FDG imaging with long-axial field-of-view PET/CT in patients with high blood glucose-a matched pair analysis.

PURPOSE: High blood glucose (hBG) in patients undergoing [18F]FDG PET/CT scans often results in rescheduling the examination, which may lead to clinical delay for the patient and decrease productivity for the department. The aim of this study was to evaluate whether long-axial field-of-view (LAFOV) PET/CT can minimize the effect of altered bio-distribution in hBG patients and is able to provide diagnostic image quality in hBG situations. MATERIALS AND METHODS: Oncologic patients with elevated blood glucose (≥ 8.0 mmol/l) and normal blood glucose (< 8.0 mmol/l, nBG) levels were matched for tumor entity, gender, age, and BMI. hBG patients were further subdivided into two groups (BG 8-11 mmol/l and BG > 11 mmol/l). Tracer uptake in the liver, muscle, and tumor was evaluated. Furthermore, image quality was compared between long acquisitions (ultra-high sensitivity mode, 360 s) on a LAFOV PET/CT and routine acquisitions equivalent to a short-axial field-of-view scanner (simulated (sSAFOV), obtained with high sensitivity mode, 120 s). Tumor-to-background ratio (TBR) and contrast-to-noise ratio (CNR) were used as the main image quality criteria. RESULTS: Thirty-one hBG patients met the inclusion criteria and were matched with 31 nBG patients. Overall, liver uptake was significantly higher in hBG patients (SUVmean, 3.07 ± 0.41 vs. 2.37 ± 0.33; p = 0.03), and brain uptake was significantly lower (SUVmax, 7.58 ± 0.74 vs. 13.38 ± 3.94; p < 0.001), whereas muscle (shoulder/gluteal) uptake showed no statistically significant difference. Tumor uptake was lower in hBG patients, resulting in a significantly lower TBR in the hBG cohort (3.48 ± 0.74 vs. 5.29 ± 1.48, p < 0.001). CNR was higher in nBG compared to hBG patients (12.17 ± 4.86 vs. 23.31 ± 12.22, p < 0.001). However, subgroup analysis of nBG 8-11 mmol/l on sSAFOV PET/CT compared to hBG (> 11 mmol/l) patients examined with LAFOV PET/CT showed no statistical significant difference in CNR (19.84 ± 8.40 vs. 17.79 ± 9.3, p = 0.08). CONCLUSION: While elevated blood glucose (> 11 mmol) negatively affected TBR and CNR in our cohort, the images from a LAFOV PET-scanner had comparable CNR to PET-images acquired from nBG patients using sSAFOV PET/CT. Therefore, we argue that oncologic patients with increased blood sugar levels might be imaged safely with LAFOV PET/CT when rescheduling is not feasible.

Long-axial field-of-view PET/CT for the assessment of inflammation in calcified coronary artery plaques with [68 Ga]Ga-DOTA-TOC.

