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Background: Visual interpretation of PET and CMR may fail to identify cardiac sarcoidosis (CS) with high specificity. This study aimed to evaluate the role of [18F]FDG PET and late gadolinium enhancement (LGE)-CMR radiomic features in differentiating CS from another cause of myocardial inflammation, in this case patients with cardiac-related clinical symptoms following COVID-19. Methods: [18F]FDG PET and LGE-CMR were treated separately in this work. There were 35 post-COVID-19 (PC) and 40 CS datasets. Regions of interest were delineated manually around the entire left ventricle for the PET and LGE-CMR datasets. Radiomic features were then extracted. The ability of individual features to correctly identify image data as CS or PC was tested to predict the clinical classification of CS vs. PC using Mann--Whitney U-tests and logistic regression. Features were retained if the P-value was <0.00053, the AUC was >0.5, and the accuracy was >0.7. After applying the correlation test, uncorrelated features were used as a signature ( joint features) to train machine learning classifiers. For LGE-CMR analysis, to further improve the results, different classifiers were used for individual features besides logistic regression, and the results of individual features of each classifier were screened to create a signature that included all features that followed the previously mentioned criteria and used it them as input for machine learning classifiers. Results: The Mann--Whitney U-tests and logistic regression were trained on individual features to build a collection of features. For [18F]FDG PET analysis, the maximum target-to-background ratio (TBRmax) showed a high area under the curve (AUC) and accuracy with small P-values (<0.00053), but the signature performed better (AUC 0.98 and accuracy 0.91). For LGE-CMR analysis, the Gray Level Dependence Matrix (gldm)-Dependence Non-Uniformity showed good results with small error bars (accuracy 0.75 and AUC 0.87). However, by applying a Support Vector Machine classifier to individual LGE-CMR features and creating a signature, a Random Forest classifier displayed better AUC and accuracy (0.91 and 0.84, respectively). Conclusion: Using radiomic features may prove useful in identifying individuals with CS. Some features showed promising results in differentiating between PC and CS. By automating the analysis, the patient management process can be accelerated and improved. [ABSTRACT FROM AUTHOR]

Blood-brain barrier dysfunction might be driven by peripheral inflammation. TNFa inhibitors (TNF-αi) are occasionally associated with a wide spectrum of neurological immuno-mediated disorders. However, patients with systemic autoimmune disorders, including rheumatoid arthritis (RA), might be prone to develop further organ-specific, including central nervous system (CNS), autoimmunity. Here we report the case of a patient, affected by RA and treated with etanercept, who suddenly developed focal neurological symptoms. Cerebrospinal fluid, magnetic resonance imaging (MRI), and positron emission tomography (PET)/MRI findings are reported and support the diagnosis of TNF-αi-associated aseptic meningitis. [ABSTRACT FROM AUTHOR]

Simple Summary: Distinguishing radionecrosis from local recurrence after cranial radiotherapy remains a challenging diagnostic dilemma due to their overlapping clinical manifestations. Although new MRI techniques and metabolic imaging have been developed, diagnostic performance remains variable. Recently, our institution acquired a PET-MRI, enabling us to investigate the diagnostic performance of multiparametric MRI when used in dual-phase 18F-FDG PET-mpMRI to enhance diagnostic accuracy. Brain metastases or primary brain tumours had poor prognosis until the use of high dose radiotherapy. However, radionecrosis is a complex challenge in the post-radiotherapy management of these patients due to the difficulty of distinguishing this complication from local tumour recurrence. MRI alone has a variable specificity and sensibility, as does PET-CT imaging. We aimed to investigate the diagnostic performance of dual-phase 18F-FDG PET-mpMRI to distinguish cerebral radionecrosis from local tumour recurrence after cranial radiotherapy. A retrospective analysis was conducted between May 2021 and September 2022. Inclusion criteria encompassed patients with inconclusive MRI findings post-radiotherapy and history of cerebral radiotherapy for primary or metastatic brain lesions. Lesions are assessed qualitatively and semi-quantitatively. The gold standard to assess radionecrosis was histopathology or a composite criterion at three months. The study evaluated 24 lesions in 23 patients. Qualitative analysis yielded 85.7% sensitivity and 75% specificity. Semi-quantitative analysis, based on contralateral background noise, achieved 100% sensitivity and 50% specificity. Moreover, using contralateral frontal lobe background noise resulted in higher performances with 92% sensitivity and 63% specificity. Stratification by lesion type demonstrated 100% sensitivity and specificity rates for metastatic lesions. The diagnostic performance of dual-phase 18F-FDG PET-mpMRI shows promising results for metastatic lesions. [ABSTRACT FROM AUTHOR]

Abstract Purpose Our objective was to assess a deconvolution and denoising technique based on Legendre polynomials compared to matrix deconvolution on dynamic 18F-FDG renography of healthy patients. Method The study was carried out and compared to the data of 24 healthy patients from a published study who underwent examinations with 99mTc-MAG3 planar scintigraphy and 18F-FDG PET/MRI. Due to corruption issues in some data used in the published article, post-publication measurements were provided. We have been warned that post-publication data were treated differently. The smoothing method switched from Bezier to Savitzky–Golay and the deconvolution from matrix-based (with Tikhonov Regularization) to Richardson–Lucy. A comparison of the split function and mean transit times of the published and post-publication data against our method based on Legendre polynomials was performed. Results For split function, we only observed a good agreement between the processing methods for the 99mTc-MAG3 and the post-published data. No correlation was found between the split functions obtained on the 99mTc-MAG3 and the 18F-FDG, contrary to the published study. However, all calculated split function values for 18F-FDG and 99mTc-MAG3 were within the established normal range. For the mean transit time, the correlation was moderate with published data and very good with the post-publication measurements for both 99mTc-MAG3 and 18F-FDG. Bias of the Bland–Altman analysis of the mean transit times for 99mTc-MAG3 versus 18F-FDG was 1.1 min (SD 1.7 min) for the published data, − 0.11 min (SD 1.9 min) for the post-publication results and .05 min (SD 1.9 min) for our method. Conclusions The processing methods used in the original publication and in the post-publication work were quite complex and required adaptation of the fitting parameters for each individual and each type of examination. Our method did not require any specific adjustment; the same unmodified and fully automated algorithm was successfully applied to all data.

Simple Summary: Simultaneous positron emission tomography/magnetic resonance imaging (PET-MRI) combines the high sensitivity of PET with the high specificity of MRI. Here, we aimed to evaluate whether a combined PET-MRI exam may give more information than conventional exams at the time of diagnosis in a series of patients presenting with a neuroendocrine tumor in the pancreas or within the gastrointestinal tract. We also investigated if the procedure could influence survival. In 71 patients, we performed a PETMRI at the baseline and in 50 patients the follow-up was based on PET-MRI performed every 6–12 months. The results show that the hybrid exam yielded new information at the baseline and during the follow-up, but had no impact on the survival. Introduction and aim: 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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

