The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights.

Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking.

Mitigating SUV uncertainties using total body PET imaging.

PURPOSE: Standardised uptake values (SUV) are commonly used to quantify 18F-FDG lesion uptake. However, SUVs may suffer from several uncertainties and errors. Long-axial field-of-view (LAFOV) PET/CT systems might enable image-based quality control (QC) by deriving 18F-FDG activity and weight from total body (TB) 18F-FDG PET images. In this study, we aimed to develop these image-based QC to reduce errors and mitigate SUV uncertainties. METHODS: Twenty-five out of 81 patient scans from a LAFOV PET/CT system were used to determine regression fits for deriving of image-derived activity and weight. Thereafter, the regression fits were applied to 56 independent 18F-FDG PET scans from the same scanner to determine if injected activity and weight could be obtained accurately from TB and half-body (HB) scans. Additionally, we studied the impact of image-based values on the precision of liver SUVmean and lesion SUVpeak. Finally, 20 scans were acquired from a short-axial field-of-view (SAFOV) PET/CT system to determine if the regression fits also applied to HB scans from a SAFOV system. RESULTS: Both TB and HB 18F-FDG activity and weight significantly predicted reported injected activity (r = 0.999; r = 0.984) and weight (r = 0.999; r = 0.987), respectively. After applying the regression fits, 18F-FDG activity and weight were accurately derived within 4.8% and 3.2% from TB scans and within 4.9% and 3.1% from HB, respectively. Image-derived values also mitigated liver and lesion SUV variability compared with reported values. Moreover, 18F-FDG activity and weight obtained from a SAFOV scanner were derived within 6.7% and 4.5%, respectively. CONCLUSION: 18F-FDG activity and weight can be derived accurately from TB and HB scans, and image-derived values improved SUV precision and corrected for lesion SUV errors. Therefore, image-derived values should be included as QC to generate a more reliable and reproducible quantitative uptake measurement.

EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy.

Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy surgery is a treatment option depending on the localisation of the seizure focus for seizure relief or seizure freedom with consecutive improvement in quality of life. Beside examinations such as scalp video/electroencephalography (EEG) telemetry, structural, and functional magnetic resonance imaging (MRI), which are primary standard tools for the diagnostic work-up and therapy management of epilepsy patients, molecular neuroimaging using different radiopharmaceuticals with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) influences and impacts on therapy decisions. To date, there are no literature-based praxis recommendations for the use of Nuclear Medicine (NM) imaging procedures in epilepsy. The aims of these guidelines are to assist in understanding the role and challenges of radiotracer imaging for epilepsy; to provide practical information for performing different molecular imaging procedures for epilepsy; and to provide an algorithm for selecting the most appropriate imaging procedures in specific clinical situations based on current literature. These guidelines are written and authorized by the European Association of Nuclear Medicine (EANM) to promote optimal epilepsy imaging, especially in the presurgical setting in children, adolescents, and adults with focal epilepsy. They will assist NM healthcare professionals and also specialists such as Neurologists, Neurophysiologists, Neurosurgeons, Psychiatrists, Psychologists, and others involved in epilepsy management in the detection and interpretation of epileptic seizure onset zone (SOZ) for further treatment decision. The information provided should be applied according to local laws and regulations as well as the availability of various radiopharmaceuticals and imaging modalities.

Pharmacokinetic analysis and simplified uptake measures for tumour lesion [18F]F-AraG PET imaging in patients with non-small cell lung cancer.

INTRODUCTION: The novel positron emission tomography (PET) imaging tracer, [18F]F-AraG, targets activated T-cells, offering a potential means to improve our understanding of immune-oncological processes. The aim of this study was to determine the optimal pharmacokinetic model to quantify tumour lesion [18F]F-AraG uptake in patients with non-small cell lung cancer (NSCLC), and to validate simplified measures at different time intervals against the pharmacokinetic uptake parameter. METHODS: Ten patients with early-stage NSCLC and three patients with advanced NSCLC underwent a dynamic PET scan of minimal 60 min. Venous and/or arterial blood sampling was obtained at maximum seven time points. Tumour lesion time activity curves and metabolite-corrected input functions were analysed using single-tissue reversible (1T2k), two-tissue irreversible (2T3k) and two-tissue reversible (2T4k) plasma input models. Simplified uptake measures, such as standardised uptake value (SUV) and tumour-to-blood (TBR) or tumour-to-plasma ratio (TPR), were evaluated for different time intervals. RESULTS: Whole-blood and plasma radioactivity concentrations showed rapid clearance of [18F]F-AraG. Metabolite analysis revealed a low rate of metabolism, at 70 min p.i., on average, 79% (SD = 9.8%) of the total radioactivity found in blood corresponded to intact [18F]F-AraG. The time activity curves were best fitted by the 2T3k model. Strong positive correlations were found for SUV (body weight (BW), lean body mass (LBM) or body surface area (BSA) corrected), TBR and TPR for any time interval between 20 and 70 min p.i. against the 2T3k-derived Ki. The correlation of TBR at 60-70 min p.i. with 2T3K-derived Ki (r (df = 20) = 0.87, p < 0.01), was stronger than for SUVBW (r (df = 20) = 0.80, p < 0.01). CONCLUSION: Tumour lesion [18F]F-AraG uptake in patients with NSCLC is characterised by a 2T3k model. TBR and TPR show most potential for simplified quantification of tumour lesion [18F]F-AraG uptake in patients with NSCLC.

