FAPi PET/CT for assessment and visualisation of active myositis-related interstitial lung disease: a prospective observational pilot study.

Background: Interstitial lung disease (ILD) is a common manifestation of idiopathic inflammatory myopathies (IIM) and a substantial contributor to hospitalisation, increased morbidity, and mortality. In-vivo evidence of ongoing tissue remodelling in IIM-ILD is scarce. We aimed to evaluate fibroblast activation in lungs of IIM-patients and control individuals using 68Ga-labelled inhibitor of Fibroblast-Activation-Protein (FAPi) based positronic emission tomography and computed tomography imaging (PET/CT). Methods: In this prospective observational pilot study, consecutive patients with IIM and participants without rheumatic conditions or ILD serving as a control group were recruited at the Medical University of Vienna, Austria, and underwent FAPi PET/CT imaging. Standard-of-care procedures including clinical examination, assessment of severity of dyspnoea, high-resolution computed tomography (HR-CT), and pulmonary function testing (PFT) were performed on all patients with IIM at baseline and for patients with IIM-ILD at follow-up of 12 months. Baseline pulmonary FAPi-uptake was assessed by the maximum (SUVmax) and mean (SUVmean) standardized uptake values (SUV) over the whole lung (wl). SUV was corrected for blood pool background activity and target-to-background ratios (TBR) were calculated. We compared pulmonary FAPi-uptake between patients with IIM-ILD and those without ILD, as well as controls, and correlated baseline FAP-uptake with standard diagnostic tools such as HR-CT and PFT. For predictive implications, we investigated whether patients with IIM and progressive ILD exhibited higher baseline FAPi-uptake compared to those with stable ILD. Metrics are reported as mean with standard deviation (±SD). Findings: Between November 16, 2021 and October 10, 2022, a total of 32 patients were enrolled in the study. Three participants from the control group were excluded due to cardiopulmonary disease. In individuals with IIM-ILD (n = 14), wlTBRmax and wlTBRmean were significantly increased as compared with both non-ILD-IIM patients (n = 5) and the control group (n = 16): wlTBRmax: 2.06 ± 1.04 vs. 1.04 ± 0.22 (p = 0.019) and 1.08 ± 0.19 (p = 0.0012) and wlTBRmean: 0.45 ± 0.19 vs. 0.26 ± 0.06 (p = 0.025) and 0.27 ± 0.07 (p = 0.0024). Similar values were observed in wlTBRmax or wlTBRmean between non-ILD IIM patients and the control group. Patients with progressive ILD displayed significantly enhanced wlTBRmax and wlTBRmean values at baseline compared to patients with stable ILD: wlTBRmax: 1.30 ± 0.31 vs. 2.63 ± 1.04 (p = 0.0084) and wlTBRmean: 0.32 ± 0.08 vs. 0.55 ± 0.19 (p = 0.021). Strong correlations were found between FAPi-uptake and disease extent on HR-CT (wlTBRmax: R = 0.42, p = 0.07; wlTBRmean: R = 0.56, p = 0.013) and severity of respiratory symptoms determined by the New York Heart Association (NYHA) classification tool (wlTBRmax: R = 0.52, p = 0.022; wlTBRmean: R = 0.59, p = 0.0073). Further, pulmonary FAPi-uptake showed inverse correlation with forced vital capacity (FVC) (wlTBRmax: R = -0.56, p = 0.012; wlTBRmean: R = -0.64, p = 0.0033) and diffusing capacity of the lungs for carbon monoxide (DLCO) (wlTBRmax: R = -0.52, p = 0.028; wlTBRmean: R = -0.68, p = 0.0017). Interpretation: Our study demonstrates higher fibroblast activation in patients with IIM-ILD compared to non-ILD patients and controls. Intensity of pulmonary FAPi accumulation was associated with progression of ILD. Considering that this study was carried out on a small population, FAPi PET/CT may serve as a useful non-invasive tool for risk stratification of lung disease in IIM. Funding: The Austrian Research Fund.