Background: Amino acid positron emission tomography (PET) imaging plays a significant role in the diagnosis of gliomas and in differentiating tumor recurrence from necrosis. In this study, the authors evaluated the diagnostic efficacy of [99mTc]Tc-methionine single-photon emission computed tomography–computed tomography (SPECT-CT) in comparison with [11C]methionine PET-magnetic resonance imaging (MRI) in delineating tumors. Methods: Thirty-one (primary: 16 and postoperative: 15) patients of confirmed (either MRI or histopathological proven) glioma underwent both [99mTc]Tc-methionine SPECT-CT and [11C]methionine PET-MRI. A comparative analysis was performed between SPECT, PET, and MR images to calculate the concordance between the modalities and to evaluate the diagnostic efficacy of the [99mTc]Tc-methionine SPECT. Results: [99mTc]Tc-methionine SPECT showed comparable uptake in the tumor lesions in comparison to [11C]methionine PET. A significant and strong positive correlation was observed between the volume of tumor (Vt) in PET and Vt MR (p < 0.004). Likewise, a significant and strong positive correlation was found between Vt SPECT and Vt MR. [99mTc]-methionine has a sensitivity and specificity of 91% and 75%, respectively, compared with 82% and 100% for [11C]methionine in postoperative cases to differentiate the tumor recurrence from necrosis. The sensitivity and specificity of [99mTc]Tc-methionine was 92% and 100%, respectively, compared with 92% and 67% for [11C]methionine in primary tumors. Conclusion: [99mTc]Tc-methionine SPECT-CT is as equally good as [11C]methionine for diagnosing and differentiating it from necrosis especially in high-grade glioma. [ABSTRACT FROM AUTHOR]

Blood-brain barrier dysfunction might be driven by peripheral inflammation. TNFα inhibitors (TNF-αi) are occasionally associated with a wide spectrum of neurological immuno-mediated disorders. However, patients with systemic autoimmune disorders, including rheumatoid arthritis (RA), might be prone to develop further organ-specific, including central nervous system (CNS), autoimmunity. Here we report the case of a patient, affected by RA and treated with etanercept, who suddenly developed focal neurological symptoms. Cerebrospinal fluid, magnetic resonance imaging (MRI), and positron emission tomography (PET)/MRI findings are reported and support the diagnosis of TNF-αi -associated aseptic meningitis.

Background: Visual interpretation of PET and CMR may fail to identify cardiac sarcoidosis (CS) with high specificity. This study aimed to evaluate the role of [18F]FDG PET and late gadolinium enhancement (LGE)-CMR radiomic features in differentiating CS from another cause of myocardial inflammation, in this case patients with cardiac-related clinical symptoms following COVID-19. Methods: [18F]FDG PET and LGE-CMR were treated separately in this work. There were thirty-five post-COVID-19 (PC) and forty CS datasets. Regions of interest were delineated manually around the entire left ventricle for PET and LGE-CMR datasets. Radiomic features were then extracted. The ability of individual features to correctly identify image data as CS or PC was tested to predict clinical classification of CS vs. PC using Mann-Whitney U-tests and logistic regression. Features were retained if P-value <0.00053, AUC >0.5 and accuracy >0.7. After applying correlation test, uncorrelated features were used as a signature (joint features) to train machine learning classifiers. For LGE-CMR analysis, to further improve the results, different classifiers were used for individual features besides logistic regression and the results of individual features of each classifier were screened to create a signature that include all features that followed the previously mentioned criteria and use them as input for machine learning classifiers. Results: The Mann-Whitney U-tests and logistic regression were trained on individual features to build a collection of features. For [18F]FDG PET analysis, the maximum target-to-background ratio (TBRmax) showed high area under the curve (AUC) and accuracy with small P-values (<0.00053) but the signature performed better (AUC 0.98 and accuracy 0.91). For LGE-CMR analysis, Gray Level Dependence Matrix (gldm)-Dependence Non-Uniformity showed good results with small error bars (accuracy 0.75 and AUC 0.87). However, by applying a Support Vector Machine classifier on individual LGE-CMR features and creating a signature, a Random Forest classifier displayed better AUC and accuracy (0.91 and 0.84, respectively). Conclusion: Using radiomic features may prove useful in identifying individuals with CS. Some features showed promising results to differentiate between PC and CS. By automating the analysis, the patient management process can be accelerated and improved. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Simultaneously operating MR-PET systems have the potential to provide synergetic multi-parametric information, and, as such, interest surrounding their use and development is increasing. However, despite the potential advantages offered by fully combined MR-PET systems, implementing this hybrid integration is technically laborious, and any factors degrading the quality of either modality must be circumvented to ensure optimal performance. In order to attain the best possible quality from both systems, most full MR-PET integrations tend to place the shielded PET system inside the MRI system, close to the target volume of the subject. The radiofrequency (RF) coil used in MRI systems is a key factor in determining the quality of the MR images, and, in simultaneous acquisition, it is generally positioned inside the PET system and PET imaging region, potentially resulting in attenuation and artefacts in the PET images. Therefore, when designing hybrid MR-PET systems, it is imperative that consideration be given to the RF coils inside the PET system. In this review, we present current state-of-the-art RF coil designs used for hybrid MR-PET experiments and discuss various design strategies for constructing PET transparent RF coils. [ABSTRACT FROM AUTHOR]

BackgroundVisual interpretation of PET and CMR may fail to identify cardiac sarcoidosis (CS) with high specificity. This study aimed to evaluate the role of [18F]FDG PET and late gadolinium enhancement (LGE)-CMR radiomic features in differentiating CS from another cause of myocardial inflammation, in this case patients with cardiac-related clinical symptoms following COVID-19.Methods[18F]FDG PET and LGE-CMR were treated separately in this work. There were 35 post-COVID-19 (PC) and 40 CS datasets. Regions of interest were delineated manually around the entire left ventricle for the PET and LGE-CMR datasets. Radiomic features were then extracted. The ability of individual features to correctly identify image data as CS or PC was tested to predict the clinical classification of CS vs. PC using Mann–Whitney U-tests and logistic regression. Features were retained if the P-value was 0.5, and the accuracy was >0.7. After applying the correlation test, uncorrelated features were used as a signature (joint features) to train machine learning classifiers. For LGE-CMR analysis, to further improve the results, different classifiers were used for individual features besides logistic regression, and the results of individual features of each classifier were screened to create a signature that included all features that followed the previously mentioned criteria and used it them as input for machine learning classifiers.ResultsThe Mann–Whitney U-tests and logistic regression were trained on individual features to build a collection of features. For [18F]FDG PET analysis, the maximum target-to-background ratio (TBRmax) showed a high area under the curve (AUC) and accuracy with small P-values (

Evidence has shown a rapid antidepressant and antisuicidal effects of low-dose ketamine infusion among patients with treatment-resistant depression (TRD) and prominent suicidal ideation (SI). The dorsolateral prefrontal cortex (DLPFC) plays a crucial role in the TRD pathomechanisms. Whether the structural and functional changes of the DLPFC, particularly Brodmann area 46, are associated with the antidepressant and antisuicidal effects of ketamine infusion among such patients is unknown. We randomized 48 patients with TRD and SI into groups receiving a single infusion of 0.5 mg/kg ketamine or 0.045 mg/kg midazolam. The Hamilton Depression Rating Scale and the Montgomery–Asberg Depression Rating Scale were used to assess symptoms. Positron emission tomography (PET)–magnetic resonance imaging was conducted prior to infusion and on Day 3 postinfusion. We performed longitudinal voxel-based morphometry (VBM) analysis to evaluate the gray matter (GM) volume changes of the DLPFC. The standardized uptake value ratio (SUVr) of 18F-fluorodeoxyglucose PET images was calculated using the SUV of the cerebellum as a reference region. The VBM analysis revealed a small but significant volumetric reduction in the right DLPFC in the ketamine group compared with that in the midazolam group. A greater reduction in depressive symptoms was associated with a smaller decrease in right DLPFC volumes (p = 0.025). However, we found no SUVr changes of the DLPFC between baseline and post-Day 3 ketamine infusion. The optimal modulation of the right DLPFC GM volumes may play an essential role in the antidepressant neuromechanisms of low-dose ketamine. • Low-dose ketamine reduced the gray matter volume of right DLPFC on Day 3 postinfusion among patients with TRD and SI. • There was a negative correlation between the changes in depression symptoms and the volumetric changes in the right DLPFC. • Optimal modulation of right DLPFC gray matter volumes may play a role in the antidepressant effect of low-dose ketamine [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

Abstract 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.