Investigating reliable amyloid accumulation in Centiloids: Results from the AMYPAD Prognostic and Natural History Study.

INTRODUCTION: To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-ß (Aß) accumulation based on Centiloids (CL) in pre-dementia populations. METHODS: A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models. RESULTS: Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aß-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education. DISCUSSION: Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.

MRI Features for Identifying MYCN-amplified RB1 Wild-type Retinoblastoma.

Background MYCN-amplified RB1 wild-type (MYCNARB1+/+) retinoblastoma is a rare but clinically important subtype of retinoblastoma due to its aggressive character and relative resistance to typical therapeutic approaches. Because biopsy is not indicated in retinoblastoma, specific MRI features might be valuable to identify children with this genetic subtype. Purpose To define the MRI phenotype of MYCNARB1+/+ retinoblastoma and evaluate the ability of qualitative MRI features to help identify this specific genetic subtype. Materials and Methods In this retrospective, multicenter, case-control study, MRI scans in children with MYCNARB1+/+ retinoblastoma and age-matched children with RB1-/- subtype retinoblastoma were included (case-control ratio, 1:4; scans acquired from June 2001 to February 2021; scans collected from May 2018 to October 2021). Patients with histopathologically confirmed unilateral retinoblastoma, genetic testing (RB1/MYCN status), and MRI scans were included. Associations between radiologist-scored imaging features and diagnosis were assessed with the Fisher exact test or Fisher-Freeman-Halton test, and Bonferroni-corrected P values were calculated. Results A total of 110 patients from 10 retinoblastoma referral centers were included: 22 children with MYCNARB1+/+ retinoblastoma and 88 control children with RB1-/- retinoblastoma. Children in the MYCNARB1+/+ group had a median age of 7.0 months (IQR, 5.0-9.0 months) (13 boys), while children in the RB1-/- group had a median age of 9.0 months (IQR, 4.6-13.4 months) (46 boys). MYCNARB1+/+ retinoblastomas were typically peripherally located (in 10 of 17 children; specificity, 97%; P < .001) and exhibited plaque or pleomorphic shape (in 20 of 22 children; specificity, 51%; P = .011) with irregular margins (in 16 of 22 children; specificity, 70%; P = .008) and extensive retina folding with vitreous enclosure (specificity, 94%; P < .001). MYCNARB1+/+ retinoblastomas showed peritumoral hemorrhage (in 17 of 21 children; specificity, 88%; P < .001), subretinal hemorrhage with a fluid-fluid level (in eight of 22 children; specificity, 95%; P = .005), and strong anterior chamber enhancement (in 13 of 21 children; specificity, 80%; P = .008). Conclusion MYCNARB1+/+ retinoblastomas show distinct MRI features that could enable early identification of these tumors. This may improve patient selection for tailored treatment in the future. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Rollins in this issue.

A multi-label CNN model for the automatic detection and segmentation of gliomas using [18F]FET PET imaging.