PURPOSE: Inflamed, prone-to-rupture coronary plaques are an important cause of myocardial infarction and their early identification is crucial. Atherosclerotic plaques are characterized by overexpression of the type-2 somatostatin receptor (SST2) in activated macrophages. SST2 ligand imaging (e.g. with [68 Ga]Ga-DOTA-TOC) has shown promise in detecting and quantifying the inflammatory activity within atherosclerotic plaques. However, the sensitivity of standard axial field of view (SAFOV) PET scanners may be suboptimal for imaging coronary arteries. Long-axial field of view (LAFOV) PET/CT scanners may help overcome this limitation. We aim to assess the ability of [68 Ga]Ga-DOTA-TOC LAFOV-PET/CT in detecting calcified, SST2 overexpressing coronary artery plaques. METHODS: In this retrospective study, 108 oncological patients underwent [68 Ga]Ga-DOTA-TOC PET/CT on a LAFOV system. [68 Ga]Ga-DOTA-TOC uptake and calcifications in the coronary arteries were evaluated visually and semi-quantitatively. Data on patients' cardiac risk factors and coronary artery calcium score were also collected. Patients were followed up for 21.5 ± 3.4 months. RESULTS: A total of 66 patients (61.1%) presented with calcified coronary artery plaques. Of these, 32 patients had increased [68 Ga]Ga-DOTA-TOC uptake in at least one coronary vessel (TBR: 1.65 ± 0.53). Patients with single-vessel calcifications showed statistically significantly lower uptake (SUVmax 1.10 ± 0.28) compared to patients with two- (SUVmax 1.31 ± 0.29, p < 0.01) or three-vessel calcifications (SUVmax 1.24 ± 0.33, p < 0.01). There was a correlation between coronary artery calcium score (CACS) and [68 Ga]Ga-DOTA-TOC uptake, especially in the LAD (p = 0.02). Stroke and all-cause death occurred more frequently in patients with increased [68 Ga]Ga-DOTA-TOC uptake (15.63% vs. 0%; p:0.001 and 21.88% vs. 6.58%; p: 0.04, respectively) during the follow-up period. CONCLUSION: [68 Ga]Ga-DOTA-TOC as a marker for the macrophage activity can reveal unknown cases of inflamed calcified coronary artery plaques using a LAFOV PET system. [68 Ga]Ga-DOTA-TOC uptake increased with the degree of calcification and correlated with higher risk of stroke and all-cause death. [68 Ga]Ga-DOTA-TOC LAFOV PET/CT may be useful to assess patients' cardiovascular risk.

Ampullary Adenocarcinoma, Version 1.2023, NCCN Clinical Practice Guidelines in Oncology.

Ampullary cancers refer to tumors originating from the ampulla of Vater (the ampulla, the intraduodenal portion of the bile duct, and the intraduodenal portion of the pancreatic duct), while periampullary cancers may arise from locations encompassing the head of the pancreas, distal bile duct, duodenum, or ampulla of Vater. Ampullary cancers are rare gastrointestinal malignancies, and prognosis varies greatly based on factors such as patient age, TNM classification, differentiation grade, and treatment modality received. Systemic therapy is used in all stages of ampullary cancer, including neoadjuvant therapy, adjuvant therapy, and first-line or subsequent-line therapy for locally advanced, metastatic, and recurrent disease. Radiation therapy may be used in localized ampullary cancer, sometimes in combination with chemotherapy, but there is no high-level evidence to support its utility. Select tumors may be treated surgically. This article describes NCCN recommendations regarding management of ampullary adenocarcinoma.

Magnetic Resonance Imaging of the Lumbar Spine: Recommendations for Acquisition and Image Evaluation from the BACPAC Spine Imaging Working Group.

Management of patients suffering from low back pain (LBP) is challenging and requires development of diagnostic techniques to identify specific patient subgroups and phenotypes in order to customize treatment and predict clinical outcome. The Back Pain Consortium (BACPAC) Research Program Spine Imaging Working Group has developed standard operating procedures (SOPs) for spinal imaging protocols to be used in all BACPAC studies. These SOPs include procedures to conduct spinal imaging assessments with guidelines for standardizing the collection, reading/grading (using structured reporting with semi-quantitative evaluation using ordinal rating scales), and storage of images. This article presents the approach to image acquisition and evaluation recommended by the BACPAC Spine Imaging Working Group. While the approach is specific to BACPAC studies, it is general enough to be applied at other centers performing magnetic resonance imaging (MRI) acquisitions in patients with LBP. The herein presented SOPs are meant to improve understanding of pain mechanisms and facilitate patient phenotyping by codifying MRI-based methods that provide standardized, non-invasive assessments of spinal pathologies. Finally, these recommended procedures may facilitate the integration of better harmonized MRI data of the lumbar spine across studies and sites within and outside of BACPAC studies.

EXPLORing Arthritis with Total-body Positron Emission Tomography.

Arthritis has significant adverse consequences on musculoskeletal tissues and often other organs of the body. Current methods for clinical evaluation of arthritis are suboptimal, and biomarkers that are objective and measurable indicators for monitoring of arthritis disease activity are in critical demand. Recently, total-body positron emission tomography (PET) has been developed that can collect imaging signals synchronously from the entire body at ultra-low doses and reduced scan times. These scanners have increased signal collection efficiency that overcomes several limitations of standard PET scanners in the evaluation of arthritis, and they may potentially provide biomarkers to assess local and systemic impact of the arthritis disease process. This article reviews current results from using total-body PET in the assessment of common arthritic conditions, and it outlines future opportunities and challenges.