Abstract Aim To compare [68Ga]PSMA-11 PET-CT, [68Ga]PSMA-11 PET-MRI and MRI in a cohort of prostate cancer (PCa) patients in biochemical recurrence after initial curative therapy. Materials and methods Fifty-three patients with biochemically recurrent PCa underwent whole-body [68Ga]PSMA-11 PET-CT 1 hour post-injection (p.i.) followed by [68Ga]PSMA-11 PET-MRI 2.5 hours p.i., including a multiparametric MRI pelvic protocol examination. Imaging data analysis consisted of visual (qualitative) evaluation of the PET-CT, PET-MRI and MRI scans, as well as semi-quantitative and quantitative analyses of the PET and MRI data, including calculation of the parameters standardized uptake value (SUV) and apparent diffusion coefficient (ADC) derived from the PCa lesions. Association analysis was performed between imaging and clinical data, including PSA level and Gleason score. The results were considered significant for p-values less than 0.05 (p

Purpose: 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. Methods: 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. Results: 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). Conclusion: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

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. [ABSTRACT FROM AUTHOR]

Abstract Background Due to comparatively long measurement times in simultaneous positron emission tomography and magnetic resonance (PET/MR) imaging, patient movement during the measurement can be challenging. This leads to artifacts which have a negative impact on the visual assessment and quantitative validity of the image data and, in the worst case, can lead to misinterpretations. Simultaneous PET/MR systems allow the MR-based registration of movements and enable correction of the PET data. To assess the effectiveness of motion correction methods, it is necessary to carry out measurements on phantoms that are moved in a reproducible way. This study explores the possibility of using such a phantom-based setup to evaluate motion correction strategies in PET/MR of the human head. Method An MR-compatible robotic system was used to generate rigid movements of a head-like phantom. Different tools, either from the manufacturer or open-source software, were used to estimate and correct for motion based on the PET data itself (SIRF with SPM and NiftyReg) and MR data acquired simultaneously (e.g. MCLFIRT, BrainCompass). Different motion estimates were compared using data acquired during robot-induced motion. The effectiveness of motion correction of PET data was evaluated by determining the segmented volume of an activity-filled flask inside the phantom. In addition, the segmented volume was used to determine the centre-of-mass and the change in maximum activity concentration. Results The results showed a volume increase between 2.7 and 36.3% could be induced by the experimental setup depending on the motion pattern. Both, BrainCompass and MCFLIRT, produced corrected PET images, by reducing the volume increase to 0.7–4.7% (BrainCompass) and to -2.8–0.4% (MCFLIRT). The same was observed for example for the centre-of-mass, where the results show that MCFLIRT (0.2–0.6 mm after motion correction) had a smaller deviation from the reference position than BrainCompass (0.5–1.8 mm) for all displacements. Conclusions The experimental setup is suitable for the reproducible generation of movement patterns. Using open-source software for motion correction is a viable alternative to the vendor-provided motion-correction software.

Abstract Background Attenuation correction is crucial in quantitative positron emission tomography-magnetic resonance (PET-MRI) imaging. We evaluated three methods to improve the segmentation and modelling of the attenuation coefficients in the nasal sinus region. Two methods (cuboid and template method) included a MRI-CT conversion model for assigning the attenuation coefficients in the nasal sinus region, whereas one used fixed attenuation coefficient assignment (bulk method). Methods The study population consisted of data of 10 subjects which had undergone PET-CT and PET-MRI. PET images were reconstructed with and without time-of-flight (TOF) using CT-based attenuation correction (CTAC) as reference. Comparison was done visually, using DICE coefficients, correlation, analyzing attenuation coefficients, and quantitative analysis of PET and bias atlas images. Results The median DICE coefficients were 0.824, 0.853, 0.849 for the bulk, cuboid and template method, respectively. The median attenuation coefficients were 0.0841 cm−1, 0.0876 cm−1, 0.0861 cm−1 and 0.0852 cm−1, for CTAC, bulk, cuboid and template method, respectively. The cuboid and template methods showed error of less than 2.5% in attenuation coefficients. An increased correlation to CTAC was shown with the cuboid and template methods. In the regional analysis, improvement in at least 49% and 80% of VOI was seen with non-TOF and TOF imaging. All methods showed errors less than 2.5% in non-TOF and less than 2% in TOF reconstructions. Conclusions We evaluated two proof-of-concept methods for improving quantitative accuracy in PET/MRI imaging and showed that bias can be further reduced by inclusion of TOF. Largest improvements were seen in the regions of olfactory bulb, Heschl's gyri, lingual gyrus and cerebellar vermis. However, the overall effect of inclusion of the sinus region as separate class in MRAC to PET quantification in the brain was considered modest.

