Left ventricular shape index and eccentricity index with ECG-gated Nitrogen-13 ammonia PET/CT in patients with myocardial infarction, ischemia, and normal perfusion

BACKGROUND

LV geometry with shape index (SI) and eccentricity index (EI) measured by myocardial perfusion positron emission tomography/computed tomography (PET/CT) may allow the evaluation of left ventricular (LV) adverse remodeling. This first study aims to explore the relationship of SI and EI values acquired by Nitrogen-13 ammonia PET/CT in patients with normal perfusion, ischemia, and myocardial infarction. And evaluate the correlations between the variables of LV geometry, and with the variables of LV function.

METHODS AND RESULTS

One hundred and forty patients who underwent an electrocardiogram (ECG)-gated PET/CT were selected and classified into 4 groups according to ischemia or infarction burden (normal perfusion, mild ischemia, moderate-severe ischemia, and infarction). The variables were automatically retrieved using dedicated software (QPS/QGS; Cedars-Sinai, Los Angeles, CA, USA). On multicomparison analysis (one-way ANOVA and Dunnett's Test), subjects in the infarction group had significant higher values of SI end-diastolic rest (P < 0.001), and stress (P = 0.003), SI end-systolic rest (P = 0.002) and stress (P < 0.001) as well as statistically significant lower values of EI rest (P < 0.001) and stress (P < 0.001) when compared with all other groups. Regarding Pearson correlation, in the infarcted group all the variables of SI and EI were significantly correlated (P < 0.001) with strong correlation coefficients (>0.60). SI end-systolic correlated significantly with the variables of LV function independently of the group of patients (P < 0.05).

CONCLUSIONS

Shape and eccentricity indices differ in patients with myocardial infarction as compared to patients with ischemia or normal perfusion. This encourage further research in their potential for detecting LV adverse remodeling.

Can Internal Carotid Arteries Be Used for Noninvasive Quantification of Brain PET Studies?

Because of the limited axial field of view of conventional PET scanners, the internal carotid arteries are commonly used to obtain an image-derived input function (IDIF) in quantitative brain PET. However, time-activity curves extracted from the internal carotids are prone to partial-volume effects due to the limited PET resolution. This study aimed to assess the use of the internal carotids for quantifying brain glucose metabolism before and after partial-volume correction. Methods: Dynamic [18F]FDG images were acquired on a 106-cm-long PET scanner, and quantification was performed with a 2-tissue-compartment model and Patlak analysis using an IDIF extracted from the internal carotids. An IDIF extracted from the ascending aorta was used as ground truth. Results: The internal carotid IDIF underestimated the area under the curve by 37% compared with the ascending aorta IDIF, leading to Ki values approximately 17% higher. After partial-volume correction, the mean relative Ki differences calculated with the ascending aorta and internal carotid IDIFs dropped to 7.5% and 0.05%, when using a 2-tissue-compartment model and Patlak analysis, respectively. However, microparameters (K 1, k 2, k 3) derived from the corrected internal carotid curve differed significantly from those obtained using the ascending aorta. Conclusion: These results suggest that partial-volume-corrected internal carotids may be used to estimate Ki but not kinetic microparameters. Further validation in a larger patient cohort with more variable kinetics is needed for more definitive conclusions.

Does FDG-PET/CT for incidentally found pulmonary lesions lead to a cascade of more incidental findings?

OBJECTIVE

To determine the frequency, nature, and downstream healthcare costs of new incidental findings that are found on whole-body FDG-PET/CT in patients with a non-FDG-avid pulmonary lesion ≥10 mm that was incidentally found on previous imaging.

MATERIALS AND METHODS

This retrospective study included a consecutive series of patients who underwent whole-body FDG-PET/CT because of an incidentally found pulmonary lesion ≥10 mm.

RESULTS

Seventy patients were included, of whom 23 (32.9 %) had an incidentally found pulmonary lesion that proved to be non-FDG-avid. In 12 of these 23 cases (52.2 %) at least one new incidental finding was discovered on FDG-PET/CT. The total number of new incidental findings was 21, of which 7 turned out to be benign, 1 proved to be malignant (incurable metastasized cancer), and 13 whose nature remained unclear. One patient sustained permanent neurologic impairment of the left leg due to iatrogenic nerve damage during laparotomy for an incidental finding which turned out to be benign. The total costs of all additional investigations due to the detection of new incidental findings amounted to €9903.17, translating to an average of €141.47 per whole-body FDG-PET/CT scan performed for the evaluation of an incidentally found pulmonary lesion.