Diagnosis and prognosis of abnormal cardiac scintigraphy uptake suggestive of cardiac amyloidosis using artificial intelligence: a retrospective, international, multicentre, cross-tracer development and validation study.

BACKGROUND: The diagnosis of cardiac amyloidosis can be established non-invasively by scintigraphy using bone-avid tracers, but visual assessment is subjective and can lead to misdiagnosis. We aimed to develop and validate an artificial intelligence (AI) system for standardised and reliable screening of cardiac amyloidosis-suggestive uptake and assess its prognostic value, using a multinational database of 99mTc-scintigraphy data across multiple tracers and scanners. METHODS: In this retrospective, international, multicentre, cross-tracer development and validation study, 16 241 patients with 19 401 scans were included from nine centres: one hospital in Austria (consecutive recruitment Jan 4, 2010, to Aug 19, 2020), five hospital sites in London, UK (consecutive recruitment Oct 1, 2014, to Sept 29, 2022), two centres in China (selected scans from Jan 1, 2021, to Oct 31, 2022), and one centre in Italy (selected scans from Jan 1, 2011, to May 23, 2023). The dataset included all patients referred to whole-body 99mTc-scintigraphy with an anterior view and all 99mTc-labelled tracers currently used to identify cardiac amyloidosis-suggestive uptake. Exclusion criteria were image acquisition at less than 2 h (99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid, 99mTc-hydroxymethylene diphosphonate, and 99mTc-methylene diphosphonate) or less than 1 h (99mTc-pyrophosphate) after tracer injection and if patients' imaging and clinical data could not be linked. Ground truth annotation was derived from centralised core-lab consensus reading of at least three independent experts (CN, TT-W, and JN). An AI system for detection of cardiac amyloidosis-associated high-grade cardiac tracer uptake was developed using data from one centre (Austria) and independently validated in the remaining centres. A multicase, multireader study and a medical algorithmic audit were conducted to assess clinician performance compared with AI and to evaluate and correct failure modes. The system's prognostic value in predicting mortality was tested in the consecutively recruited cohorts using cox proportional hazards models for each cohort individually and for the combined cohorts. FINDINGS: The prevalence of cases positive for cardiac amyloidosis-suggestive uptake was 142 (2%) of 9176 patients in the Austrian, 125 (2%) of 6763 patients in the UK, 63 (62%) of 102 patients in the Chinese, and 103 (52%) of 200 patients in the Italian cohorts. In the Austrian cohort, cross-validation performance showed an area under the curve (AUC) of 1·000 (95% CI 1·000-1·000). Independent validation yielded AUCs of 0·997 (0·993-0·999) for the UK, 0·925 (0·871-0·971) for the Chinese, and 1·000 (0·999-1·000) for the Italian cohorts. In the multicase multireader study, five physicians disagreed in 22 (11%) of 200 cases (Fleiss' kappa 0·89), with a mean AUC of 0·946 (95% CI 0·924-0·967), which was inferior to AI (AUC 0·997 [0·991-1·000], p=0·0040). The medical algorithmic audit demonstrated the system's robustness across demographic factors, tracers, scanners, and centres. The AI's predictions were independently prognostic for overall mortality (adjusted hazard ratio 1·44 [95% CI 1·19-1·74], p<0·0001). INTERPRETATION: AI-based screening of cardiac amyloidosis-suggestive uptake in patients undergoing scintigraphy was reliable, eliminated inter-rater variability, and portended prognostic value, with potential implications for identification, referral, and management pathways. FUNDING: Pfizer.

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.

PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group.

Response Assessment in Neuro-Oncology (RANO) response criteria have been established and were updated in 2023 for MRI-based response evaluation of diffuse gliomas in clinical trials. In addition, PET-based imaging with amino acid tracers is increasingly considered for disease monitoring in both clinical practice and clinical trials. So far, a standardised framework defining timepoints for baseline and follow-up investigations and response evaluation criteria for PET imaging of diffuse gliomas has not been established. Therefore, in this Policy Review, we propose a set of criteria for response assessment based on amino acid PET imaging in clinical trials enrolling participants with diffuse gliomas as defined in the 2021 WHO classification of tumours of the central nervous system. These proposed PET RANO criteria provide a conceptual framework that facilitates the structured implementation of PET imaging into clinical research and, ultimately, clinical routine. To this end, the PET RANO 1.0 criteria are intended to encourage specific investigations of amino acid PET imaging of gliomas.