Purpose: Tumor-to-background ratio (TBR) is a critical metric in oncologic PET imaging. This study aims to enhance the TBR of [18F]FET in brain tumor imaging by substituting deuterium ("D") for hydrogen ("H"), thereby improving the diagnostic sensitivity and accuracy.[18F]d4-FET was synthesised by two automated radiochemistry modules. Biodistribution studies and imaging efficacy were evaluated in vivo  and ex vivo in rodent models, while metabolic stability and radiation dosimetry were assessed in non-human primates. Additionally, preliminary imaging evaluations were carried out in five brain tumor patients: three glioma patients underwent imaging with both [18F]d4-FET and [18F]FET, and two patients with brain metastases were imaged using [18F]d4-FET and [18F]FDG.[18F]d4-FET demonstrated high radiochemical purity and yield. PET/MRI in rodent models demonstrated superior TBR for [18F]d4-FET compared to [18F]FET, and autoradiography showed tumor margins that correlated well with pathological extents. Studies in cynomolgus monkeys indicated comparable in vivo stability and effective dose with [18F]FET. In glioma patients, [18F]d4-FET showed enhanced TBR, while in patients with brain metastases, [18F]d4-FET displayed superior lesion delineation compared to [18F]FDG, especially in smaller metastatic sites.We successfully synthesized the novel PET radiotracer [18F]d4-FET, which retains the advantageous properties of [18F]FET while potentially enhancing TBR for glioma imaging. Preliminary studies indicate excellent stability, efficacy, and sensitivity of [18F]d4-FET, suggesting its potential in clinical evaluations of brain tumors.ChiCTR2400081576, registration date: 2024–03-05, https://www.chictr.org.cn/bin/project/edit?pid=206162Methods: Tumor-to-background ratio (TBR) is a critical metric in oncologic PET imaging. This study aims to enhance the TBR of [18F]FET in brain tumor imaging by substituting deuterium ("D") for hydrogen ("H"), thereby improving the diagnostic sensitivity and accuracy.[18F]d4-FET was synthesised by two automated radiochemistry modules. Biodistribution studies and imaging efficacy were evaluated in vivo  and ex vivo in rodent models, while metabolic stability and radiation dosimetry were assessed in non-human primates. Additionally, preliminary imaging evaluations were carried out in five brain tumor patients: three glioma patients underwent imaging with both [18F]d4-FET and [18F]FET, and two patients with brain metastases were imaged using [18F]d4-FET and [18F]FDG.[18F]d4-FET demonstrated high radiochemical purity and yield. PET/MRI in rodent models demonstrated superior TBR for [18F]d4-FET compared to [18F]FET, and autoradiography showed tumor margins that correlated well with pathological extents. Studies in cynomolgus monkeys indicated comparable in vivo stability and effective dose with [18F]FET. In glioma patients, [18F]d4-FET showed enhanced TBR, while in patients with brain metastases, [18F]d4-FET displayed superior lesion delineation compared to [18F]FDG, especially in smaller metastatic sites.We successfully synthesized the novel PET radiotracer [18F]d4-FET, which retains the advantageous properties of [18F]FET while potentially enhancing TBR for glioma imaging. Preliminary studies indicate excellent stability, efficacy, and sensitivity of [18F]d4-FET, suggesting its potential in clinical evaluations of brain tumors.ChiCTR2400081576, registration date: 2024–03-05, https://www.chictr.org.cn/bin/project/edit?pid=206162Results: Tumor-to-background ratio (TBR) is a critical metric in oncologic PET imaging. This study aims to enhance the TBR of [18F]FET in brain tumor imaging by substituting deuterium ("D") for hydrogen ("H"), thereby improving the diagnostic sensitivity and accuracy.[18F]d4-FET was synthesised by two automated radiochemistry modules. Biodistribution studies and imaging efficacy were evaluated in vivo  and ex vivo in rodent models, while metabolic stability and radiation dosimetry were assessed in non-human primates. Additionally, preliminary imaging evaluations were carried out in five brain tumor patients: three glioma patients underwent imaging with both [18F]d4-FET and [18F]FET, and two patients with brain metastases were imaged using [18F]d4-FET and [18F]FDG.[18F]d4-FET demonstrated high radiochemical purity and yield. PET/MRI in rodent models demonstrated superior TBR for [18F]d4-FET compared to [18F]FET, and autoradiography showed tumor margins that correlated well with pathological extents. Studies in cynomolgus monkeys indicated comparable in vivo stability and effective dose with [18F]FET. In glioma patients, [18F]d4-FET showed enhanced TBR, while in patients with brain metastases, [18F]d4-FET displayed superior lesion delineation compared to [18F]FDG, especially in smaller metastatic sites.We successfully synthesized the novel PET radiotracer [18F]d4-FET, which retains the advantageous properties of [18F]FET while potentially enhancing TBR for glioma imaging. Preliminary studies indicate excellent stability, efficacy, and sensitivity of [18F]d4-FET, suggesting its potential in clinical evaluations of brain tumors.ChiCTR2400081576, registration date: 2024–03-05, https://www.chictr.org.cn/bin/project/edit?pid=206162Conclusion: Tumor-to-background ratio (TBR) is a critical metric in oncologic PET imaging. This study aims to enhance the TBR of [18F]FET in brain tumor imaging by substituting deuterium ("D") for hydrogen ("H"), thereby improving the diagnostic sensitivity and accuracy.[18F]d4-FET was synthesised by two automated radiochemistry modules. Biodistribution studies and imaging efficacy were evaluated in vivo  and ex vivo in rodent models, while metabolic stability and radiation dosimetry were assessed in non-human primates. Additionally, preliminary imaging evaluations were carried out in five brain tumor patients: three glioma patients underwent imaging with both [18F]d4-FET and [18F]FET, and two patients with brain metastases were imaged using [18F]d4-FET and [18F]FDG.[18F]d4-FET demonstrated high radiochemical purity and yield. PET/MRI in rodent models demonstrated superior TBR for [18F]d4-FET compared to [18F]FET, and autoradiography showed tumor margins that correlated well with pathological extents. Studies in cynomolgus monkeys indicated comparable in vivo stability and effective dose with [18F]FET. In glioma patients, [18F]d4-FET showed enhanced TBR, while in patients with brain metastases, [18F]d4-FET displayed superior lesion delineation compared to [18F]FDG, especially in smaller metastatic sites.We successfully synthesized the novel PET radiotracer [18F]d4-FET, which retains the advantageous properties of [18F]FET while potentially enhancing TBR for glioma imaging. Preliminary studies indicate excellent stability, efficacy, and sensitivity of [18F]d4-FET, suggesting its potential in clinical evaluations of brain tumors.ChiCTR2400081576, registration date: 2024–03-05, https://www.chictr.org.cn/bin/project/edit?pid=206162Trial registration: Tumor-to-background ratio (TBR) is a critical metric in oncologic PET imaging. This study aims to enhance the TBR of [18F]FET in brain tumor imaging by substituting deuterium ("D") for hydrogen ("H"), thereby improving the diagnostic sensitivity and accuracy.[18F]d4-FET was synthesised by two automated radiochemistry modules. Biodistribution studies and imaging efficacy were evaluated in vivo  and ex vivo in rodent models, while metabolic stability and radiation dosimetry were assessed in non-human primates. Additionally, preliminary imaging evaluations were carried out in five brain tumor patients: three glioma patients underwent imaging with both [18F]d4-FET and [18F]FET, and two patients with brain metastases were imaged using [18F]d4-FET and [18F]FDG.[18F]d4-FET demonstrated high radiochemical purity and yield. PET/MRI in rodent models demonstrated superior TBR for [18F]d4-FET compared to [18F]FET, and autoradiography showed tumor margins that correlated well with pathological extents. Studies in cynomolgus monkeys indicated comparable in vivo stability and effective dose with [18F]FET. In glioma patients, [18F]d4-FET showed enhanced TBR, while in patients with brain metastases, [18F]d4-FET displayed superior lesion delineation compared to [18F]FDG, especially in smaller metastatic sites.We successfully synthesized the novel PET radiotracer [18F]d4-FET, which retains the advantageous properties of [18F]FET while potentially enhancing TBR for glioma imaging. Preliminary studies indicate excellent stability, efficacy, and sensitivity of [18F]d4-FET, suggesting its potential in clinical evaluations of brain tumors.ChiCTR2400081576, registration date: 2024–03-05, https://www.chictr.org.cn/bin/project/edit?pid=206162 [ABSTRACT FROM AUTHOR]

This study aimed to assess the glymphatic function and its correlation with clinical characteristics and the loss of dopaminergic neurons in Parkinson's disease (PD) using hybrid positron emission tomography (PET)-magnetic resonance imaging (MRI) combined with diffusion tensor image analysis along the perivascular space (DTI-ALPS), choroid plexus volume (CPV), and enlarged perivascular space (EPVS) volume. Twenty-five PD patients and thirty matched healthy controls (HC) participated in the study. All participants underwent 18F-fluorodopa (18F-DOPA) PET-MRI scanning. The striatal standardized uptake value ratio (SUVR), DTI-ALPS index, CPV, and EPVS volume were calculated. Furthermore, we also analysed the relationship between the DTI-ALPS index, CPV, EPVS volume and striatal SUVR as well as clinical characteristics of PD patients. PD patients demonstrated significantly lower values in DTI-ALPS (t = 3.053, p = 0.004) and larger CPV (t = 2.743, p = 0.008) and EPVS volume (t = 2.807, p = 0.008) compared to HC. In PD group, the ALPS-index was negatively correlated with the Unified Parkinson's Disease Rating Scale III (UPDRS-III) scores (r = −0.730, p < 0.001), and positively correlated with the mean putaminal SUVR (r = 0.560, p = 0.007) and mean caudal SUVR (r = 0.459, p = 0.032). Moreover, the mean putaminal SUVR was negatively associated with the UPDRS-III scores (r = −0.544, p = 0.009). DTI-ALPS has the potential to uncover glymphatic dysfunction in patients with PD, with this dysfunction correlating strongly with the severity of disease, together with the mean putaminal and caudal SUVR. PET- MRI can serve as a potential multimodal imaging biomarker for early-stage PD. • An early detection method for Parkinson's disease with hybrid PET-MRI is introduced. • The dopaminergic and glymphatic systems exhibit dysfunction and correlation. • PET-MRI may be a potential imaging biomarker for early Parkinson's disease. [ABSTRACT FROM AUTHOR]