PURPOSE: The aim of this study was to develop a convolutional neural network (CNN) for the automatic detection and segmentation of gliomas using [18F]fluoroethyl-L-tyrosine ([18F]FET) PET. METHODS: Ninety-three patients (84 in-house/7 external) who underwent a 20-40-min static [18F]FET PET scan were retrospectively included. Lesions and background regions were defined by two nuclear medicine physicians using the MIM software, such that delineations by one expert reader served as ground truth for training and testing the CNN model, while delineations by the second expert reader were used to evaluate inter-reader agreement. A multi-label CNN was developed to segment the lesion and background region while a single-label CNN was implemented for a lesion-only segmentation. Lesion detectability was evaluated by classifying [18F]FET PET scans as negative when no tumor was segmented and vice versa, while segmentation performance was assessed using the dice similarity coefficient (DSC) and segmented tumor volume. The quantitative accuracy was evaluated using the maximal and mean tumor to mean background uptake ratio (TBRmax/TBRmean). CNN models were trained and tested by a threefold cross-validation (CV) using the in-house data, while the external data was used for an independent evaluation to assess the generalizability of the two CNN models. RESULTS: Based on the threefold CV, the multi-label CNN model achieved 88.9% sensitivity and 96.5% precision for discriminating between positive and negative [18F]FET PET scans compared to a 35.3% sensitivity and 83.1% precision obtained with the single-label CNN model. In addition, the multi-label CNN allowed an accurate estimation of the maximal/mean lesion and mean background uptake, resulting in an accurate TBRmax/TBRmean estimation compared to a semi-automatic approach. In terms of lesion segmentation, the multi-label CNN model (DSC = 74.6 ± 23.1%) demonstrated equal performance as the single-label CNN model (DSC = 73.7 ± 23.2%) with tumor volumes estimated by the single-label and multi-label model (22.9 ± 23.6 ml and 23.1 ± 24.3 ml, respectively) closely approximating the tumor volumes estimated by the expert reader (24.1 ± 24.4 ml). DSCs of both CNN models were in line with the DSCs by the second expert reader compared with the lesion segmentations by the first expert reader, while detection and segmentation performance of both CNN models as determined with the in-house data were confirmed by the independent evaluation using external data. CONCLUSION: The proposed multi-label CNN model detected positive [18F]FET PET scans with high sensitivity and precision. Once detected, an accurate tumor segmentation and estimation of background activity was achieved resulting in an automatic and accurate TBRmax/TBRmean estimation, such that user interaction and potential inter-reader variability can be minimized.

Reproducibility of [18F]FDG PET/CT liver SUV as reference or normalisation factor.

INTRODUCTION: Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics. METHODS: PET/CT scans from 34 lymphoma patients were used to calculate SUVmaxliver, SUVpeakliver and SUVmeanliver as a function of (1) volume-of-interest (VOI) size, (2) location, (3) imaging time point and (4) as a function of total metabolic tumour volume (MTV). The impact of reconstruction protocol on liver uptake is studied on 15 baseline lymphoma patient scans. The effect of noise on liver SUV was assessed using full and 25% count images of 15 lymphoma scans. RESULTS: Generally, SUVmaxliver and SUVpeakliver were 38% and 16% higher compared to SUVmeanliver. SUVmaxliver and SUVpeakliver increased up to 31% and 15% with VOI size while SUVmeanliver remained unchanged with the lowest variability for the largest VOI size. Liver uptake metrics were not affected by VOI location. Compared to baseline, liver uptake metrics were 15-18% and 9-18% higher at interim and EoT PET, respectively. SUVliver decreased with larger total MTVs. SUVmaxliver and SUVpeakliver were affected by reconstruction protocol up to 62%. SUVmax and SUVpeak moved 22% and 11% upward between full and 25% count images. CONCLUSION: SUVmeanliver was most robust against VOI size, location, reconstruction protocol and image noise level, and is thus the most reproducible metric for liver uptake. The commonly recommended 3 cm diameter spherical VOI-based SUVmeanliver values were only slightly more variable than those seen with larger VOI sizes and are sufficient for SUVmeanliver measurements in future studies. TRIAL REGISTRATION: EudraCT: 2006-005,174-42, 01-08-2008.

Validation of simplified uptake measures against dynamic Patlak Ki for quantification of lesional 89Zr-Immuno-PET antibody uptake.