Implementation of a 7T Epilepsy Task Force consensus imaging protocol for routine presurgical epilepsy work-up: effect on diagnostic yield and lesion delineation.

OBJECTIVE: Recently, the 7 Tesla (7 T) Epilepsy Task Force published recommendations for 7 T magnetic resonance imaging (MRI) in patients with pharmaco-resistant focal epilepsy in pre-surgical evaluation. The objective of this study was to implement and evaluate this consensus protocol with respect to both its practicability and its diagnostic value/potential lesion delineation surplus effect over 3 T MRI in the pre-surgical work-up of patients with pharmaco-resistant focal onset epilepsy. METHODS: The 7 T MRI protocol consisted of T1-weighted, T2-weighted, high-resolution-coronal T2-weighted, fluid-suppressed, fluid-and-white-matter-suppressed, and susceptibility-weighted imaging, with an overall duration of 50 min. Two neuroradiologists independently evaluated the ability of lesion identification, the detection confidence for these identified lesions, and the lesion border delineation at 7 T compared to 3 T MRI. RESULTS: Of 41 recruited patients > 12 years of age, 38 were successfully measured and analyzed. Mean detection confidence scores were non-significantly higher at 7 T (1.95 ± 0.84 out of 3 versus 1.64 ± 1.19 out of 3 at 3 T, p = 0.050). In 50% of epilepsy patients measured at 7 T, additional findings compared to 3 T MRI were observed. Furthermore, we found improved border delineation at 7 T in 88% of patients with 3 T-visible lesions. In 19% of 3 T MR-negative cases a new potential epileptogenic lesion was detected at 7 T. CONCLUSIONS: The diagnostic yield was beneficial, but with 19% new 7 T over 3 T findings, not major. Our evaluation revealed epilepsy outcomes worse than ILAE Class 1 in two out of the four operated cases with new 7 T findings.

Theranostics in Neurooncology: Heading Toward New Horizons.

Therapeutic approaches to brain tumors remain a challenge, with considerable limitations regarding delivery of drugs. There has been renewed and increasing interest in translating the popular theranostic approach well known from prostate and neuroendocrine cancer to neurooncology. Although far from perfect, some of these approaches show encouraging preliminary results, such as for meningioma and leptomeningeal spread of certain pediatric brain tumors. In brain metastases and gliomas, clinical results have failed to impress. Perspectives on these theranostic approaches regarding meningiomas, brain metastases, gliomas, and common pediatric brain tumors will be discussed. For each tumor entity, the general context, an overview of the literature, and future perspectives will be provided. Ongoing studies will be discussed in the supplemental materials. As most theranostic agents are unlikely to cross the blood-brain barrier, the delivery of these agents will be dependent on the successful development and clinical implementation of techniques enhancing permeability and retention. Moreover, the international community should strive toward sufficiently large and randomized studies to generate high-level evidence on theranostic approaches with radioligand therapies for central nervous system tumors.

High-temporal resolution functional PET/MRI reveals coupling between human metabolic and hemodynamic brain response.

PURPOSE: Positron emission tomography (PET) provides precise molecular information on physiological processes, but its low temporal resolution is a major obstacle. Consequently, we characterized the metabolic response of the human brain to working memory performance using an optimized functional PET (fPET) framework at a temporal resolution of 3 s. METHODS: Thirty-five healthy volunteers underwent fPET with [18F]FDG bolus plus constant infusion, 19 of those at a hybrid PET/MRI scanner. During the scan, an n-back working memory paradigm was completed. fPET data were reconstructed to 3 s temporal resolution and processed with a novel sliding window filter to increase signal to noise ratio. BOLD fMRI signals were acquired at 2 s. RESULTS: Consistent with simulated kinetic modeling, we observed a constant increase in the [18F]FDG signal during task execution, followed by a rapid return to baseline after stimulation ceased. These task-specific changes were robustly observed in brain regions involved in working memory processing. The simultaneous acquisition of BOLD fMRI revealed that the temporal coupling between hemodynamic and metabolic signals in the primary motor cortex was related to individual behavioral performance during working memory. Furthermore, task-induced BOLD deactivations in the posteromedial default mode network were accompanied by distinct temporal patterns in glucose metabolism, which were dependent on the metabolic demands of the corresponding task-positive networks. CONCLUSIONS: In sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing. This allows to capture unique information in the temporal domain, which is not accessible to conventional PET imaging.