Purpose: PET-CT has recently been included in the NCCN staging recommendations for cervical cancer stages II-IV and is already routinely applied to radiotherapy planning for other malignancies, as it is expected to provide higher accuracy for the detection of areas with tumor cell spread. In this study, we report on our first experiences of PET-based radiotherapy planning for cervical cancer.Methods: 19 patients with cervical cancer that underwent pre-therapeutic PET imaging treated at our institution between January 2016 and April 2019 were included in the study. Information on the primary tumor, lymph node involvement, metastatic spread and changes in the radiotherapy procedure based on the PET findings are described.Results: A previously unknown primary tumor extension that was detected by PET imaging in one patient. In patients who underwent a PET before the systematic pelvic and paraaortic lymphonodectomy (n = 2), PET was false negative for pelvic lymph node metastases in 50%. In patients who underwent a PET after the systematic LNE (n = 13), additional lymph node metastases were detected in seven patients (53.80%). Distant metastases were suspected in three patients (15.7%) based on PET imaging. The suspicion was confirmed in one patient (peritoneal spread) and excluded in two patients (supra-diaphragmatic lymph nodes). In 13 patients (68.4%), RT procedures were altered due to findings in PET imaging.Conclusion: PET-based radiochemotherapy planning may improve control rates by identifying areas of tumor cell spread eligible for dose escalation. False positivity, however, should be excluded in patients with findings that lead to major modifications of the therapeutic strategy. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract Background Graft versus host disease (GvHD) is a frequent complication of allogeneic stem cell transplantation (alloSCT), significantly increasing mortality. Previous imaging studies focused on the assessment of intestinal GvHD with contrast-enhanced MRI/CT or 18F-FDG-PET imaging alone. The objective of this retrospective study was to elucidate the diagnostic value of a combined 18F-FDG-PET-MRI protocol in patients with acute intestinal GvHD. Methods Between 2/2015 and 8/2019, 21 patients with acute intestinal GvHD underwent 18F-FDG-PET-MRI. PET, MRI and PET-MRI datasets were independently reviewed. Readers assessed the number of affected segments of the lower gastrointestinal tract and the reliability of the diagnosis on a 5-point Likert scale and quantitative PET (SUVmax, SUVpeak, metabolic volume (MV)) and MRI parameter (wall thickness), were correlated to clinical staging of acute intestinal GvHD. Results The detection rate for acute intestinal GvHD was 56.8% for PET, 61.4% for MRI and 100% for PET-MRI. PET-MRI (median Likert-scale value: 5; range: 4–5) offers a significantly higher reliability of the diagnosis compared to PET (median: 4; range: 2–5; p = 0.01) and MRI alone (median: 4; range: 3–5; p = 0.03). The number of affected segments in PET-MRI (rs = 0.677; p

We have developed chelator-free copper-64-incorporated iron oxide (IO) nanoparticle (NPs) which have both magnetic and radioactive properties being applied to positron emission tomography (PET)-magnetic resonance imaging (MRI). We have found that the IO nanoparticles composed of radioactive isotope 64Cu may act as a contrast agent being a diagnostic tool for PET as well as a good T2 MRI nanoprobe due to their good r2/r1 ratio. Furthermore, we demonstrate that the 64Cu incorporation at the core of core-shell-structured IO NPs exhibits a good in vivo stability, giving us an insightful strategy for the design of a contrast agent for the PET-MRI system. [ABSTRACT FROM AUTHOR]

Abstract Introduction The assessment of ex vivo biodistribution is the preferred method for quantification of radiotracers biodistribution in preclinical models, but is not in line with current ethics on animal research. PET imaging allows for noninvasive longitudinal evaluation of tracer distribution in the same animals, but systemic comparison with ex vivo biodistribution is lacking. Our aim was to evaluate the potential of preclinical PET imaging for accurate tracer quantification, especially in tumor models. Methods NEMA NU 4-2008 phantoms were filled with 11C, 68Ga, 18F, or 89Zr solutions and scanned in Mediso nanoPET/CT and PET/MR scanners until decay. N87 tumor-bearing mice were i.v. injected with either [18F]FDG (~ 14 MBq), kept 50 min under anesthesia followed by imaging for 20 min, or with [89Zr]Zr-DFO-NCS-trastuzumab (~ 5 MBq) and imaged 3 days post-injection for 45 min. After PET acquisition, animals were killed and organs of interest were collected and measured in a γ-counter to determine tracer uptake levels. PET data were reconstructed using TeraTomo reconstruction algorithm with attenuation and scatter correction and regions of interest were drawn using Vivoquant software. PET imaging and ex vivo biodistribution were compared using Bland–Altman plots. Results In phantoms, the highest recovery coefficient, thus the smallest partial volume effect, was obtained with 18F for both PET/CT and PET/MR. Recovery was slightly lower for 11C and 89Zr, while the lowest recovery was obtained with 68Ga in both scanners. In vivo, tumor uptake of the 18F- or 89Zr-labeled tracer proved to be similar irrespective whether quantified by either PET/CT and PET/MR or ex vivo biodistribution with average PET/ex vivo ratios of 0.8–0.9 and a deviation of 10% or less. Both methods appeared less congruent in the quantification of tracer uptake in healthy organs such as brain, kidney, and liver, and depended on the organ evaluated and the radionuclide used. Conclusions Our study suggests that PET quantification of 18F- and 89Zr-labeled tracers is reliable for the evaluation of tumor uptake in preclinical models and a valuable alternative technique for ex vivo biodistribution. However, PET and ex vivo quantification require fully described experimental and analytical procedures for reliability and reproducibility.

Abstract Background Malignancy during pregnancy is increasing, and the most common type of malignancy is uterine cervical cancer. When planning the treatment of cervical cancer, it is important to look for signs of metastasis before surgery, especially metastasis to the lymph nodes. In this report, we assessed the diagnostic value of positron emission tomography/magnetic resonance imaging (PET/MRI) for evaluating cervical cancer propagation before surgery, with a focus on pregnant women. Case presentation 18F Fluorodeoxyglucose (FDG)-PET/MRI was performed in seven pregnant cervical cancer patients (28–34 years old) at 9–18 gestational weeks. In case #5, a second PET/MRI was performed at 24 gestational weeks. Of seven FDG-PET/MRI examination series in six cases (cases #1–6), FDG-PET/MR imaging could detect cervical tumors with abnormal FDG accumulation; these tumors were confirmed with a standardized uptake value max (SUV max) titer of 4.5–16. A second PET/MRI examination in case #5 revealed the same SUV max titer as the first examination. In these six imaging series (cases #1–5), there were no signs of cancer metastasis to the parametrium and lymph nodes. However, in case #6, abnormal FDG accumulation in the left parametrial lymph nodes was also detectable. Pathological examination showed lymph node metastasis in case #6. In case #7, PET/MRI could not detect any abnormal FDG accumulation in the cervix and other sites. Cone biopsy demonstrated only micro-invasive squamous cell carcinoma. After treatment for cervical cancer, all seven patients have had no recurrence of disease within the follow-up period (2.8–5.6 years), and their children have developed appropriately. Conclusion PET/MRI is an effective imaging tool to evaluate cervical cancer progression in pregnancy.