PURPOSE: Positron emission tomography imaging of zirconium-89-labelled monoclonal antibodies (89Zr-Immuno-PET) allows for visualisation and quantification of antibody uptake in tumours in vivo. Patlak linearization provides distribution volume (VT) and nett influx rate (Ki) values, representing reversible and irreversible uptake, respectively. Standardised uptake value (SUV) and tumour-to-plasma/tumour-to-blood ratio (TPR/TBR) are often used, but their validity depends on the comparability of plasma kinetics and clearances. This study assesses the validity of SUV, TPR and TBR against Patlak Ki for quantifying irreversible 89Zr-Immuno-PET uptake in tumours. METHODS: Ten patients received 37 MBq 10 mg 89Zr-anti-EGFR with 500 mg/m2 unlabelled mAbs. Five patients received two doses of 37 MBq 89Zr-anti-HER3: 8-24 mg for the first administration and 24 mg-30 mg/kg for the second. Seven tumours from four patients showed 89Zr-anti-EGFR uptake, and 18 tumours from five patients showed 89Zr-anti-HER3 uptake. SUVpeak, TPRpeak and TBRpeak values were obtained from one to six days p.i. Patlak linearization was applied to tumour time activity curves and plasma samples to obtain Ki. RESULTS: For 89Zr-anti-EGFR, there was a small variability along the linear regression line between SUV (- 0.51-0.57), TPR (- 0.06‒0.11) and TBR (- 0.13‒0.16) on day 6 versus Ki. Similar doses of 89Zr-anti-HER3 showed similar variability for SUV (- 1.3‒1.0), TPR (- 1.1‒0.53) and TBR (- 1.5‒0.72) on day 5 versus Ki. However, for the second administration of 89Zr-anti-HER3 with a large variability in administered mass doses, SUV showed a larger variability (- 1.4‒2.3) along the regression line with Ki, which improved when using TPR (- 0.38-0.32) or TBR (- 0.56‒0.46). CONCLUSION: SUV, TPR and TBR at late time points were valid for quantifying irreversible lesional 89Zr-Immuno-PET uptake when constant mass doses were administered. However, for variable mass doses, only TPR and TBR provided reliable values for irreversible uptake, but not SUV, because SUV does not take patient and mass dose-specific plasma clearance into account.

Optimisation of scan duration and image quality in oncological 89Zr immunoPET imaging using the Biograph Vision PET/CT.

PURPOSE: Monoclonal antibody (mAb)-based PET (immunoPET) imaging can characterise tumour lesions non-invasively. It may be a valuable tool to determine which patients may benefit from treatment with a specific monoclonal antibody (mAb) and evaluate treatment response. For 89Zr immunoPET imaging, higher sensitivity of state-of-the art PET/CT systems equipped with silicon photomultiplier (SiPM)-based detector elements may be beneficial as the low positron abundance of 89Zr causes a low signal-to-noise level. Moreover, the long physical half-life limits the amount of activity that can be administered to the patients leading to poor image quality even when using long scan durations. Here, we investigated the difference in semiquantitative performance between the PMT-based Biograph mCT, our clinical reference system, and the SiPM-based Biograph Vision PET/CT in 89Zr immunoPET imaging. Furthermore, the effects of scan duration reduction using the Vision on semiquantitative imaging parameters and its influence on image quality assessment were evaluated. METHODS: Data were acquired on day 4 post 37 MBq 89Zr-labelled mAb injection. Five patients underwent a double scan protocol on both systems. Ten patients were scanned only on the Vision. For PET image reconstruction, three protocols were used, i.e. one camera-dependent protocol and European Association of Nuclear Medicine Research Limited (EARL) standards 1 and 2 compliant protocols. Vision data were acquired in listmode and were reprocessed to obtain images at shorter scan durations. Semiquantitative PET image parameters were derived from tumour lesions and healthy tissues to assess differences between systems and scan durations. Differently reconstructed images obtained using the Vision were visually scored regarding image quality by two nuclear medicine physicians. RESULTS: When images were reconstructed using 100% acquisition time on both systems following EARL standard 1 compliant reconstruction protocols, results regarding semiquantification were comparable. For Vision data, reconstructed images that conform to EARL1 standards still resulted in comparable semiquantification at shorter scan durations (75% and 50%) regarding 100% acquisition time. CONCLUSION: Scan duration of 89Zr immunoPET imaging using the Vision can be decreased up to 50% compared with using the mCT while maintaining image quality using the EARL1 compliant reconstruction protocol.

Quantification of P-glycoprotein function at the human blood-brain barrier using [18F]MC225 and PET.

