OBJECTIVE: Simultaneous positron emission tomography/magnetic resonance imaging (PET-MRI) combines the high sensitivity of PET with the high specificity of MRI and is a tool for the assessment of gastroenteropancreatic neuroendocrine neoplasms (G-NENs). However, it remains poorly evaluated with no clear recommendations in current guidelines. Thus, we evaluated the prognostic impact of PET-MRI in G-NEN patients.
METHODS: From June 2017 to December 2021, 71 G-NEN patients underwent whole-body PET-MRI for staging and/or follow-up purposes. A whole-body emission scan with 18F-6-fluoro-L-dihydroxyphenylalanine (18FDOPA, n = 30), 18F-fluoro-2-deoxy-D-glucose (18FDG, n = 21), or 68Ga-(DOTA(0)-Phe(1)-Tyr(3))-octreotide (68Ga-DOTATOC, n = 20) with the simultaneous acquisition of a T1-Dixon sequence and diffusion-weighed imaging (DWI), followed by a dedicated step of MRI sequences with a Gadolinium contrast was performed. The patients underwent PET-MRI every 6-12 months during the follow-up period until death. Over this period, 50 patients with two or more PET-MRI were evaluated.
RESULTS: The mean age was 61 [extremes, 31-92] years. At the baseline, PET-MRI provided new information in 12 cases (17%) as compared to conventional imaging: there were more metastases in eight, an undescribed location (myocardia) in two, and an unknown primary location in two cases. G grading at the baseline influenced overall survival. During the follow-up (7-381 months, mean 194), clinical and therapy managements were influenced by PET-MRI in three (6%) patients due to new metastases findings when neither overall, nor disease-free survivals in these two subgroups (n = 12 vs. n = 59), were different.
CONCLUSIONS: Our study suggests that using PET/MRI with the appropriate radiotracer improves the diagnostic performance with no benefit on survival. Further studies are warranted to evaluate the cost-effectiveness of this procedure.

Neurocutaneous melanocytosis (NCM) is a rare, sporadic neuroectodermal dysplasia characterized by the presence of large or multiple congenital cutaneous nevi and melanocytic deposits in the central nervous system. Hitherto, unreported we describe a case of NCM with optic neuropathy and spinal cord melanoma from India. A 20 year-old-lady had headache and vomiting for 3 months followed by consecutive profound painless visual impairment. Visual acuity was counting of fingers at 1 m distance in both eyes with normal fundus. There were no symptoms of spinal cord involvement. Clinical examination showed multiple small to large melanocytic nevi over the face and body. Muscle power was normal. Tendon reflexes were exaggerated. Visual evoked potential showed bilateral prolonged P100 latency (Right eye - 144 msec; Left eye - 151 msec). Brain MRI revealed leptomeningeal enhancement of brainstem, cerebellum, oculomotor and facial-abducent nerve complex without optic nerve involvement. MRI spine showed extensive dorsal thoracic cord epidural lesion extending along the entire thoracic cord segment with dorsal cord compression. Positron Emission Tomography (PET) imaging showed Fludeoxyglucose F18 (FDG) avidity along D1-D12 levels of spinal cord. Biopsy from the cord lesion was suggestive of meningeal melanoma. Here we document a rare case of late onset NCM with intracranial meningeal infiltration and asymptomatic large epidural lesion of spinal cord, expanding its phenotypic spectrum. Optic neuropathy in NCM has not been reported earlier. Periodic screening of brain and spine is recommended for early prognostication and lesion identification in NCM.