Natural History of Lung Hernias.

BACKGROUND: Lung herniation has been described in case reports or series. There are scare data in the form of original research studies to systematically evaluate this condition. OBJECTIVE: Our aim was to evaluate lung hernias with a focus on their natural history. METHODS: This is a retrospective study at our institution of patients who were found to have lung herniation on imaging between September 2010 and November 2022. Electronic medical record review was performed to extract clinical information regarding patients. Computed tomographic imaging was used to evaluate hernia size and size progression over time with a median follow-up time of 3.8 years. RESULTS: Thirty-eight patients were eligible for analysis. Majority of patients were overweight or obese (31/38), smokers (31/38), had prior thoracic surgery (30/38), and were asymptomatic (33/38). Twenty of 38 patients had stability in hernia size, 12 of 38 patients had hernia size progression, and 6 of 38 patients showed hernia size regression. Younger age was found to be predictive of hernia size progression with age of 60 years being the cut-off for its prediction. CONCLUSION: Lung hernias typically either remain stable in size or show size progression. Younger age (60 years cut-off) was found to be predictive of size progression. This is the largest systematic investigation at a medical institution to the best of our knowledge of lung hernias which used computed tomographic imaging to follow up lung hernias. Further information could be given to patients with this condition and to clinicians for potential management guidance.

18F-FDG gallbladder uptake: observation from a total-body PET/CT scanner.

BACKGROUND: Total-body positron emission tomography/computed tomography (PET/CT) scanners are characterized by higher signal collection efficiency and greater spatial resolution compared to conventional scanners, allowing for delayed imaging and improved image quality. These advantages may also lead to better detection of physiological processes that diagnostic imaging professionals should be aware of. The gallbladder (GB) is not usually visualized as an 18F-2-fluorodeoxyglucose (18F-FDG)-avid structure in routine clinical PET/CT studies; however, with the total-body PET/CT, we have been increasingly visualizing GB activity without it being involved in an inflammatory or neoplastic process. The aim of this study was to report visualization rates and characteristics of GB 18F-FDG uptake observed in both healthy and oncological subjects scanned on a total-body PET/CT system. MATERIALS AND METHODS: Scans from 73 participants (48 healthy and 25 with newly diagnosed lymphoma) who underwent 18F-FDG total-body PET/CT were retrospectively reviewed. Subjects were scanned at multiple timepoints up to 3 h post-injection. Gallbladder 18F-FDG activity was graded using liver uptake as a reference, and the pattern was qualified as present in the wall, lumen, or both. Participants' characteristics, such as age, sex, body-mass index, blood glucose, and other clinical parameters, were collected to assess for any significant correlation with GB 18F-FDG uptake. RESULTS: All 73 subjects showed GB uptake at one or more imaging timepoints. An increase in uptake intensity overtime was observed up until the 180-min scan, and the visualization rate of GB 18F-FDG uptake was 100% in the 120- and 180-min post-injection scans. GB wall uptake was detected in a significant number of patients (44/73, 60%), especially at early timepoint scans, whereas luminal activity was detected in 71/73 (97%) subjects, especially at later timepoint scans. No significant correlation was found between GB uptake intensity/pattern and subjects' characteristics. CONCLUSION: The consistent observation of GB 18F-FDG uptake recorded in this study in healthy participants and subjects with a new oncological diagnosis indicates that this is a normal physiologic finding rather than representing an exception.

AI-Based Automated Lipomatous Tumor Segmentation in MR Images: Ensemble Solution to Heterogeneous Data.