Abstract Background Respiratory motion during PET imaging reduces image quality. Data-driven gating (DDG) based on principal component analysis (PCA) can be used to identify respiratory signals. The use of DDG, without need for external devices, would greatly increase the feasibility of using respiratory gating in a routine clinical setting. The objective of this study was to evaluate data-driven gating in relation to external hardware gating and regular static image acquisition on PET-MRI data with respect to SUVmax and lesion volumes. Methods Sixteen patients with esophageal or gastroesophageal cancer (Siewert I and II) underwent a 6-min PET scan on a Signa PET-MRI system (GE Healthcare) 1.5–2 h after injection of 4 MBq/kg 18F-FDG. External hardware gating was done using a respiratory bellow device, and DDG was performed using MotionFree (GE Healthcare). The DDG raw data files and the external hardware-gating raw files were created on a Matlab-based toolbox from the whole 6-min scan LIST-file. For comparison, two 3-min static raw files were created for each patient. Images were reconstructed using TF-OSEM with resolution recovery with 2 iterations, 28 subsets, and 3-mm post filter. SUVmax and lesion volume were measured in all visible lesions, and noise level was measured in the liver. Paired t-test, linear regression, Pearson correlation, and Bland-Altman analysis were used to investigate difference, correlation, and agreement between the methods. Results A total number of 30 lesions were included in the study. No significant differences between DDG and external hardware-gating SUVmax or lesion volumes were found, but the noise level was significantly reduced in the DDG images. Both DDG and external hardware gating demonstrated significantly higher SUVmax (9.4% for DDG, 10.3% for external hardware gating) and smaller lesion volume (− 5.4% for DDG, − 6.6% for external gating) in comparison with non-gated static images. Conclusions Data-driven gating with MotionFree for PET-MRI performed similar to external device gating for esophageal lesions with respect to SUVmax and lesion volume. Both gating methods significantly increased the SUVmax and reduced the lesion volume in comparison with non-gated static acquisition. DDG resulted in reduced image noise compared to external device gating and static images.

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.

Background: 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. Methods: 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. Results: 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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

Gliomas are the most frequent primary tumors of the brain. They can be divided into grade II-IV astrocytomas and grade II-III oligodendrogliomas, based on their histomolecular profile. The prognosis and treatment is highly dependent on grade and well-identified prognostic and/or predictive molecular markers. Multi-parametric MRI, including diffusion weighted imaging, perfusion, and MR spectroscopy, showed increasing value in the non-invasive characterization of specific molecular subsets of gliomas. Radiolabeled amino-acid analogues, such as 18F-FET, have also been proven valuable in glioma imaging. These tracers not only contribute in the diagnostic process by detecting areas of dedifferentiation in diffuse gliomas, but this technique is also valuable in the follow-up of gliomas, as it can differentiate pseudo-progression from real tumor progression. Since multi-parametric MRI and 18F-FET PET are complementary imaging techniques, there may be a synergistic role for PET-MRI imaging in the neuro-oncological imaging of primary brain tumors. This could be of value for both primary staging, as well as during treatment and follow-up. [ABSTRACT FROM AUTHOR]

Background: Due to comparatively long measurement times in simultaneous positron emission tomography and magnetic resonance (PET/MR) imaging, patient movement during the measurement can be challenging. This leads to artifacts which have a negative impact on the visual assessment and quantitative validity of the image data and, in the worst case, can lead to misinterpretations. Simultaneous PET/MR systems allow the MR-based registration of movements and enable correction of the PET data. To assess the effectiveness of motion correction methods, it is necessary to carry out measurements on phantoms that are moved in a reproducible way. This study explores the possibility of using such a phantom-based setup to evaluate motion correction strategies in PET/MR of the human head. Method: An MR-compatible robotic system was used to generate rigid movements of a head-like phantom. Different tools, either from the manufacturer or open-source software, were used to estimate and correct for motion based on the PET data itself (SIRF with SPM and NiftyReg) and MR data acquired simultaneously (e.g. MCLFIRT, BrainCompass). Different motion estimates were compared using data acquired during robot-induced motion. The effectiveness of motion correction of PET data was evaluated by determining the segmented volume of an activity-filled flask inside the phantom. In addition, the segmented volume was used to determine the centre-of-mass and the change in maximum activity concentration. Results: The results showed a volume increase between 2.7 and 36.3% could be induced by the experimental setup depending on the motion pattern. Both, BrainCompass and MCFLIRT, produced corrected PET images, by reducing the volume increase to 0.7–4.7% (BrainCompass) and to -2.8–0.4% (MCFLIRT). The same was observed for example for the centre-of-mass, where the results show that MCFLIRT (0.2–0.6 mm after motion correction) had a smaller deviation from the reference position than BrainCompass (0.5–1.8 mm) for all displacements. Conclusions: The experimental setup is suitable for the reproducible generation of movement patterns. Using open-source software for motion correction is a viable alternative to the vendor-provided motion-correction software. [ABSTRACT FROM AUTHOR]

BackgroundAdvancements 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.MethodsWe 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.ResultsThe 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.ConclusionCONN-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.

Moreover, given the rich information provided by AI methodologies, molecular imaging probes can also be more accurate in time and space, which not only identifies the location of the tumor but also specifically identifies the tumor staging and completes the time-specific imaging. The MRI/optical imaging bimodal imaging probe has been applied in many studies ([3]), because of its combination of high anatomical resolution from MRI, high sensitivity, and real-time imaging property from optical imaging ([4]). Consequently, improving the performance of the CT devices and developing CT imaging agents with higher contrast and specificity are potential approaches to increasing the accuracy of CT in tumor diagnosis. Keywords: tumor; multi-modal probes; multi-parametric imaging; MRI; CT; fluorescence; PET-CT; PET-MRI EN tumor multi-modal probes multi-parametric imaging MRI CT fluorescence PET-CT PET-MRI 1 4 4 01/18/22 20220114 NES 220114 Preface With the development of multidisciplinary integration, multi-modal imaging has become an important concept that is very popular in relevant research fields and has expanded to accommodate a wide range of advanced technologies. [Extracted from the article]

Suppression of hepatic gluconeogenesis is thought to largely underlie the antidiabetes action of metformin. However, this drug also exerts various effects on the gut, one of which is the enhancement of the uptake of 18F-labeled fluorodeoxyglucose (FDG), a nonmetabolizable glucose derivative, during [18F]FDG positron emission tomography (PET)–computed tomography (CT). Whereas the relevance of this effect to the glucose-lowering action of metformin remains unclear, it is of special interest because it was discovered in humans. Cessation of metformin treatment for several days is required to normalize [18F]FDG uptake in the intestine, suggesting that the enhanced uptake is not a direct effect of the drug in the circulation but rather a prolonged secondary effect. A recent study with state-of-the-art PET–magnetic resonance imaging (MRI), which provides better tissue registration and soft-tissue contrast compared with PET-CT, revealed that metformin-induced accumulation of [18F]FDG occurs primarily in the lumen of the intestine, indicating that the drug promotes excretion of glucose from the circulation into this space. This phenomenon does not necessarily imply that metformin stimulates the removal of glucose from the body in the stool. Instead, it might be related to changes in the abundance and metabolism of the gut microbiota induced by metformin. Further studies of this effect of metformin might shed light on the unanswered questions that still remain concerning the clinical action of this old drug. [ABSTRACT FROM AUTHOR]

Abstract Background Whether routine lymph node dissection for early endometrial cancer is beneficial to survival is still controversial. However, surgeons usually perform lymph node dissection on all patients with early endometrial cancer. This study aimed to prove that the risk of lymph node metastasis, as defined by our standard, is very low in such patients and may change the current surgical practice. Methods 36 consecutive patients who had staged surgery for endometrial cancer were collected. All eligible patients meet the following very low risk criteria for lymph node metastasis, including: (1) preoperative diagnosis of endometrial cancer (preoperative pathological diagnosis), (2) tumors confined to the uterine cavity and not beyond the uterine body, (3) PET-MRI lymph node metastasis test is negative. PET-MRI and pathological examination were used to assess the extent and size of the tumor, the degree of muscular invasion, and lymph node metastasis. Results The median age at diagnosis was 52 years (range 35–72 years). The median tumor size on PET-MRI was 2.82 cm (range 0.66–6.37 cm). Six patients underwent robotic surgery, 20 underwent laparoscopic surgery, 8 underwent Laparoscopic-assisted vaginal hysterectomy, and 2 underwent vaginal hysterectomy. 23% (63.9%) patients had high-grade (i.e. 2 and 3) tumors. Among the 36 patients who underwent lymph node sampling, the median number of lymph nodes retrieved was 32 (range 9–57 nodules). No patient (0%) was diagnosed with lymph node metastasis. According to the policy of each institution, 8 patients (22.2%) received adjuvant therapy, and half of them also received chemotherapy (4 patients; 50%). Conclusions None of the patients who met the criteria had a pathological assessment of lymph node metastasis. Omitting lymph node dissection may be reasonable for patients who meet our criteria.