INTRODUCTION: P-glycoprotein (P-gp) is one of the most studied efflux transporters at the blood-brain barrier. It plays an important role in brain homeostasis by protecting the brain from a variety of endogenous and exogeneous substances. Changes in P-gp function are associated both with the onset of neuropsychiatric diseases, including Alzheimer's disease and Parkinson's disease, and with drug-resistance, for example in treatment-resistant depression. The most widely used approach to measure P-gp function in vivo is (R)-[11C]verapamil PET. (R)-[11C]verapamil is, however, an avid P-gp substrate, which complicates the use of this tracer to measure an increase in P-gp function as its baseline uptake is already very low. [18F]MC225 was developed to measure both increases and decreases in P-gp function. AIM: The aim of this study was (1) to identify the pharmacokinetic model that best describes [18F]MC225 kinetics in the human brain and (2) to determine test-retest variability. METHODS: Five (2 male, 3 female) of fourteen healthy subjects (8 male, 6 female, age 67 ± 5 years) were scanned twice (injected dose 201 ± 47 MBq) with a minimum interval of 2 weeks between scans. Each scanning session consisted of a 60-min dynamic [18F]MC225 scan with continuous arterial sampling. Whole brain grey matter data were fitted to a single tissue compartment model, and to reversible and irreversible two tissue-compartment models to obtain various outcome parameters (in particular the volume of distribution (VT), Ki, and the rate constants K1 and k2). In addition, a reversible two-tissue compartment model with fixed k3/k4 was included. The preferred model was selected based on the weighted Akaike Information Criterion (AIC) score. Test-retest variability (TRTV) was determined to assess reproducibility. RESULTS: Sixty minutes post-injection, the parent fraction was 63.8 ± 4.0%. The reversible two tissue compartment model corrected for plasma metabolites with an estimated blood volume (VB) showed the highest AIC weight score of 34.3 ± 17.6%. The TRVT of the VT for [18F]MC225 PET scans was 28.3 ± 20.4% for the whole brain grey matter region using this preferred model. CONCLUSION: [18F]MC225 VT, derived using a reversible two-tissue compartment model, is the preferred parameter to describe P-gp function in the human BBB. This outcome parameter has an average test-retest variability of 28%. TRIAL REGISTRATION: EudraCT 2020-001564-28 . Registered 25 May 2020.

International EANM-SNMMI-ISMRM consensus recommendation for PET/MRI in oncology.

PREAMBLE: The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote the science, technology, and practical application of nuclear medicine. The European Association of Nuclear Medicine (EANM) is a professional non-profit medical association that facilitates communication worldwide between individuals pursuing clinical and research excellence in nuclear medicine. The EANM was founded in 1985. The merged International Society for Magnetic Resonance in Medicine (ISMRM) is an international, nonprofit, scientific association whose purpose is to promote communication, research, development, and applications in the field of magnetic resonance in medicine and biology and other related topics and to develop and provide channels and facilities for continuing education in the field.The ISMRM was founded in 1994 through the merger of the Society of Magnetic Resonance in Medicine and the Society of Magnetic Resonance Imaging. SNMMI, ISMRM, and EANM members are physicians, technologists, and scientists specializing in the research and practice of nuclear medicine and/or magnetic resonance imaging. The SNMMI, ISMRM, and EANM will periodically define new guidelines for nuclear medicine practice to help advance the science of nuclear medicine and/or magnetic resonance imaging and to improve the quality of service to patients throughout the world. Existing practice guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated. Each practice guideline, representing a policy statement by the SNMMI/EANM/ISMRM, has undergone a thorough consensus process in which it has been subjected to extensive review. The SNMMI, ISMRM, and EANM recognize that the safe and effective use of diagnostic nuclear medicine imaging and magnetic resonance imaging requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guideline by those entities not providing these services is not authorized. These guidelines are an educational tool designed to assist practitioners in providing appropriate care for patients. They are not inflexible rules or requirements of practice and are not intended, nor should they be used, to establish a legal standard of care. For these reasons and those set forth below, the SNMMI, the ISMRM, and the EANM caution against the use of these guidelines in litigation in which the clinical decisions of a practitioner are called into question. The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by the physician or medical physicist in light of all the circumstances presented. Thus, there is no implication that an approach differing from the guidelines, standing alone, is below the standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources, or advances in knowledge or technology subsequent to publication of the guidelines. The practice of medicine includes both the art and the science of the prevention, diagnosis, alleviation, and treatment of disease. The variety and complexity of human conditions make it impossible to always reach the most appropriate diagnosis or to predict with certainty a particular response to treatment. Therefore, it should be recognized that adherence to these guidelines will not ensure an accurate diagnosis or a successful outcome. All that should be expected is that the practitioner will follow a reasonable course of action based on current knowledge, available resources, and the needs of the patient to deliver effective and safe medical care. The sole purpose of these guidelines is to assist practitioners in achieving this objective.

Cerebral blood flow, amyloid burden, and cognition in cognitively normal individuals.