Deep learning (DL) has been proposed to automate image segmentation and provide accuracy, consistency, and efficiency. Accurate segmentation of lipomatous tumors (LTs) is critical for correct tumor radiomics analysis and localization. The major challenge of this task is data heterogeneity, including tumor morphological characteristics and multicenter scanning protocols. To mitigate the issue, we aimed to develop a DL-based Super Learner (SL) ensemble framework with different data correction and normalization methods. Pathologically proven LTs on pre-operative T1-weighted/proton-density MR images of 185 patients were manually segmented. The LTs were categorized by tumor locations as distal upper limb (DUL), distal lower limb (DLL), proximal upper limb (PUL), proximal lower limb (PLL), or Trunk (T) and grouped by 80%/9%/11% for training, validation and testing. Six configurations of correction/normalization were applied to data for fivefold-cross-validation trainings, resulting in 30 base learners (BLs). A SL was obtained from the BLs by optimizing SL weights. The performance was evaluated by dice-similarity-coefficient (DSC), sensitivity, specificity, and Hausdorff distance (HD95). For predictions of the BLs, the average DSC, sensitivity, and specificity from the testing data were 0.72 [Formula: see text] 0.16, 0.73 [Formula: see text] 0.168, and 0.99 [Formula: see text] 0.012, respectively, while for SL predictions were 0.80 [Formula: see text] 0.184, 0.78 [Formula: see text] 0.193, and 1.00 [Formula: see text] 0.010. The average HD95 of the BLs were 11.5 (DUL), 23.2 (DLL), 25.9 (PUL), 32.1 (PLL), and 47.9 (T) mm, whereas of SL were 1.7, 8.4, 15.9, 2.2, and 36.6 mm, respectively. The proposed method could improve the segmentation accuracy and mitigate the performance instability and data heterogeneity aiding the differential diagnosis of LTs in real clinical situations.

Pericardial computed tomography imaging findings in the setting of coccidioidomycosis.

BACKGROUND: Pericardial disease can be a manifestation of infection and imaging can have a role in its diagnosis. coccidioidomycosis endemic fungal infection has been more frequently reported over the past few decades. Other than case reports or series, there has been no systemic study evaluating pericardial imaging findings in patients with coccidioidomycosis to the best of our knowledge. The purpose of this study was to evaluate intrathoracic computed tomographic (CT) imaging abnormalities in patients with coccidioidal infection with specific emphasis on the pericardium. METHODS: Retrospective review of radiology reports and clinical chart review was performed to identify patients with coccidioidomycosis between January 2000 and September 2021 at our medical center. Diagnosis of infection was confirmed predominately with serology. Patients were excluded if a CT was not performed within 3 months of confirmed diagnosis date and if there was concomitant additional granulomatous or fungal infection. Chest CT was reviewed for pericardial and additional intrathoracic findings. RESULTS: The final retrospective cohort consisted of 37 patients. Imaging findings included lung nodules (N = 33/37), consolidation (N = 25/37), mediastinal or hilar lymphadenopathy (N = 20/37) and pleural effusions (N = 13/37). Eleven of 37 patients (30%) had either trace pericardial fluid (N = 3/37) or small pericardial effusions (N = 8/37). One patient had pericardial enhancement/thickening and history of pericardial tamponade. No other patient had clinical pericarditis or pericardial tamponade. Pericardial calcifications were not seen in any patient. Pericardial effusion was statistically associated with presence of pleural effusion as 9/13 patients with pleural effusion had pericardial effusion versus 2/26 patients without pleural effusion had pericardial effusion (p < 0.001). Otherwise patients with and without pericardial imaging findings were similar in terms of demographics, comorbidities and other imaging findings. CONCLUSION: Pulmonary parenchymal pathology is a common manifestation of coccidioidal infection. Most patients with coccidioidomycosis do not have pericardial imaging abnormalities on CT.

Marrow uptake on FDG PET/CT is associated with progression from smoldering to symptomatic multiple myeloma.