Abstract Background The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) (PET-MRI) is a unique hybrid imaging modality mainly used in oncology and neurology. The MRI-based attenuation correction (MRAC) is crucial for correct quantification of PET data. A suitable phantom to validate quantitative results in PET-MRI is currently missing. In particular, the correction of attenuation due to bone is usually not verified by commonly available phantoms. The aim of this work was, thus, the development of such a phantom and to explore whether such a phantom might be used to validate MRACs. Method Various materials were investigated for their attenuation and MR properties. For the substitution of bone, water-saturated gypsum plaster was used. The attenuation of 511 keV annihilation photons was regulated by addition of iodine. Adipose tissue was imitated by silicone and brain tissue by agarose gel, respectively. The practicability with respect to the comparison of MRACs was checked as follows: A small flask inserted into the phantom and a large spherical phantom (serving as a reference with negligible error in MRAC) were filled with the very same activity concentration. The activity concentration was measured and compared using clinical protocols on PET-MRI and different built-in and offline MRACs. The same measurements were carried out using PET-CT for comparison. Results The phantom imitates the human head in sufficient detail. All tissue types including bone were detected as such so that the phantom-based comparison of the quantification accuracy of PET-MRI was possible. Quantitatively, the activity concentration in the brain, which was determined using different MRACs, showed a deviation of about 5% on average and a maximum deviation of 11% compared to the spherical phantom. For PET-CT, the deviation was 5%. Conclusions The comparatively small error in quantification indicates that it is possible to construct a brain PET-MRI phantom that leads to MR-based attenuation-corrected images with reasonable accuracy.

Abstract Objectives To decipher the correlations between PET and DCE kinetic parameters in non-small-cell lung cancer (NSCLC), by using voxel-wise analysis of dynamic simultaneous [18F]FDG PET-MRI. Material and methods Fourteen treatment-naïve patients with biopsy-proven NSCLC prospectively underwent a 1-h dynamic [18F]FDG thoracic PET-MRI scan including DCE. The PET and DCE data were normalized to their corresponding T1-weighted MR morphological space, and tumors were masked semi-automatically. Voxel-wise parametric maps of PET and DCE kinetic parameters were computed by fitting the dynamic PET and DCE tumor data to the Sokoloff and Extended Tofts models respectively, by using in-house developed procedures. Curve-fitting errors were assessed by computing the relative root mean square error (rRMSE) of the estimated PET and DCE signals at the voxel level. For each tumor, Spearman correlation coefficients (r s) between all the pairs of PET and DCE kinetic parameters were estimated on a voxel-wise basis, along with their respective bootstrapped 95% confidence intervals (n = 1000 iterations). Results Curve-fitting metrics provided fit errors under 20% for almost 90% of the PET voxels (median rRMSE = 10.3, interquartile ranges IQR = 8.1; 14.3), whereas 73.3% of the DCE voxels showed fit errors under 45% (median rRMSE = 31.8%, IQR = 22.4; 46.6). The PET-PET, DCE-DCE, and PET-DCE voxel-wise correlations varied according to individual tumor behaviors. Beyond this wide variability, the PET-PET and DCE-DCE correlations were mainly high (absolute r s values > 0.7), whereas the PET-DCE correlations were mainly low to moderate (absolute r s values < 0.7). Half the tumors showed a hypometabolism with low perfused/vascularized profile, a hallmark of hypoxia, and tumor aggressiveness. Conclusion A dynamic “one-stop shop” procedure applied to NSCLC is technically feasible in clinical practice. PET and DCE kinetic parameters assessed simultaneously are not highly correlated in NSCLC, and these correlations showed a wide variability among tumors and patients. These results tend to suggest that PET and DCE kinetic parameters might provide complementary information. In the future, this might make PET-MRI a unique tool to characterize the individual tumor biological behavior in NSCLC.

Abstract Background The undifferentiated embryonic sarcoma of the liver (UESL) is a rare, aggressive tumor mainly affecting children. Since UESL has no specific clinical symptoms or imaging characteristics, many cases of UESL are diagnosed late. The paraneoplastic leukemoid reaction (PLR) is a very rare concomitant of oncological patients associated with poor prognosis. This report describes the clinical course of a patient combining these two rare entities and describes the diagnostic challenges and dynamics of paraneoplastic syndrome. Case presentation We report a case of UESL in a 46-year-old male who became clinically conspicuous due to pronounced B symptoms. CT and MRI showed a suspicious unifocal liver lesion. As the histological analysis of a tissue sample did not reveal a clear result, an 18F-FDG-PET-CT examination was performed. In addition to a high glucose metabolism of the liver lesion, an increased glucose metabolism in the entire bone marrow was observed. This finding was considered as pronounced paraneoplasia and laparotomy with liver segment resection followed. Immediately after resection of the tumor the paraneoplastic symptoms completely declined and the patient showed no signs of recurrence in the 1-year follow-up. Conclusions Although UESL is rare and predominantly affects children, this diagnosis should always be considered for unclear unifocal cystic liver lesions, regardless of the patient’s age, as appropriate treatment has a good prognosis.

BackgroundThis study aimed to explore the radiomic features from PET images to detect active cardiac sarcoidosis (CS).MethodsForty sarcoid patients and twenty-nine controls were scanned using FDG PET-CMR. Five feature classes were compared between the groups. From the PET images alone, two different segmentations were drawn. For segmentation A, a region of interest (ROI) was manually delineated for the patients' myocardium hot regions with standardized uptake value (SUV) higher than 2.5 and the controls' normal myocardium region. A second ROI was drawn in the entire left ventricular myocardium for both study groups, segmentation B. The conventional metrics and radiomic features were then extracted for each ROI. Mann-Whitney U-test and a logistic regression classifier were used to compare the individual features of the study groups.ResultsFor segmentation A, the SUVmin had the highest area under the curve (AUC) and greatest accuracy among the conventional metrics. However, for both segmentations, the AUC and accuracy of the TBRmax were relatively high, >0.85. Twenty-two (from segmentation A) and thirty-five (from segmentation B) of 75 radiomic features fulfilled the criteria: P-value < 0.00061 (after Bonferroni correction), AUC >0.5, and accuracy >0.7. Principal Component Analysis (PCA) was conducted, with five components leading to cumulative variance higher than 90%. Ten machine learning classifiers were then tested and trained. Most of them had AUCs and accuracies ≥0.8. For segmentation A, the AUCs and accuracies of all classifiers are >0.9, but k-neighbors and neural network classifiers were the highest (=1). For segmentation B, there are four classifiers with AUCs and accuracies ≥0.8. However, the gaussian process classifier indicated the highest AUC and accuracy (0.9 and 0.8, respectively).ConclusionsRadiomic analysis of the specific PET data was not proven to be necessary for the detection of CS. However, building an automated procedure will help to accelerate the analysis and potentially lead to more reproducible findings across different scanners and imaging centers and consequently improve standardization procedures that are important for clinical trials and development of more robust diagnostic protocols.