PURPOSE: The role of cerebral blood flow (CBF) in the early stages of Alzheimer's disease is complex and largely unknown. We investigated cross-sectional and longitudinal associations between CBF, amyloid burden, and cognition, in cognitively normal individuals with subjective cognitive decline (SCD). METHODS: We included 187 cognitively normal individuals with SCD from the SCIENCe project (65 ± 8 years, 39% F, MMSE 29 ± 1). Each underwent a dynamic (0-70 min) [18F]florbetapir PET and T1-weighted MRI scan, enabling calculation of mean binding potential (BPND; specific amyloid binding) and R1 (measure of relative (r)CBF). Eighty-three individuals underwent a second [18F]florbetapir PET (2.6 ± 0.7 years). Participants annually underwent neuropsychological assessment (follow-up time 3.8 ± 3.1 years; number of observations n = 774). RESULTS: A low baseline R1 was associated with steeper decline on tests addressing memory, attention, and global cognition (range betas 0.01 to 0.27, p < 0.05). High BPND was associated with steeper decline on tests covering all domains (range betas - 0.004 to - 0.70, p < 0.05). When both predictors were simultaneously added to the model, associations remained essentially unchanged. Additionally, we found longitudinal associations between R1 and BPND. High baseline BPND predicted decline over time in R1 (all regions, range betasBP×time - 0.09 to - 0.14, p < 0.05). Vice versa, low baseline R1 predicted increase in BPND in frontal, temporal, and composite ROIs over time (range betasR1×time - 0.03 to - 0.08, p < 0.05). CONCLUSION: Our results suggest that amyloid accumulation and decrease in rCBF are two parallel disease processes without a fixed order, both providing unique predictive information for cognitive decline and each process enhancing the other longitudinally.

External validation of an MR-based radiomic model predictive of locoregional control in oropharyngeal cancer.

OBJECTIVES: To externally validate a pre-treatment MR-based radiomics model predictive of locoregional control in oropharyngeal squamous cell carcinoma (OPSCC) and to assess the impact of differences between datasets on the predictive performance. METHODS: Radiomic features, as defined in our previously published radiomics model, were extracted from the primary tumor volumes of 157 OPSCC patients in a different institute. The developed radiomics model was validated using this cohort. Additionally, parameters influencing performance, such as patient subgroups, MRI acquisition, and post-processing steps on prediction performance will be investigated. For this analysis, matched subgroups (based on human papillomavirus (HPV) status of the tumor, T-stage, and tumor subsite) and a subgroup with only patients with 4-mm slice thickness were studied. Also the influence of harmonization techniques (ComBat harmonization, quantile normalization) and the impact of feature stability across observers and centers were studied. Model performances were assessed by area under the curve (AUC), sensitivity, and specificity. RESULTS: Performance of the published model (AUC/sensitivity/specificity: 0.74/0.75/0.60) drops when applied on the validation cohort (AUC/sensitivity/specificity: 0.64/0.68/0.60). The performance of the full validation cohort improves slightly when the model is validated using a patient group with comparable HPV status of the tumor (AUC/sensitivity/specificity: 0.68/0.74/0.60), using patients acquired with a slice thickness of 4 mm (AUC/sensitivity/specificity: 0.67/0.73/0.57), or when quantile harmonization was performed (AUC/sensitivity/specificity: 0.66/0.69/0.60). CONCLUSION: The previously published model shows its generalizability and can be applied on data acquired from different vendors and protocols. Harmonization techniques and subgroup definition influence performance of predictive radiomics models. KEY POINTS: • Radiomics, a noninvasive quantitative image analysis technique, can support the radiologist by enhancing diagnostic accuracy and/or treatment decision-making. • A previously published model shows its generalizability and could be applied on data acquired from different vendors and protocols.

Functional stress imaging to predict abnormal coronary fractional flow reserve: the PACIFIC 2 study.

AIMS: The diagnostic performance of non-invasive imaging in patients with prior coronary artery disease (CAD) has not been tested in prospective head-to-head comparative studies. The aim of this study was to compare the diagnostic performance of qualitative single-photon emission computed tomography (SPECT), quantitative positron emission tomography (PET), and qualitative magnetic resonance imaging (MRI) in patients with a prior myocardial infarction (MI) or percutaneous coronary intervention (PCI). METHODS AND RESULTS: In this prospective clinical study, all patients with prior MI and/or PCI and new symptoms of ischaemic CAD underwent 99mTc-tetrofosmin SPECT, [15O]H2O PET, and MRI, followed by invasive coronary angiography with fractional flow reserve (FFR) in all coronary arteries. All modalities were interpreted by core laboratories. Haemodynamically significant CAD was defined by at least one coronary artery with an FFR ≤0.80. Among the 189 enrolled patients, 63% had significant CAD. Sensitivity was 67% (95% confidence interval 58-76%) for SPECT, 81% (72-87%) for PET, and 66% (56-75%) for MRI. Specificity was 61% (48-72%) for SPECT, 65% (53-76%) for PET, and 62% (49-74%) for MRI. Sensitivity of PET was higher than SPECT (P = 0.016) and MRI (P = 0.014), whereas specificity did not differ among the modalities. Diagnostic accuracy for PET (75%, 68-81%) did not statistically differ from SPECT (65%, 58-72%, P = 0.03) and MRI (64%, 57-72%, P = 0.052). Using FFR < 0.75 as a reference, accuracies increased to 69% (SPECT), 79% (PET), and 71% (MRI). CONCLUSION: In this prospective head-to-head comparative study, SPECT, PET, and MRI did not show a significantly different accuracy for diagnosing FFR defined significant CAD in patients with prior PCI and/or MI. Overall diagnostic performances, however, were discouraging and the additive value of non-invasive imaging in this high-risk population is questionable.