OBJECTIVE: To determine association of body composition measurements on CT and PET with progression of smoldering myeloma to multiple myeloma. METHODS: A retrospective cohort study in 65 patients with smoldering myeloma and PET/CT at diagnosis was performed at a tertiary cancer center. Subjects were between 38 and 87 years of age (mean 64) and included 37 males. Primary outcome was progression-free survival as a function of bone, fat, and muscle metrics on CT and PET (measured at the level of L4 pedicles) and clinical confounders. CT metrics included attenuation of L4 and retroperitoneal fat and various indices derived from the psoas muscle. PET measures included SUVmax and SUVmean of L4, retroperitoneal fat, and psoas. Cox proportional hazards modeling was performed with entry and retention criteria of p < 0.1 and p < 0.05, respectively. RESULTS: SUVmax and SUVmean were associated for each compartment (R2 = 0.78-0.84), and SUVmean (SUV) was used for subsequent analyses. SUV of the L4 vertebral body was associated with attenuation of the L4 vertebral body (p = 0.0032). There was no association between SUV and CT for muscle and fat compartments. In the subset of patients with bone marrow biopsy results (n = 43), there was no association between SUV of L4 and plasma cell concentration on core biopsy or flow cytometry (p = 0.089 and 0.072, respectively). The final Cox model showed association with albumin (HR 0.29, 95%CI 0.088-0.93, p = 0.038), M protein (HR 1.31, 95%CI 1.021-1.68, p = 0.034), and SUV of L4 (HR 1.99, 95%CI 1.037-3.82, p = 0.039). CONCLUSION: SUV of L4 is a prognostic indicator in patients with smoldering myeloma.

Development and Validation of a Multitask Deep Learning Model for Severity Grading of Hip Osteoarthritis Features on Radiographs.

Background A multitask deep learning model might be useful in large epidemiologic studies wherein detailed structural assessment of osteoarthritis still relies on expert radiologists' readings. The potential of such a model in clinical routine should be investigated. Purpose To develop a multitask deep learning model for grading radiographic hip osteoarthritis features on radiographs and compare its performance to that of attending-level radiologists. Materials and Methods This retrospective study analyzed hip joints seen on weight-bearing anterior-posterior pelvic radiographs from participants in the Osteoarthritis Initiative (OAI). Participants were recruited from February 2004 to May 2006 for baseline measurements, and follow-up was performed 48 months later. Femoral osteophytes (FOs), acetabular osteophytes (AOs), and joint-space narrowing (JSN) were graded as absent, mild, moderate, or severe according to the Osteoarthritis Research Society International atlas. Subchondral sclerosis and subchondral cysts were graded as present or absent. The participants were split at 80% (n = 3494), 10% (n = 437), and 10% (n = 437) by using split-sample validation into training, validation, and testing sets, respectively. The multitask neural network was based on DenseNet-161, a shared convolutional features extractor trained with multitask loss function. Model performance was evaluated in the internal test set from the OAI and in an external test set by using temporal and geographic validation consisting of routine clinical radiographs. Results A total of 4368 participants (mean age, 61.0 years ± 9.2 [standard deviation]; 2538 women) were evaluated (15 364 hip joints on 7738 weight-bearing anterior-posterior pelvic radiographs). The accuracy of the model for assessing these five features was 86.7% (1333 of 1538) for FOs, 69.9% (1075 of 1538) for AOs, 81.7% (1257 of 1538) for JSN, 95.8% (1473 of 1538) for subchondral sclerosis, and 97.6% (1501 of 1538) for subchondral cysts in the internal test set, and 82.7% (86 of 104) for FOS, 65.4% (68 of 104) for AOs, 80.8% (84 of 104) for JSN, 88.5% (92 of 104) for subchondral sclerosis, and 91.3% (95 of 104) for subchondral cysts in the external test set. Conclusion A multitask deep learning model is a feasible approach to reliably assess radiographic features of hip osteoarthritis. © RSNA, 2020 Online supplemental material is available for this article.

Qualitative evaluation of MRI features of lipoma and atypical lipomatous tumor: results from a multicenter study.