Accurate differentiation of benign and malignant cervical lymph nodes is important for prognosis and treatment planning in patients with head and neck squamous cell carcinoma. We evaluated the diagnostic performance of magnetic resonance image (MRI) texture analysis and traditional 18F-deoxyglucose positron emission tomography (FDG-PET) features. This retrospective study included 21 patients with head and neck squamous cell carcinoma. We used texture analysis of MRI and FDG-PET features to evaluate 109 histologically confirmed cervical lymph nodes (41 metastatic, 68 benign). Predictive models were evaluated using area under the curve (AUC). Significant differences were observed between benign and malignant cervical lymph nodes for 36 of 41 texture features (p < 0.05). A combination of 22 MRI texture features discriminated benign and malignant nodal disease with AUC, sensitivity, and specificity of 0.952, 92.7%, and 86.7%, which was comparable to maximum short-axis diameter, lymph node morphology, and maximum standard uptake value (SUVmax). The addition of MRI texture features to traditional FDG-PET features differentiated these groups with the greatest AUC, sensitivity, and specificity (0.989, 97.5%, and 94.1%). The addition of the MRI texture feature to lymph node morphology improved nodal assessment specificity from 70.6% to 88.2% among FDG-PET indeterminate lymph nodes. Texture features are useful for differentiating benign and malignant cervical lymph nodes in patients with head and neck squamous cell carcinoma. Lymph node morphology and SUVmax remain accurate tools. Specificity is improved by the addition of MRI texture features among FDG-PET indeterminate lymph nodes. This approach is useful for differentiating benign and malignant cervical lymph nodes.

BACKGROUND: The aim of this study is to explore the utility of cardiac magnetic resonance (CMR) imaging of radiomic features to distinguish active and inactive cardiac sarcoidosis (CS).
METHODS: Subjects were classified into active cardiac sarcoidosis (CSactive) and inactive cardiac sarcoidosis (CSinactive) based on PET-CMR imaging. CSactive was classified as featuring patchy [18F]fluorodeoxyglucose ([18F]FDG) uptake on PET and presence of late gadolinium enhancement (LGE) on CMR, while CSinactive was classified as featuring no [18F]FDG uptake in the presence of LGE on CMR. Among those screened, thirty CSactive and thirty-one CSinactive patients met these criteria. A total of 94 radiomic features were subsequently extracted using PyRadiomics. The values of individual features were compared between CSactive and CSinactive using the Mann-Whitney U test. Subsequently, machine learning (ML) approaches were tested. ML was applied to two sub-sets of radiomic features (signatures A and B) that were selected by logistic regression and PCA, respectively.
RESULTS: Univariate analysis of individual features showed no significant differences. Of all features, gray level co-occurrence matrix (GLCM) joint entropy had a good area under the curve (AUC) and accuracy with the smallest confidence interval, suggesting it may be a good target for further investigation. Some ML classifiers achieved reasonable discrimination between CSactive and CSinactive patients. With signature A, support vector machine and k-neighbors showed good performance with AUC (0.77 and 0.73) and accuracy (0.67 and 0.72), respectively. With signature B, decision tree demonstrated AUC and accuracy around 0.7; Conclusion: CMR radiomic analysis in CS provides promising results to distinguish patients with active and inactive disease.

Reperfusion therapies in acute ischemic stroke have demonstrated their efficacy in promoting clinical recovery. However, ischemia/reperfusion injury and related inflammation remain a major challenge in patient clinical management. We evaluated the spatio-temporal evolution of inflammation using sequential clinical [11C]PK11195 PET-MRI in a non-human primate (NHP) stroke model mimicking endovascular thrombectomy (EVT) with a neuroprotective cyclosporine A (CsA) treatment. The NHP underwent a 110-min transient endovascular middle cerebral artery occlusion. We acquired [11C]PK11195 dynamic PET-MR imaging at baseline, 7 and 30 days after intervention. Individual voxel-wise analysis was performed thanks to a baseline scan database. We quantified [11C]PK11195 in anatomical regions and in lesioned areas defined on per-occlusion MR diffusion-weighted imaging and perfusion [15O2]H2OPET imaging. [11C]PK11195 parametric maps showed a clear uptake overlapping the lesion core at D7, which further increased at D30. Voxel-wise analysis identified individuals with significant inflammation at D30, with voxels located within the most severe diffusion reduction area during occlusion, mainly in the putamen. The quantitative analysis revealed that thalamic inflammation lasted until D30 and was significantly reduced in the CsA-treated group compared to the placebo. In conclusion, we showed that chronic inflammation matched ADC decrease at occlusion time, a region exposed to an initial burst of damage-associated molecular patterns, in an NHP stroke model mimicking EVT. We described secondary thalamic inflammation and the protective effect of CsA in this region. We propose that major ADC drop in the putamen during occlusion may identify individuals who could benefit from early personalized treatment targeting inflammation.