CONCLUSION

In many patients in whom whole-body FDG-PET/CT was performed to evaluate an incidentally found pulmonary lesion that turned out to be non-FDG-avid and therefore very likely benign, FDG-PET/CT detected new incidental findings in our preliminary study. Whether the detection of these new incidental findings is cost-effective or not, requires further research with larger sample sizes.

Automated multiclass segmentation, quantification, and visualization of the diseased aorta on hybrid PET/CT-SEQUOIA

BACKGROUND

Cardiovascular disease is the most common cause of death worldwide, including infection and inflammation related conditions. Multiple studies have demonstrated potential advantages of hybrid positron emission tomography combined with computed tomography (PET/CT) as an adjunct to current clinical inflammatory and infectious biochemical markers. To quantitatively analyze vascular diseases at PET/CT, robust segmentation of the aorta is necessary. However, manual segmentation is extremely time-consuming and labor-intensive.

PURPOSE

To investigate the feasibility and accuracy of an automated tool to segment and quantify multiple parts of the diseased aorta on unenhanced low-dose computed tomography (LDCT) as an anatomical reference for PET-assessed vascular disease.

METHODS

A software pipeline was developed including automated segmentation using a 3D U-Net, calcium scoring, PET uptake quantification, background measurement, radiomics feature extraction, and 2D surface visualization of vessel wall calcium and tracer uptake distribution. To train the 3D U-Net, 352 non-contrast LDCTs from (2-[18 F]FDG and Na[18 F]F) PET/CTs performed in patients with various vascular pathologies with manual segmentation of the ascending aorta, aortic arch, descending aorta, and abdominal aorta were used. The last 22 consecutive scans were used as a hold-out internal test set. The remaining dataset was randomly split into training (n = 264; 80%) and validation (n = 66; 20%) sets. Further evaluation was performed on an external test set of 49 PET/CTs. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to assess segmentation performance. Automatically obtained calcium scores and uptake values were compared with manual scoring obtained using clinical softwares (syngo.via and Affinity Viewer) in six patient images. intraclass correlation coefficients (ICC) were calculated to validate calcium and uptake values.

RESULTS

Fully automated segmentation of the aorta using a 3D U-Net was feasible in LDCT obtained from PET/CT scans. The external test set yielded a DSC of 0.867 ± 0.030 and HD of 1.0 [0.6-1.4] mm, similar to an open-source model with a DSC of 0.864 ± 0.023 and HD of 1.4 [1.0-1.8] mm. Quantification of calcium and uptake values were in excellent agreement with clinical software (ICC: 1.00 [1.00-1.00] and 0.99 [0.93-1.00] for calcium and uptake values, respectively).

CONCLUSIONS

We present an automated pipeline to segment the ascending aorta, aortic arch, descending aorta, and abdominal aorta on LDCT from PET/CT and to accurately provide uptake values, calcium scores, background measurement, radiomics features, and a 2D visualization. We call this algorithm SEQUOIA (SEgmentation, QUantification, and visualizatiOn of the dIseased Aorta) and is available at https://github.com/UMCG-CVI/SEQUOIA. This model could augment the utility of aortic evaluation at PET/CT studies tremendously, irrespective of the tracer, and potentially provide fast and reliable quantification of cardiovascular diseases in clinical practice, both for primary diagnosis and disease monitoring.

Ultra-low dose CT scanning for PET/CT

BACKGROUND

The use of computed tomography (CT) for attenuation correction (AC) in whole-body PET/CT can result in a significant contribution to radiation exposure. This can become a limiting factor for reducing considerably the overall radiation exposure of the patient when using the new long axial field of view (LAFOV) PET scanners. However, recent CT technology have introduced features such as the tin (Sn) filter, which can substantially reduce the CT radiation dose.

PURPOSE

The purpose of this study was to investigate the ultra-low dose CT for attenuation correction using the Sn filter together with other dose reduction options such as tube current (mAs) reduction. We explore the impact of dose reduction in the context of AC-CT and how it affects PET image quality.