OBJECTIVES: The objectives of the study are (1) to distinguish lipoma (L) from atypical lipomatous tumor (ALT) using MRI qualitative features, (2) to assess the value of contrast enhancement, and (3) to evaluate the reproducibility and confidence level of radiological readings. MATERIALS AND METHODS: Patients with pathologically proven L or ALT, who underwent MRI within 3 months from surgical excision were included in this retrospective multicenter international study. Two radiologists independently reviewed MRI centrally. Impressions were recorded as L or ALT. A third radiologist was consulted for discordant readings. The two radiologists re-read all non-contrast sequences; impression was recorded; then post-contrast images were reviewed and any changes were recorded. RESULTS: A total of 246 patients (135 females; median age, 59 years) were included. ALT was histopathologically confirmed in 70/246 patients. In multivariable analysis, in addition to the lesion size, deep location, proximal lower limb lesions, demonstrating incomplete fat suppression, or increased architectural complexity were the independent predictive features of ALT; but not the contrast enhancement. Post-contrast MRI changed the impression in a total of 5 studies (3 for R1 and 4 for R2; 2 studies are common); all of them were incorrectly changed from Ls to ALTs. Overall, inter-reader kappa agreement was 0.42 (95% CI 0.39-0.56). Discordance between the two readers was statistically significant for both pathologically proven L (p < 0.001) and ALT (p = 0.003). CONCLUSION: Most qualitative MR imaging features can help distinguish ALTs from BLs. However, contrast enhancement may be limited and occasionally misleading. Substantial discordance on MRI readings exists between radiologists with a relatively high false positive and negative rates.

Beneficial Effects of Melatonin on Apolipoprotein-E Knockout Mice by Morphological and 18F-FDG PET/CT Assessments.

Atherosclerosis represents one of the main risk factors for the development of cardiovascular diseases. Their etiologies have been studied in recent years in order to better define therapeutic targets for intervention and to identify diagnostic methods. Two different subtypes of macrophages, M1 and M2, have been described in physiological conditions. They can also be found in the atherosclerotic process, where they both have opposite roles in disease progression. Perivascular brown adipose tissue is also involved in inflammation and endothelial damage. In this work, we provide insights into the protective role of melatonin in the atherosclerotic process by morphological and 18F-FDG-PET/CT analyses. In particular, we examined the effects of melatonin on pathways that are linked to atherosclerosis development. We showed that melatonin, by suppressing M1 activity, reduced inflammation and directed macrophage polarization toward the M2 macrophage subtype. Moreover, melatonin preserved the activity of perivascular brown adipose tissue. In addition, 18F-FDG uptake is very high in mice treated with melatonin, confirming that other factors may alter 18F-FDG distribution. In conclusion, we showed that melatonin affects inflammatory pathways that have been linked to atherosclerosis, assessed the relationships of the 18F-FDG PET/CT parameters with macrophage markers and the production of their cytokines, which that have been defined by morphological evaluations.

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain.

Purpose To develop and validate a deep learning algorithm that predicts the final diagnosis of Alzheimer disease (AD), mild cognitive impairment, or neither at fluorine 18 (18F) fluorodeoxyglucose (FDG) PET of the brain and compare its performance to that of radiologic readers. Materials and Methods Prospective 18F-FDG PET brain images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) (2109 imaging studies from 2005 to 2017, 1002 patients) and retrospective independent test set (40 imaging studies from 2006 to 2016, 40 patients) were collected. Final clinical diagnosis at follow-up was recorded. Convolutional neural network of InceptionV3 architecture was trained on 90% of ADNI data set and tested on the remaining 10%, as well as the independent test set, with performance compared to radiologic readers. Model was analyzed with sensitivity, specificity, receiver operating characteristic (ROC), saliency map, and t-distributed stochastic neighbor embedding. Results The algorithm achieved area under the ROC curve of 0.98 (95% confidence interval: 0.94, 1.00) when evaluated on predicting the final clinical diagnosis of AD in the independent test set (82% specificity at 100% sensitivity), an average of 75.8 months prior to the final diagnosis, which in ROC space outperformed reader performance (57% [four of seven] sensitivity, 91% [30 of 33] specificity; P < .05). Saliency map demonstrated attention to known areas of interest but with focus on the entire brain. Conclusion By using fluorine 18 fluorodeoxyglucose PET of the brain, a deep learning algorithm developed for early prediction of Alzheimer disease achieved 82% specificity at 100% sensitivity, an average of 75.8 months prior to the final diagnosis. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Larvie in this issue.

MRI and biomechanics multidimensional data analysis reveals R2 -R1ρ as an early predictor of cartilage lesion progression in knee osteoarthritis.