Evaluation of Gliomas with Magnetic Resonance Fingerprinting with PET Correlation-A Comparative Study.

OBJECTIVES: Advanced MR imaging of brain tumors is still mainly based on qualitative imaging. PET imaging offers additive metabolic information, and MR fingerprinting (MRF) offers a novel approach to quantitative data acquisition. The purpose of this study was to evaluate the ability of MRF to predict tumor regions and grading in combination with PET. METHODS: Seventeen patients with histologically verified infiltrating gliomas and available amino-acid PET data were enrolled. ROIs for solid tumor parts (SPo), perifocal edema (ED1), and normal-appearing white matter (NAWM) were selected on conventional MRI sequences and aligned to the MRF and PET images. The predictability of gliomas by region and grading as well as intermodal correlations were assessed. RESULTS: For MRF, we calculated an overall predictability by region (SPo, ED1, and NAWM) for all of the MRF parameters of 76.5%, 47.1%, and 94.1%, respectively. The overall ability to distinguish low- from high-grade gliomas using MRF was 88.9% for LGG and 75% for HGG, with an accuracy of 82.4%, a ppV of 85.71%, and an npV of 80%. PET positivity was found in 13/17 patients for solid tumor parts, and in 3/17 patients for the edema region. However, there was no significant difference in region-specific MRF values between PET positive and PET negative patients. CONCLUSIONS: MRF and PET provide quantitative measurements of the tumor tissue characteristics of gliomas, with good predictability. Nonetheless, the results are dissimilar, reflecting the different underlying mechanisms of each method.

Comparison of cardiac image-derived input functions for quantitative whole body [18F]FDG imaging with arterial blood sampling.

Introduction: Dynamic positron emission tomography (PET) and the application of kinetic models can provide important quantitative information based on its temporal information. This however requires arterial blood sampling, which can be challenging to acquire. Nowadays, state-of-the-art PET/CT systems offer fully automated, whole-body (WB) kinetic modelling protocols using image-derived input functions (IDIF) to replace arterial blood sampling. Here, we compared the validity of an automatic WB kinetic model protocol to the reference standard arterial input function (AIF) for both clinical and research settings. Methods: Sixteen healthy participants underwent dynamic WB [18F]FDG scans using a continuous bed motion PET/CT system with simultaneous arterial blood sampling. Multiple processing pipelines that included automatic and manually generated IDIFs derived from the aorta and left ventricle, with and without motion correction were compared to the AIF. Subsequently generated quantitative images of glucose metabolism were compared to evaluate performance of the different input functions. Results: We observed moderate to high correlations between IDIFs and the AIF regarding area under the curve (r = 0.49-0.89) as well as for the cerebral metabolic rate of glucose (CMRGlu) (r = 0.68-0.95). Manual placing of IDIFs and motion correction further improved their similarity to the AIF. Discussion: In general, the automatic vendor protocol is a feasible approach for the quantification of CMRGlu for both, clinical and research settings where expertise or time is not available. However, we advise on a rigorous inspection of the placement of the volume of interest, the resulting IDIF, and the quantitative values to ensure valid interpretations. In protocols requiring longer scan times or where cohorts are prone to involuntary movement, manual IDIF definition with additional motion correction is recommended, as this has greater accuracy and reliability.

Whole-body metabolic connectivity framework with functional PET.