METHODS

The study evaluated a range of ultra-low dose CT protocols using five physical phantoms that represented a broad collection of tissue electron densities. A long axial field of view (LAFOV) PET/CT scanner was used to scan all phantoms, applying various CT dose reduction parameters such as reducing tube current (mAs), increasing the pitch value, and applying the Sn filter. The effective dose resulting from the CT scans was determined using the CTDIVol reported by the scanner. Several voxel-based and volumes of interest (VOI)-based comparisons were performed to compare the ultra-low dose CT images, the generated attenuation maps, and corresponding PET images against those images acquired with the standard low dose CT protocol. Finally, two patient datasets were acquired using one of the suggested ultra-low dose CT settings.

RESULTS

By incorporating the Sn filter and adjusting mAs to the lowest available value, the radiation dose in CT images of PBU-60 phantom was significantly reduced; resulting in an effective dose of nearly 2% compared to the routine low dose CT protocols currently in clinical use. The assessment of PET images using VOI and voxel-based comparisons indicated relative differences (RD%) of under 6% for mean activity concentration (AC) in the torso phantom and patient dataset and under 8% for a source point in the CIRS phantom. The maximum RD% value of AC was 14% for the point source in the CIRS phantom. Increasing the tube current from 6 mAs to 30 mAs in patients with high BMI, or with arms down, can suppress the photon starvation artifact, whilst still preserving a dose reduction of 90%.

CONCLUSIONS

Introducing a Sn filter in CT imaging lowers radiation dose by more than 90%. This reduction has minimal effect on PET image quantification at least for patients without Body Mass Index (BMI) higher than 30. Notably, this study results need validation using a larger clinical PET/CT dataset in the future, including patients with higher BMI.

The clinical value of quantitative cardiovascular molecular imaging: a step towards precision medicine

Cardiovascular diseases (CVD) are the leading cause of death worldwide and have an increasing impact on society. Precision medicine, in which optimal care is identified for an individual or a group of individuals rather than for the average population, might provide significant health benefits for this patient group and decrease CVD morbidity and mortality. Molecular imaging provides the opportunity to assess biological processes in individuals in addition to anatomical context provided by other imaging modalities and could prove to be essential in the implementation of precision medicine in CVD. New developments in single-photon emission computed tomography (SPECT) and positron emission tomography (PET) systems, combined with rapid innovations in promising and specific radiopharmaceuticals, provide an impressive improvement of diagnostic accuracy and therapy evaluation. This may result in improved health outcomes in CVD patients, thereby reducing societal impact. Furthermore, recent technical advances have led to new possibilities for accurate image quantification, dynamic imaging, and quantification of radiotracer kinetics. This potentially allows for better evaluation of disease activity over time and treatment response monitoring. However, the clinical implementation of these new methods has been slow. This review describes the recent advances in molecular imaging and the clinical value of quantitative PET and SPECT in various fields in cardiovascular molecular imaging, such as atherosclerosis, myocardial perfusion and ischemia, infiltrative cardiomyopathies, systemic vascular diseases, and infectious cardiovascular diseases. Moreover, the challenges that need to be overcome to achieve clinical translation are addressed, and future directions are provided.

Long Versus Short Axial Field of View Immuno-PET/CT: Semiquantitative Evaluation for 89Zr-Trastuzumab

The purpose of this study was to quantify any differences between the SUVs of 89Zr immuno-PET scans obtained using a PET/CT system with a long axial field of view (LAFOV; Biograph Vision Quadra) compared to a PET/CT system with a short axial field of view (SAFOV; Biograph Vision) and to evaluate how LAFOV PET scan duration affects image noise and SUV metrics. Methods: Five metastatic breast cancer patients were scanned consecutively on SAFOV and LAFOV PET/CT scanners. Four additional patients were scanned using only LAFOV PET/CT. Scans on both systems lasted approximately 30 min and were acquired 4 d after injection of 37 MBq of 89Zr-trastuzumab. LAFOV list-mode data were reprocessed to obtain images acquired using shorter scan durations (15, 10, 7.5, 5, and 3 min). Volumes of interest were placed in healthy tissues, and tumors were segmented semiautomatically to compare coefficients of variation and to perform Bland-Altman analysis on SUV metrics (SUVmax, SUVpeak, and SUVmean). Results: Using 30-min images, 2 commonly used lesion SUV metrics were higher for SAFOV than for LAFOV PET (SUVmax, 16.2% ± 13.4%, and SUVpeak, 10.1% ± 7.2%), whereas the SUVmean of healthy tissues showed minimal differences (0.7% ± 5.8%). Coefficients of variation in the liver derived from 30-min SAFOV PET were between those of 3- and 5-min LAFOV PET. The smallest SUVmax and SUVpeak differences between SAFOV and LAFOV were found for 3-min LAFOV PET. Conclusion: LAFOV 89Zr immuno-PET showed a lower SUVmax and SUVpeak than SAFOV because of lower image noise. LAFOV PET scan duration may be reduced at the expense of increasing image noise and bias in SUV metrics. Nevertheless, SUVpeak showed only minimal bias when reducing scan duration from 30 to 10 min.