PURPOSE: To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and gait. While we can now acquire detailed information about the knee joint structure and function, we are not yet able to leverage the multifactorial factors for diagnosis and disease management of knee OA. MATERIALS AND METHODS: We mapped 178 subjects in a multidimensional space integrating: demographic, clinical information, gait kinematics and kinetics, cartilage compositional T1ρ and T2 and R2 -R1ρ (1/T2 -1/T1ρ ) acquired at 3T and whole-organ magnetic resonance imaging score morphological grading. Topological data analysis (TDA) and Kolmogorov-Smirnov test were adopted for data integration, analysis, and hypothesis generation. Regression models were used for hypothesis testing. RESULTS: The results of the TDA showed a network composed of three main patient subpopulations, thus potentially identifying new phenotypes. T2 and T1ρ values (T2 lateral femur P = 1.45*10-8 , T1ρ medial tibia P = 1.05*10-5 ), the presence of femoral cartilage defects (P = 0.0013), lesions in the meniscus body (P = 0.0035), and race (P = 2.44*10-4 ) were key markers in the subpopulation classification. Within one of the subpopulations we observed an association between the composite metric R2 -R1ρ and the longitudinal progression of cartilage lesions. CONCLUSION: The analysis presented demonstrates some of the complex multitissue biochemical and biomechanical interactions that define joint degeneration and OA using a multidimensional approach, and potentially indicates that R2 -R1ρ may be an imaging biomarker for early OA. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:78-90.

Cyclops lesions detected by MRI are frequent findings after ACL surgical reconstruction but do not impact clinical outcome over 2 years.

OBJECTIVES: To assess the impact of cyclops lesions with MRI in patients treated for anterior cruciate ligament (ACL) tears on clinical outcome. METHODS: In 113 patients (age 29.8 ± 10.5y; 55 females; BMI 24.8 ± 3.7 kg/m2) with complete ACL tear, 3 T-MRI scans were obtained before, 6-months, 1-year (n = 75) and 2-years (n = 33) after ACL reconstruction. Presence and volume of cyclops lesions were assessed. Clinical outcomes were measured using the Knee injury and Osteoarthritis Outcome Score (KOOS) and differences between time points (∆KOOS) were calculated. Changes of KOOS subscales were compared between patients with and without cyclops lesion. KOOS was also correlated with lesion volume. RESULTS: Cyclops lesions were found in 25% (28/113), 27% (20/75) and 33% (11/33) of patients after 6-months, 1- and 2-years, respectively. The lesion volume did not change significantly (P > 0.05) between time points, measuring 0.65 ± 0.59, 0.81 ± 0.70 and 0.72.9 ± 0.96 cm3, respectively. Clinical outcomes based on KOOS subscales were not significantly different in patients with cyclops lesions compared to those without cyclops lesions (each comparison P > 0.05), and no significant associations of clinical outcomes with lesion volume were found (P > 0.05). CONCLUSIONS: Neither presence nor size of cyclops lesions within the first 2-years after ACL surgery were associated with inferior clinical outcome. KEY POINTS: • Cyclops lesions had a prevalence of 25% in patients after ACL reconstruction. • Subjects with cyclops lesions did not have an inferior clinical outcome. • Cyclops lesions developed within the first 6 months after surgery. • The size of cyclops lesions did not significantly change over a period of 2 years.

Sporadic Inclusion Body Myositis: MRI Findings and Correlation With Clinical and Functional Parameters.