The recent introduction of integrated PET-MRI systems into practice seems promising in oncologic imaging, and efforts are made to specify their added values. The current study evaluates the added values of PET-MRI over PET-CT in detecting active malignant hepatic lesions.
As part of an ongoing prospective study in our institution that assesses the added values of PET-MRI, subjects undergo PET-CT and subsequent PET-MRI after single radiotracer injection. The current study included 97 pairs of whole-body PET-CT and liver PET-MRI scans, of 61 patients (19/61 had ≥ 2 paired scans), all performed with [18F]FDG and interpreted as showing active malignant hepatic involvement. Primary malignancies were of colorectal/biliary/pancreatic/breast/other origins in 19/9/9/7/17 patients. Monitoring response to therapy was the indication in 86/97 cases. When PET-MRI detected additional malignant lesions over PET-CT, lesions size, their characteristics on PET-MRI, and the influence on the final report were recorded.
In 37/97 (38.1%) cases, a total of 78 malignant lesions were identified on PET-MRI but not on PET-CT: 19 lesions (11 cases) were identified on PET of PET-MRI but not on PET of PET-CT; 37 lesions (14 cases) were small (≤ 0.8 cm) and identified on MRI only; 22 lesions (12 cases) were > 0.8 cm, had low/no [18F]FDG uptake, but were categorized as viable based on MRI. These 78 lesions caused major effect on final reports in 11/97 (11.3%) cases, changing reported response assessment category (10/86 cases) or defining malignant hepatic disease on staging/restaging scans (1/11 cases).
PET-MRI offers several advantages over PET-CT in assessing the extent and response to therapy of malignant hepatic involvement. Additional malignant lesions detected on PET-MRI are attributed to superior PET performance (compared with PET of PET-CT), greater spatial resolution provided by MRI, and improved multi-parametric viability assessment. In around one-tenth of cases, findings identified on PET-MRI but not on PET-CT significantly change the final report\'s conclusion.

The osteoarthritis (OA) research community has been advocating a shift from radiography-based screening criteria and outcome measures in OA clinical trials to a magnetic resonance imaging (MRI)-based definition of eligibility and endpoint. For conventional morphological MRI, various semiquantitative evaluation tools are available. We have lately witnessed a remarkable technological advance in MRI techniques, including compositional/physiologic imaging and automated quantitative analyses of articular and periarticular structures. More recently, additional technologies were introduced, including positron emission tomography (PET)-MRI, weight-bearing computed tomography (CT), photon-counting spectral CT, shear wave elastography, contrast-enhanced ultrasound, multiscale X-ray phase contrast imaging, and spectroscopic photoacoustic imaging of cartilage. On top of these, we now live in an era in which artificial intelligence is increasingly utilized in medicine. Osteoarthritis imaging is no exception. Successful implementation of artificial intelligence (AI) will hopefully improve the workflow of radiologists, as well as the level of precision and reproducibility in the interpretation of images.