Background: Amino acid positron emission tomography (PET) imaging plays a significant role in the diagnosis of gliomas and in differentiating tumor recurrence from necrosis. In this study, the authors evaluated the diagnostic efficacy of [ 99m Tc]Tc-methionine single-photon emission computed tomography-computed tomography (SPECT-CT) in comparison with [ 11 C]methionine PET-magnetic resonance imaging (MRI) in delineating tumors. Methods: Thirty-one (primary: 16 and postoperative: 15) patients of confirmed (either MRI or histopathological proven) glioma underwent both [ 99m Tc]Tc-methionine SPECT-CT and [ 11 C]methionine PET-MRI. A comparative analysis was performed between SPECT, PET, and MR images to calculate the concordance between the modalities and to evaluate the diagnostic efficacy of the [ 99m Tc]Tc-methionine SPECT. Results: [ 99m Tc]Tc-methionine SPECT showed comparable uptake in the tumor lesions in comparison to [ 11 C]methionine PET. A significant and strong positive correlation was observed between the volume of tumor (Vt) in PET and Vt MR ( p  < 0.004). Likewise, a significant and strong positive correlation was found between Vt SPECT and Vt MR. [ 99m Tc]-methionine has a sensitivity and specificity of 91% and 75%, respectively, compared with 82% and 100% for [ 11 C]methionine in postoperative cases to differentiate the tumor recurrence from necrosis. The sensitivity and specificity of [ 99m Tc]Tc-methionine was 92% and 100%, respectively, compared with 92% and 67% for [ 11 C]methionine in primary tumors. Conclusion: [ 99m Tc]Tc-methionine SPECT-CT is as equally good as [ 11 C]methionine for diagnosing and differentiating it from necrosis especially in high-grade glioma.

Background: Graft versus host disease (GvHD) is a frequent complication of allogeneic stem cell transplantation (alloSCT), significantly increasing mortality. Previous imaging studies focused on the assessment of intestinal GvHD with contrast-enhanced MRI/CT or 18F-FDG-PET imaging alone. The objective of this retrospective study was to elucidate the diagnostic value of a combined 18F-FDG-PET-MRI protocol in patients with acute intestinal GvHD.Methods: Between 2/2015 and 8/2019, 21 patients with acute intestinal GvHD underwent 18F-FDG-PET-MRI. PET, MRI and PET-MRI datasets were independently reviewed. Readers assessed the number of affected segments of the lower gastrointestinal tract and the reliability of the diagnosis on a 5-point Likert scale and quantitative PET (SUVmax, SUVpeak, metabolic volume (MV)) and MRI parameter (wall thickness), were correlated to clinical staging of acute intestinal GvHD.Results: The detection rate for acute intestinal GvHD was 56.8% for PET, 61.4% for MRI and 100% for PET-MRI. PET-MRI (median Likert-scale value: 5; range: 4-5) offers a significantly higher reliability of the diagnosis compared to PET (median: 4; range: 2-5; p = 0.01) and MRI alone (median: 4; range: 3-5; p = 0.03). The number of affected segments in PET-MRI (rs = 0.677; p <  0.001) and the MV (rs = 0.703; p <  0.001) correlated significantly with the clinical stage. SUVmax (rs = 0.345; p = 0.14), SUVpeak (rs = 0.276; p = 0.24) and wall thickening (rs = 0.174; p = 0.17) did not show a significant correlation to clinical stage.Conclusion: 18F-FDG-PET-MRI allows for highly reliable assessment of acute intestinal GvHD and adds information indicating clinical severity. [ABSTRACT FROM AUTHOR]

Accurate localization of the epileptogenic zone (EZ) is a key factor to obtain good surgical outcome for refractory epilepsy patients. However, no technique, so far, can precisely locate the EZ, and there are barely any reports on the combined application of multiple technologies to improve the localization accuracy of the EZ. In this study, we aimed to explore the use of a multimodal method combining PET-MRI, fluid and white matter suppression (FLAWS)—a novel MRI sequence, and high-frequency oscillation (HFO) automated analysis to delineate EZ. We retrospectively collected 15 patients with refractory epilepsy who underwent surgery and used the above three methods to detect abnormal brain areas of all patients. We compared the PET-MRI, FLAWS, and HFO results with traditional methods to evaluate their diagnostic value. The sensitivities, specificities of locating the EZ, and marking extent removed versus not removed [RatioChann(ev)] of each method were compared with surgical outcome. We also tested the possibility of using different combinations to locate the EZ. The marked areas in every patient established using each method were also compared to determine the correlations among the three methods. The results showed that PET-MRI, FLAWS, and HFOs can provide more information about potential epileptic areas than traditional methods. When detecting the EZs, the sensitivities of PET-MRI, FLAWS, and HFOs were 68.75, 53.85, and 87.50%, and the specificities were 80.00, 33.33, and 100.00%. The RatioChann(ev) of HFO-marked contacts was significantly higher in patients with good outcome than those with poor outcome (p< 0.05). When intracranial electrodes covered all the abnormal areas indicated by neuroimaging with the overlapping EZs being completely removed referred to HFO analysis, patients could reach seizure-free (p < 0.01). The periphery of the lesion marked by neuroimaging may be epileptic, but not every lesion contributes to seizures. Therefore, approaches in multimodality can detect EZ more accurately, and HFO analysis may help in defining real epileptic areas that may be missed in the neuroimaging results. The implantation of intracranial electrodes guided by non-invasive PET-MRI and FLAWS findings as well as HFO analysis would be an optimized multimodal approach for locating EZ.

Introduction: The assessment of ex vivo biodistribution is the preferred method for quantification of radiotracers biodistribution in preclinical models, but is not in line with current ethics on animal research. PET imaging allows for noninvasive longitudinal evaluation of tracer distribution in the same animals, but systemic comparison with ex vivo biodistribution is lacking. Our aim was to evaluate the potential of preclinical PET imaging for accurate tracer quantification, especially in tumor models. Methods: NEMA NU 4-2008 phantoms were filled with 11C, 68Ga, 18F, or 89Zr solutions and scanned in Mediso nanoPET/CT and PET/MR scanners until decay. N87 tumor-bearing mice were i.v. injected with either [18F]FDG (~ 14 MBq), kept 50 min under anesthesia followed by imaging for 20 min, or with [89Zr]Zr-DFO-NCS-trastuzumab (~ 5 MBq) and imaged 3 days post-injection for 45 min. After PET acquisition, animals were killed and organs of interest were collected and measured in a γ-counter to determine tracer uptake levels. PET data were reconstructed using TeraTomo reconstruction algorithm with attenuation and scatter correction and regions of interest were drawn using Vivoquant software. PET imaging and ex vivo biodistribution were compared using Bland–Altman plots. Results: In phantoms, the highest recovery coefficient, thus the smallest partial volume effect, was obtained with 18F for both PET/CT and PET/MR. Recovery was slightly lower for 11C and 89Zr, while the lowest recovery was obtained with 68Ga in both scanners. In vivo, tumor uptake of the 18F- or 89Zr-labeled tracer proved to be similar irrespective whether quantified by either PET/CT and PET/MR or ex vivo biodistribution with average PET/ex vivo ratios of 0.8–0.9 and a deviation of 10% or less. Both methods appeared less congruent in the quantification of tracer uptake in healthy organs such as brain, kidney, and liver, and depended on the organ evaluated and the radionuclide used. Conclusions: Our study suggests that PET quantification of 18F- and 89Zr-labeled tracers is reliable for the evaluation of tumor uptake in preclinical models and a valuable alternative technique for ex vivo biodistribution. However, PET and ex vivo quantification require fully described experimental and analytical procedures for reliability and reproducibility. [ABSTRACT FROM AUTHOR]