The nervous and circulatory system interconnects the various organs of the human body, building hierarchically organized subsystems, enabling fine-tuned, metabolically expensive brain-body and inter-organ crosstalk to appropriately adapt to internal and external demands. A deviation or failure in the function of a single organ or subsystem could trigger unforeseen biases or dysfunctions of the entire network, leading to maladaptive physiological or psychological responses. Therefore, quantifying these networks in healthy individuals and patients may help further our understanding of complex disorders involving body-brain crosstalk. Here we present a generalized framework to automatically estimate metabolic inter-organ connectivity utilizing whole-body functional positron emission tomography (fPET). The developed framework was applied to 16 healthy subjects (mean age ± SD, 25 ± 6 years; 13 female) that underwent one dynamic 18F-FDG PET/CT scan. Multiple procedures of organ segmentation (manual, automatic, circular volumes) and connectivity estimation (polynomial fitting, spatiotemporal filtering, covariance matrices) were compared to provide an optimized thorough overview of the workflow. The proposed approach was able to estimate the metabolic connectivity patterns within brain regions and organs as well as their interactions. Automated organ delineation, but not simplified circular volumes, showed high agreement with manual delineation. Polynomial fitting yielded similar connectivity as spatiotemporal filtering at the individual subject level. Furthermore, connectivity measures and group-level covariance matrices did not match. The strongest brain-body connectivity was observed for the liver and kidneys. The proposed framework offers novel opportunities towards analyzing metabolic function from a systemic, hierarchical perspective in a multitude of physiological pathological states.

Feasibility of dose reduction for [18F]FDG-PET/MR imaging of patients with non-lesional epilepsy.

The aim of the study was to evaluate the effect of reduced injected [18F]FDG activity levels on the quantitative and diagnostic accuracy of PET images of patients with non-lesional epilepsy (NLE).Nine healthy volunteers and nine patients with NLE underwent 60-min dynamic list-mode (LM) scans on a fully-integrated PET/MRI system. Injected FDG activity levels were reduced virtually by randomly removing counts from the last 10-min of the LM data, so as to simulate the following activity levels: 50 %, 35 %, 20 %, and 10 % of the original activity. Four image reconstructions were evaluated: standard OSEM, OSEM with resolution recovery (PSF), the A-MAP, and the Asymmetrical Bowsher (AsymBowsher) algorithms. For the A-MAP algorithms, two weights were selected (low and high). Image contrast and noise levels were evaluated for all subjects while the lesion-to-background ratio (L/B) was only evaluated for patients. Patient images were scored by a Nuclear Medicine physician on a 5-point scale to assess clinical impression associated with the various reconstruction algorithms.The image contrast and L/B ratio characterizing all four reconstruction algorithms were similar, except for reconstructions based on only 10 % of total counts. Based on clinical impression, images with diagnostic quality can be achieved with as low as 35 % of the standard injected activity. The selection of algorithms utilizing an anatomical prior did not provide a significant advantage for clinical readings, despite a small improvement in L/B (< 5 %) using the A-MAP and AsymBowsher reconstruction algorithms.In patients with NLE who are undergoing [18F]FDG-PET/MR imaging, the injected [18F]FDG activity can be reduced to 35 % of the original dose levels without compromising.

Sex-specific radiomic features of L-[S-methyl-11C] methionine PET in patients with newly-diagnosed gliomas in relation to IDH1 predictability.