BACKGROUND: We sought to determine the utility of PET-MRI in diagnosing Idiopathic Inflammatory Myositis (IIM), and look for association between FDG uptake and clinical, pathological and laboratory parameters.
METHODS: A retrospective, observational study was conducted on IIM patients having positive serum autoantibodies and who underwent PET-MRI (3-Tesla SIEMENS Biograph MR scanner) between 2017 and 2021. Thirty patients who underwent PET-MRI to detect systemic metastasis without muscle involvement formed the control group.
RESULTS: In the IIM cohort, female: male sex ratio was 1.73, mean age at diagnosis was 40.33 years, and the mean duration of illness was 7 months. 33.33% of patients had severe limb weakness. Mi2B (43.33%), Mi2A (43.33%), PL-7(10%), PL-12(6.67%), SRP (16.67%), Tif1gamma (3.33%), NxP2 (3.33%), Ro-52(40%), PM-Scl, U1-RNP, ANA (26.67%) were the serum autoantibodies identified. Using SUV max Ratio to quantify FDG uptake, PET-MRI showed a sensitivity of 100% with 93.3% specificity in diagnosing IIM.FDG uptake was maximum in proximal lower limb region followed by proximal upper limb. Multivariate regression analysis showed that the severity of muscle weakness, serum Mi2B antibody positivity and serum creatinine kinase levels had a significant positive correlation with FDG uptake (value of 0.005, 0.043, 0.042, respectively for whole-body FDG uptake). FDG uptake also showed good correlation with histopathological features and muscle MRI, but there was no significant association with treatment response. Three female patients in our cohort had primary malignancy involving the breast, uterus, and cervix.
CONCLUSIONS: PET-MRI is a promising diagnostic modality for IIM. PET-MRI reflects the severity of muscle inflammation, showing good association with various clinical/laboratory parameters, histopathology, and muscle MRI. Parameters associated with severe muscle inflammation in PET-MRI-clinical severity of muscle weakness, Mi2B positivity, and serum creatine kinase levels-may be used as clinical/laboratory markers of disease severity in IIM. PET-MRI has the added advantage of detection of systemic malignancy.

POEMS syndrome is a rare paraneoplastic syndrome associated with a plasma cell proliferative disorder. Gallbladder adenocarcinoma is a rare malignancy, with no association with POEMS syndrome. The plasma cell dyscrasia is routinely evaluated with advanced hybrid imaging to assess both anatomic and functional components. We present a case of a 59-year-old female with a known diagnosis of POEMS syndrome who underwent a whole-body restaging evaluation with hybrid positron emission tomography (PET) and magnetic resonance imaging (MR) to restage her plasma cell dyscrasia. She also had a prior diagnosis of gallbladder adenocarcinoma. Our case focuses on the value of PET/MR in this scenario as well as a rare case of osseous metastasis from gallbladder carcinoma.

UNASSIGNED: Advancements in hybrid positron emission tomography-magnetic resonance (PET-MR) systems allow for combining the advantages of each modality. Integrating information from MRI and PET can be valuable for diagnosing and treating neurological disorders. However, combining diffusion MRI (dMRI) and PET data, which provide highly complementary information, has rarely been exploited in image post-processing. dMRI has the ability to investigate the white matter pathways of the brain through fibre tractography, which enables comprehensive mapping of the brain connection networks (the \"connectome\"). Novel methods are required to combine information present in the connectome and PET to increase the full potential of PET-MRI.
UNASSIGNED: We developed a CONNectome-based Non-Local Means (CONN-NLM) filter to exploit synergies between dMRI-derived structural connectivity and PET intensity information to denoise PET images. PET-MR data are parcelled into a number of regions based on a brain atlas, and the inter-regional structural connectivity is calculated based on dMRI fibre-tracking. The CONN-NLM filter is then implemented as a post-reconstruction filter by combining the nonlocal means filter and a connectivity-based cortical smoothing. The effect of this approach is to weight voxels with similar PET intensity and highly connected voxels higher when computing the weighted-average to perform more informative denoising. The proposed method was first evaluated using a novel computer phantom framework to simulate realistic hybrid PET-MR images with different lesion scenarios. CONN-NLM was further assessed with clinical dMRI and tau PET examples.
UNASSIGNED: The results showed that CONN-NLM has the capacity to improve the overall PET image quality by reducing noise while preserving lesion contrasts, and it outperformed a range of filters that did not use dMRI information. The simulations demonstrate that CONN-NLM can handle various lesion contrasts consistently, as well as lesions with different levels of inter-connectivity.
UNASSIGNED: CONN-NLM has unique advantages of providing more informative and accurate PET smoothing by adding complementary structural connectivity information from dMRI, representing a new avenue to exploit synergies between MRI and PET.