EANM procedure guidelines for brain PET imaging using [18F]FDG, version 3.

The present procedural guidelines summarize the current views of the EANM Neuro-Imaging Committee (NIC). The purpose of these guidelines is to assist nuclear medicine practitioners in making recommendations, performing, interpreting, and reporting results of [18F]FDG-PET imaging of the brain. The aim is to help achieve a high-quality standard of [18F]FDG brain imaging and to further increase the diagnostic impact of this technique in neurological, neurosurgical, and psychiatric practice. The present document replaces a former version of the guidelines that have been published in 2009. These new guidelines include an update in the light of advances in PET technology such as the introduction of digital PET and hybrid PET/MR systems, advances in individual PET semiquantitative analysis, and current broadening clinical indications (e.g., for encephalitis and brain lymphoma). Further insight has also become available about hyperglycemia effects in patients who undergo brain [18F]FDG-PET. Accordingly, the patient preparation procedure has been updated. Finally, most typical brain patterns of metabolic changes are summarized for neurodegenerative diseases. The present guidelines are specifically intended to present information related to the European practice. The information provided should be taken in the context of local conditions and regulations.

Differential associations between neocortical tau pathology and blood flow with cognitive deficits in early-onset vs late-onset Alzheimer's disease.

PURPOSE: Early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) differ in neuropathological burden and type of cognitive deficits. Assessing tau pathology and relative cerebral blood flow (rCBF) measured with [18F]flortaucipir PET in relation to cognition may help explain these differences between EOAD and LOAD. METHODS: Seventy-nine amyloid-positive individuals with a clinical diagnosis of AD (EOAD: n = 35, age-at-PET = 59 ± 5, MMSE = 23 ± 4; LOAD: n = 44, age-at-PET = 71 ± 5, MMSE = 23 ± 4) underwent a 130-min dynamic [18F]flortaucipir PET scan and extensive neuropsychological assessment. We extracted binding potentials (BPND) and R1 (proxy of rCBF) from parametric images using receptor parametric mapping, in medial and lateral temporal, parietal, occipital, and frontal regions-of-interest and used nine neuropsychological tests covering memory, attention, language, and executive functioning. We first examined differences between EOAD and LOAD in BPND or R1 using ANOVA (region-of-interest analysis) and voxel-wise contrasts. Next, we performed linear regression models to test for potential interaction effects between age-at-onset and BPND/R1 on cognition. RESULTS: Both region-of-interest and voxel-wise contrasts showed higher [18F]flortaucipir BPND values across all neocortical regions in EOAD. By contrast, LOAD patients had lower R1 values (indicative of more reduced rCBF) in medial temporal regions. For both tau and flow in lateral temporal, and occipitoparietal regions, associations with cognitive impairment were stronger in EOAD than in LOAD (EOAD BPND - 0.76 ≤ stß ≤ - 0.48 vs LOAD - 0.18 ≤ stß ≤ - 0.02; EOAD R1 0.37 ≤ stß ≤ 0.84 vs LOAD - 0.25 ≤ stß ≤ 0.16). CONCLUSIONS: Compared to LOAD, the degree of lateral temporal and occipitoparietal tau pathology and relative cerebral blood-flow is more strongly associated with cognition in EOAD.

Comparing lesion and feature selections to predict progression in newly diagnosed DLBCL patients with FDG PET/CT radiomics features.

