Photon-counting CT: Benefits of High-Resolution Photon-counting CT.

PURPOSE: To compare the performance of energy-integrating detector (EID) CT, photon-counting detector CT (PCCT), and high-resolution PCCT (HR-PCCT) for the visualization of coronary plaques and reduction of stent artifacts in a phantom model. MATERIALS AND METHODS: An investigational scanner with EID and PCCT subsystems was used to image a coronary artery phantom containing cylindrical probes simulating different plaque compositions. The phantom was imaged with and without coronary stents using both subsystems. Images were reconstructed with a clinical cardiac kernel and an additional HR-PCCT kernel. Regions of interest were drawn around probes and evaluated for in-plane diameter and a qualitative comparison by expert readers. A linear mixed-effects model was used to compare the diameter results, and a Shrout-Fleiss intraclass correlation coefficient was used to assess consistency in the reader study. RESULTS: Comparing in-plane diameter to the physical dimension for nonstented and stented phantoms, measurements of the HR-PCCT images were more accurate (nonstented: 4.4% ± 1.1 [standard deviation], stented: -9.4% ± 4.6) than EID (nonstented: 15.5% ± 4.0, stented: -19.5% ± 5.8) and PCCT (nonstented: 19.4% ± 2.5, stented: -18.3% ± 4.4). Our analysis of variance found diameter measurements to be different across image groups for both nonstented and stented cases (P < .001). HR-PCCT showed less change on average in percent stenosis due to the addition of a stent (-5.5%) than either EID (+90.5%) or PCCT (+313%). For both nonstented and stented phantoms, observers rated the HR-PCCT images as having higher plaque conspicuity and as being the image type that was least impacted by stent artifacts, with a high level of agreement (interclass correlation coefficient = 0.85). CONCLUSION: Despite increased noise, HR-PCCT images were able to better visualize coronary plaques and reduce stent artifacts compared with EID or PCCT reconstructions.Keywords: CT-Spectral Imaging (Dual Energy), Phantom Studies, Cardiac, Physics, Technology Assessment© RSNA, 2021.

A deep-learning based artificial intelligence (AI) approach for differentiation of clear cell renal cell carcinoma from oncocytoma on multi-phasic MRI.

PURPOSE: To investigate the diagnostic performance of a deep convolutional neural network for differentiation of clear cell renal cell carcinoma (ccRCC) from renal oncocytoma. METHODS: In this retrospective study, 74 patients (49 male, mean age 59.3) with 243 renal masses (203 ccRCC and 40 oncocytoma) that had undergone MR imaging 6 months prior to pathologic confirmation of the lesions were included. Segmentation using seed placement and bounding box selection was used to extract the lesion patches from T2-WI, and T1-WI pre-contrast, post-contrast arterial and venous phases. Then, a deep convolutional neural network (AlexNet) was fine-tuned to distinguish the ccRCC from oncocytoma. Five-fold cross validation was used to evaluate the AI algorithm performance. A subset of 80 lesions (40 ccRCC, 40 oncocytoma) were randomly selected to be classified by two radiologists and their performance was compared to the AI algorithm. Intra-class correlation coefficient was calculated using the Shrout-Fleiss method. RESULTS: Overall accuracy of the AI system was 91% for differentiation of ccRCC from oncocytoma with an area under the curve of 0.9. For the observer study on 80 randomly selected lesions, there was moderate agreement between the two radiologists and AI algorithm. In the comparison sub-dataset, classification accuracies were 81%, 78%, and 70% for AI, radiologist 1, and radiologist 2, respectively. CONCLUSION: The developed AI system in this study showed high diagnostic performance in differentiation of ccRCC versus oncocytoma on multi-phasic MRIs.

18Fluorodeoxyglucose-positron emission tomography/computed tomography for differentiation of renal tumors in hereditary kidney cancer syndromes.

PURPOSE: To assess differences in FDG-PET/CT uptake among four subtypes of renal tumors: clear cell RCC (ccRCC), papillary type I and II RCC (pRCC), and oncocytoma. METHODS: This retrospective study investigated 33 patients with 98 hereditary renal tumors. Lesions greater than 1 cm and patients with a timeframe of less than 18 months between preoperative imaging and surgery were considered. FDG-PET/CT images were independently reviewed by two nuclear medicine physicians, blinded to clinical information. Volumetric lesion SUVmean was measured and used to calculate a target-to-background ratio respective to liver (TBR). The Shrout-Fleiss intra-class correlation coefficient was used to assess reliability between readers. A linear mixed effects model, accounting for within-patient correlations, was used to compare TBR values of primary renal lesions with and without distant metastasis. RESULTS: The time interval between imaging and surgery for all tumors had a median of 77 (Mean: 139; Range: 1-512) days. Intra-class reliability of mean TBR resulted in a mean κ score of 0.93, indicating strong agreement between the readers. The mixed model showed a significant difference in mean TBR among the subtypes (p < 0.0001). Pairwise comparison showed significant differences between pRCC type II and ccRCC (p < 0.0001), pRCC type II and pRCC type I (p = 0.0001), and pRCC type II and oncocytoma (p = 0.0016). Furthermore, a significant difference in FDG uptake was present between primary pRCC type II renal lesions with and without distant metastasis (p = 0.023). CONCLUSION: pRCC type II lesions demonstrated significantly higher FDG activity than ccRCC, pRCC type I, or oncocytoma. These findings indicate that FDG may prove useful in studying the metabolic activity of renal neoplasms, identifying lesions of highest clinical concern, and ultimately optimizing active surveillance, and personalizing management plans.

Review of Technical Advancements and Clinical Applications of Photon-counting Computed Tomography in Imaging of the Thorax.

Photon-counting computed tomography (CT) is a developing technology that has the potential to address some limitations of CT imaging and bring about improvements and potentially new applications to this field. Photon-counting detectors have a fundamentally different detection mechanism from conventional CT energy-integrating detectors that can improve dose efficiency, spatial resolution, and energy-discrimination capabilities. In the past decade, promising human studies have been reported in the literature that have demonstrated benefits of this relatively new technology for various clinical applications. In this review, we provide a succinct description of the photon-counting detector technology and its detection mechanism in comparison with energy-integrating detectors in a manner understandable for clinicians and radiologists, introduce benefits and some of the existing challenges present in this technology, and provide an overview of the current status and potential clinical applications of this technology in imaging of the thorax by providing example images acquired with an investigational whole-body photon-counting CT scanner.

Reinventing Molecular Imaging with Total-Body PET, Part II: Clinical Applications.

Total-body PET scans will initiate a new era for the PET clinic. The benefits of 40-fold effective sensitivity improvement provide new capabilities to image with lower radiation dose, perform delayed imaging, and achieve improved temporal resolution. These technical features are detailed in the first of this 2-part series. In this part, the clinical impacts of the novel features of total-body PET scans are further explored. Applications of total-body PET scans focus on the real-time interrogation of systemic disease manifestations in a variety of practical clinical contexts. Total-body PET scans make clinical systems biology imaging a reality.