Introduction: Amino-acid positron emission tomography (PET) is a validated metabolic imaging approach for the diagnostic work-up of gliomas. This study aimed to evaluate sex-specific radiomic characteristics of L-[S-methyl-11Cmethionine (MET)-PET images of glioma patients in consideration of the prognostically relevant biomarker isocitrate dehydrogenase (IDH) mutation status. Methods: MET-PET of 35 astrocytic gliomas (13 females, mean age 41 ± 13 yrs. and 22 males, mean age 46 ± 17 yrs.) and known IDH mutation status were included. All patients underwent radiomic analysis following imaging biomarker standardization initiative (IBSI)-conform guidelines both from standardized uptake value (SUV) and tumor-to-background ratio (TBR) PET values. Aligned Monte Carlo (MC) 100-fold split was utilized for SUV and TBR dataset pairs for both sex and IDH-specific analysis. Borderline and outlier scores were calculated for both sex and IDH-specific MC folds. Feature ranking was performed by R-squared ranking and Mann-Whitney U-test together with Bonferroni correction. Correlation of SUV and TBR radiomics in relation to IDH mutational status in male and female patients were also investigated. Results: There were no significant features in either SUV or TBR radiomics to distinguish female and male patients. In contrast, intensity histogram coefficient of variation (ih.cov) and intensity skewness (stat.skew) were identified as significant to predict IDH +/-. In addition, IDH+ females had significant ih.cov deviation (0.031) and mean stat.skew (-0.327) differences compared to IDH+ male patients (0.068 and -0.123, respectively) with two-times higher standard deviations of the normal brain background MET uptake as well. Discussion: We demonstrated that female and male glioma patients have significantly different radiomic profiles in MET PET imaging data. Future IDH prediction models shall not be built on mixed female-male cohorts, but shall rely on sex-specific cohorts and radiomic imaging biomarkers.

Does [99mTc]-3,3-diphosphono-1,2-propanodicarboxylic acid (DPD) soft tissue uptake allow the identification of patients with the diagnosis of cardiac transthyretin-related (ATTR) amyloidosis with higher risk for polyneuropathy?

BACKGROUND: With the introduction of several drugs for the therapy of transthyretin-related amyloidosis (ATTR) which slow down the disease, early detection of polyneuropathy (PNP) is becoming increasingly of interest. [99mTc]-3,3-Diphosphono-1,2-Propanodicarboxylic Acid (DPD) bone scintigraphy, which is used for the diagnosis of cardiac (c)ATTR, can possibly make an important contribution in the identification of patients at risk for PNP. METHODS: Fifty patients with cATTR, who underwent both planar whole-body DPD scintigraphy and nerve conduction studies (NCS) were retrospectively evaluated. A subgroup of 22 patients also underwent quantitative SPECT/CT of the thorax from which Standardized Uptake Values (SUVpeak) in the subcutaneous fat tissue of the left axillar region were evaluated. RESULTS: The Perugini score was significantly increased in patients with cATTR and additional diagnosis of PNP compared to patients without (2.51 ± 0.51 vs 2.13 ± 0.52; P = 0.03). Quantitative SPECT/CT revealed that DPD uptake in the subcutaneous fat of the left axillar region was significantly increased in cATTR patients with compared to patients without (1.36 ± 0.60 vs 0.74 ± 0.52; P = 0.04). CONCLUSION: This study suggests that DPD bone scintigraphy is a useful tool for identification of patients with cATTR and a risk for PNP due to increased DPD soft tissue uptake.

Cardiac DPD-uptake time dependency in ATTR patients verified by quantitative SPECT/CT and semiquantitative planar parameters.

BACKGROUND: Bone scintigraphy plays an important role in the diagnosis of cardiac Transthyretin-Related Amyloidosis (ATTR). The mechanism of myocardial tracer accumulation and its dependence over time are not fully understood. Recently, a scintigraphic quantification of the cardiac amyloid deposition has been discussed. Nevertheless, little is known regarding the right time of quantitative imaging. METHODS: The geometrical mean of decay corrected total counts over the heart and the heart/whole-body ratio (H/WB) were evaluated in 23 patients undergoing DPD-bone scan with planar whole-body images 1 and 3 hours post injection (p.i.). Myocardial standard uptake values (SUV)peak were assessed in another 15 patients with quantitative SPECT/CT imaging 1 hours and 3 hours p.i.. RESULTS: Total counts over the heart (1 hours p.i.: 81,676 cts, range 69,887 to 93,091 cts and 3 hours p.i.: 64,819 cts, range 52,048 to 86,123 cts, P = .0005) and H/WB ratio (1 hours p.i.:0.076 ± 0.020 and 3 hours p.i. 0.070 ± 0.022; P = .0003) were significantly increased 1 hours p.i.. Furthermore median myocardial SUVpeak (1 hours p.i.:12.2, range 9.6 to 18.9 and 3 hours p.i.: 9.6, range 8.2 to 15.0, P = 0.0012) was also significantly higher after 1 hours p.i. compared to 3 hours p.i.. CONCLUSION: Cardiac DPD activity and myocardial SUVpeak are time-dependent, which should be considered when using quantitative bone scintigraphy in ATTR patients.