PURPOSE: Biomarkers that can accurately predict outcome in DLBCL patients are urgently needed. Radiomics features extracted from baseline [18F]-FDG PET/CT scans have shown promising results. This study aims to investigate which lesion- and feature-selection approaches/methods resulted in the best prediction of progression after 2 years. METHODS: A total of 296 patients were included. 485 radiomics features (n = 5 conventional PET, n = 22 morphology, n = 50 intensity, n = 408 texture) were extracted for all individual lesions and at patient level, where all lesions were aggregated into one VOI. 18 features quantifying dissemination were extracted at patient level. Several lesion selection approaches were tested (largest or hottest lesion, patient level [all with/without dissemination], maximum or median of all lesions) and compared to the predictive value of our previously published model. Several data reduction methods were applied (principal component analysis, recursive feature elimination (RFE), factor analysis, and univariate selection). The predictive value of all models was tested using a fivefold cross-validation approach with 50 repeats with and without oversampling, yielding the mean cross-validated AUC (CV-AUC). Additionally, the relative importance of individual radiomics features was determined. RESULTS: Models with conventional PET and dissemination features showed the highest predictive value (CV-AUC: 0.72-0.75). Dissemination features had the highest relative importance in these models. No lesion selection approach showed significantly higher predictive value compared to our previous model. Oversampling combined with RFE resulted in highest CV-AUCs. CONCLUSION: Regardless of the applied lesion selection or feature selection approach and feature reduction methods, patient level conventional PET features and dissemination features have the highest predictive value. Trial registration number and date: EudraCT: 2006-005174-42, 01-08-2008.

EARL compliance and imaging optimisation on the Biograph Vision Quadra PET/CT using phantom and clinical data.

PURPOSE: Current European Association of Nuclear Medicine (EANM) Research Ltd. (EARL) guidelines for the standardisation of PET imaging developed for conventional systems have not yet been adjusted for long axial field-of-view (LAFOV) systems. In order to use the LAFOV Siemens Biograph Vision Quadra PET/CT (Siemens Healthineers, Knoxville, TN, USA) in multicentre research and harmonised clinical use, compliance to EARL specifications for 18F-FDG tumour imaging was explored in the current study. Additional tests at various locations throughout the LAFOV and the use of shorter scan durations were included. Furthermore, clinical data were collected to further explore and validate the effects of reducing scan duration on semi-quantitative PET image biomarker accuracy and precision when using EARL-compliant reconstruction settings. METHODS: EARL compliance phantom measurements were performed using the NEMA image quality phantom both in the centre and at various locations throughout the LAFOV. PET data (maximum ring difference (MRD) = 85) were reconstructed using various reconstruction parameters and reprocessed to obtain images at shorter scan durations. Maximum, mean and peak activity concentration recovery coefficients (RC) were obtained for each sphere and compared to EARL standards specifications. Additionally, PET data (MRD = 85) of 10 oncological patients were acquired and reconstructed using various reconstruction settings and reprocessed from 10 min listmode acquisition into shorter scan durations. Per dataset, SUVs were derived from tumour lesions and healthy tissues. ANOVA repeated measures were performed to explore differences in lesion SUVmax and SUVpeak. Wilcoxon signed-rank tests were performed to evaluate differences in background SUVpeak and SUVmean between scan durations. The coefficient of variation (COV) was calculated to characterise noise. RESULTS: Phantom measurements showed EARL compliance for all positions throughout the LAFOV for all scan durations. Regarding patient data, EARL-compliant images showed no clinically meaningful significant differences in lesion SUVmax and SUVpeak or background SUVmean and SUVpeak between scan durations. Here, COV only varied slightly. CONCLUSION: Images obtained using the Vision Quadra PET/CT comply with EARL specifications. Scan duration and/or activity administration can be reduced up to a factor tenfold without the interference of increased noise.

18F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma.

PURPOSE: Accurate prognostic markers are urgently needed to identify diffuse large B-Cell lymphoma (DLBCL) patients at high risk of progression or relapse. Our purpose was to investigate the potential added value of baseline radiomics features to the international prognostic index (IPI) in predicting outcome after first-line treatment. METHODS: Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value ≥ 4.0), and 490 radiomics features were extracted. We used logistic regression with backward feature selection to predict 2-year time to progression (TTP). The area under the curve (AUC) of the receiver operator characteristic curve was calculated to assess model performance. High-risk groups were defined based on prevalence of events; diagnostic performance was assessed using positive and negative predictive values. RESULTS: The IPI model yielded an AUC of 0.68. The optimal radiomics model comprised the natural logarithms of metabolic tumor volume (MTV) and of SUVpeak and the maximal distance between the largest lesion and any other lesion (Dmaxbulk, AUC 0.76). Combining radiomics and clinical features showed that a combination of tumor- (MTV, SUVpeak and Dmaxbulk) and patient-related parameters (WHO performance status and age > 60 years) performed best (AUC 0.79). Adding radiomics features to clinical predictors increased PPV with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP, 44% vs 28%, respectively). CONCLUSION: Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance. TRIAL REGISTRATION NUMBER AND DATE: EudraCT: 2006-005,174-42, 01-08-2008.