OBJECTIVE: The purpose of this prospective study is to assess MRI findings in patients with sporadic inclusion body myositis (IBM) and correlate them with clinical and functional parameters. SUBJECTS AND METHODS: This study included 12 patients with biopsy-proven sporadic IBM. All patients underwent MRI of the bilateral upper and lower extremities. The images were scored for muscle atrophy, fatty infiltration, and edema pattern. Clinical data included onset and duration of disease. Muscle strength was measured using the Medical Research Council (MRC) scale, and functional status was assessed using the Modified Rankin Scale. Correlation between MRI and different clinical and functional parameters was calculated using the Spearman rank test and Pearson correlation. RESULTS: All patients showed MRI abnormalities, which were more severe within the lower limbs and the distal segments. The most prevalent MRI finding was fat infiltration. There was a statistically significant correlation between disease duration and number of muscles infiltrated by fat (r = 0.65; p = 0.04). The number of muscles with fat infiltration correlated with the sum of the scores of MRC (r = -0.60; p = 0.04) and with the Modified Rankin Scale (r = 0.48; p = 0.03). CONCLUSION: Our findings suggest that most patients with biopsy-proven sporadic IBM present with a typical pattern of muscle involvement at MRI, more extensively in the lower extremities. Moreover, MRI findings strongly correlated with clinical and functional parameters, because both the extent and severity of muscle involvement assessed by MRI and clinical and functional parameters are associated with the early onset of the disease and its duration.

MR T1ρ and T2 of meniscus after acute anterior cruciate ligament injuries.

OBJECTIVE: To evaluate differences in meniscal T1ρ and T2 quantification in patients with acute anterior cruciate ligament (ACL) injuries and to determine correlations of these differences with MR morphological grading and patient-reported outcomes. DESIGN: Bilateral knees of 52 patients with acute ACL injury and 20 healthy controls were scanned using 3 T magnetic resonance imaging (MRI) T1ρ and T2 mapping in this prospective study. Quantitative analysis of the meniscus was performed in anterior and posterior horns of the lateral and medial menisci. Morphological meniscal damage was assessed using modified whole-organ MRI scores (WORMS). Measurements were compared between injured, uninjured contralateral, and control knees using a mixed-effects regression model. Correlations between meniscal T1ρ/T2, WORMS and Knee Injury and Osteoarthritis Outcome Scores (KOOS) were examined using partial correlation analysis. RESULTS: Mean meniscal T1ρ and T2 values were significantly higher in ACL-injured knees compared to control and contralateral knees. Menisci of ACL-injured knees without tears, including those limited to modified meniscal WORMS grade 0, also had significantly higher T1ρ and T2 values compared to menisci of uninjured knees. Within ACL-injured knees, T1ρ and T2 values showed significant positive associations with meniscal WORMS and significant negative associations with KOOS. CONCLUSION: Acute ACL injuries are associated with significantly increased meniscal T1ρ and T2 values in both patients with and without meniscal lesions or tears, suggesting quantitative MRI provides more sensitive measures of meniscal differences compared to traditional morphological MRI sequences. Correlation between meniscal T1ρ/T2 and KOOS suggest that quantitative MRI is reflective of the extent of patients' clinical symptoms.

Quantitative assessment of morphology, T1ρ, and T2 of shoulder cartilage using MRI.

OBJECTIVES: The aim of this study was to assess the feasibility of quantifying shoulder cartilage morphology and relaxometry in a clinically feasible scan time comparing different pulse sequences and assessing their reproducibility at 3 Tesla. METHODS: Three pulse sequences were compared for morphological assessments of shoulder cartilage thickness and volume (SPGR, MERGE, FIESTA), while a combined T1ρ-T2 sequence was optimized for relaxometry measurements. The shoulders of six healthy subjects were scanned twice with repositioning, and the cartilage was segmented and quantified. The degree of agreement between the three morphological sequences was assessed using Bland-Altman plots, while the morphological and relaxometry reproducibility were assessed with root-mean-square coefficients of variation (RMS-CVs) RESULTS: Bland-Altman plots indicated good levels of agreement between the morphological assessments of the three sequences. The reproducibility of morphological assessments yielded RMS-CVs between 4.0 and 17.7 %. All sequences correlated highly (R > 0.9) for morphologic assessments with no statistically significant differences. For relaxometry assessments of humeral cartilage, RMS-CVs of 6.4 and 10.6 % were found for T1ρ and T2, respectively. CONCLUSIONS: The assessment of both cartilage morphology and relaxometry is feasible in the shoulder with SPGR, humeral head, and T1ρ being the more reproducible morphological sequence, anatomic region, and quantitative sequence, respectively. KEY POINTS: • The thin cartilage morphology can be assessed in the shoulder in vivo. • Non-invasive biochemical assessment of shoulder cartilage is feasible in vivo using MRI.