The trends and significance of SSTR PET/CT added to MRI in follow-up imaging of low-grade meningioma treated with fractionated proton therapy.

PURPOSE: Overexpression of the somatostatin receptor (SSTR) has led to adoption of SSTR PET/CT for diagnosis and radiotherapy planning in meningioma, but data on SSTR expression during follow-up remain scarce. We investigated PET/CT quantifiers of SSTR tracers in WHO grade I meningioma following fractionated proton beam therapy (PBT) compared to standard response assessment with MRI. METHODS: Twenty-two patients diagnosed with low-grade meningioma treated by PBT were included. Follow-up included clinical visits, MRI, and [68Ga]Ga-DOTATOC PET/CT scans. Radiologic tumor response, MRI and PET volume (VMRI and VPET), maximum and mean standardied uptake value (SUVmax/SUVmean), total lesion activity (TLA), and heterogeneity index (HI) were evaluated. RESULTS: Median follow-up was 35.3 months (range: 6.4-47.9). Nineteen patients (86.4%, p = 0.0009) showed a decrease of SUVmax between baseline and first follow-up PET/CT (median: -24%, range: -53% to +89%) and in 81.8% of all cases, the SUVmax, SUVmean, and TLA at last follow-up were eventually lower than at baseline (p = 0.0043). Ambiguous trends without significance between the timepoints analyzed were observed for VPET. HI increased between baseline and last follow-up in 75% of cases (p = 0.024). All patients remained radiologically and clinically stable. Median VMRI decreased by -9.3% (range 0-32.5%, p < 0.0001) between baseline and last follow-up. CONCLUSION: PET/CT in follow-up of irradiated meningioma showed an early trend towards decreased binding of SSTR-specific tracers following radiation and MRI demonstrated consistently stable or decreasing tumor volume. Translational research is needed to clarify the underlying biology of the subsequent increase in SSTR PET quantifiers.

Automated data preparation for in vivo tumor characterization with machine learning.

Background: This study proposes machine learning-driven data preparation (MLDP) for optimal data preparation (DP) prior to building prediction models for cancer cohorts. Methods: A collection of well-established DP methods were incorporated for building the DP pipelines for various clinical cohorts prior to machine learning. Evolutionary algorithm principles combined with hyperparameter optimization were employed to iteratively select the best fitting subset of data preparation algorithms for the given dataset. The proposed method was validated for glioma and prostate single center cohorts by 100-fold Monte Carlo (MC) cross-validation scheme with 80-20% training-validation split ratio. In addition, a dual-center diffuse large B-cell lymphoma (DLBCL) cohort was utilized with Center 1 as training and Center 2 as independent validation datasets to predict cohort-specific clinical endpoints. Five machine learning (ML) classifiers were employed for building prediction models across all analyzed cohorts. Predictive performance was estimated by confusion matrix analytics over the validation sets of each cohort. The performance of each model with and without MLDP, as well as with manually-defined DP were compared in each of the four cohorts. Results: Sixteen of twenty established predictive models demonstrated area under the receiver operator characteristics curve (AUC) performance increase utilizing the MLDP. The MLDP resulted in the highest performance increase for random forest (RF) (+0.16 AUC) and support vector machine (SVM) (+0.13 AUC) model schemes for predicting 36-months survival in the glioma cohort. Single center cohorts resulted in complex (6-7 DP steps) DP pipelines, with a high occurrence of outlier detection, feature selection and synthetic majority oversampling technique (SMOTE). In contrast, the optimal DP pipeline for the dual-center DLBCL cohort only included outlier detection and SMOTE DP steps. Conclusions: This study demonstrates that data preparation prior to ML prediction model building in cancer cohorts shall be ML-driven itself, yielding optimal prediction models in both single and multi-centric settings.