Current and Future Use of Long Axial Field-of-View Positron Emission Tomography/Computed Tomography Scanners in Clinical Oncology

The latest technical development in the field of positron emission tomography/computed tomography (PET/CT) imaging has been the extension of the PET axial field-of-view. As a result of the increased number of detectors, the long axial field-of-view (LAFOV) PET systems are not only characterized by a larger anatomical coverage but also by a substantially improved sensitivity, compared with conventional short axial field-of-view PET systems. In clinical practice, this innovation has led to the following optimization: (1) improved overall image quality, (2) decreased duration of PET examinations, (3) decreased amount of radioactivity administered to the patient, or (4) a combination of any of the above. In this review, novel applications of LAFOV PET in oncology are highlighted and future directions are discussed.

[15O]H2O PET: Potential or Essential for Molecular Imaging?

Imaging water pathways in the human body provides an excellent way of measuring accurately the blood flow directed to different organs. This makes it a powerful diagnostic tool for a wide range of diseases that are related to perfusion and oxygenation. Although water PET has a long history, its true potential has not made it into regular clinical practice. The article highlights the potential of water PET in molecular imaging and suggests its prospective role in becoming an essential tool for the 21st century precision medicine in different domains ranging from preclinical to clinical research and practice. The recent technical advances in high-sensitivity PET imaging can play a key accelerating role in empowering this technique, though there are still several challenges to overcome.

Exploring the Utility of Cardiovascular Magnetic Resonance Radiomic Feature Extraction for Evaluation of Cardiac Sarcoidosis

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 (CS_active) and inactive cardiac sarcoidosis (CS_inactive) based on PET-CMR imaging. CS_active was classified as featuring patchy [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) uptake on PET and presence of late gadolinium enhancement (LGE) on CMR, while CS_inactive was classified as featuring no [¹⁸F]FDG uptake in the presence of LGE on CMR. Among those screened, thirty CS_active and thirty-one CS_inactive patients met these criteria. A total of 94 radiomic features were subsequently extracted using PyRadiomics. The values of individual features were compared between CS_active and CS_inactive 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 CS_active and CS_inactive 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.

Oral administration of PET tracers: Current status

The oral route is the most widely used and preferable way of drug administration. Several pharmacokinetic processes play a role in the distribution of administered drugs. Therefore, accurate quantification of absorption, distribution, metabolism, excretion, and characterisation of drug kinetics after oral administration is extremely important for developing new human drugs. In vivo methods, such as gamma-scintigraphy, magnetic resonance imaging (MRI), and positron emission tomography (PET), have been used to analyse gastrointestinal tract (GIT) absorption behaviour. This scoping review provides an overview of PET studies that used oral tracer administration. A systematic literature search was performed using PubMed, EMBASE, Scopus, Science Direct, and Web of Science databases. Extensive variation between these studies was seen concerning acquisition protocols, quantification methods, and pharmacokinetic outcome parameters. Studies in humans indicate that it takes 10 to 30 min for the tracer to be in the intestine and about 100 min to reach its maximum concentration in the brain. In rodent studies, different pharmacokinetic parameters for the brain, blood, and GIT were estimated, showing the potential of PET to measure the absorption and distribution of drugs and pharmaceuticals non-invasively. Finally, regarding radiation protection, oral administration has a higher absorbed dose in GIT and, consequently, a higher effective dose. However, with the recent introduction of Long Axial Field of View (LAFOV) PET scanners, it is possible to reduce the administered dose, making oral administration feasible for routine clinical studies.

An Automated Method for Artifical Intelligence Assisted Diagnosis of Active Aortitis Using Radiomic Analysis of FDG PET-CT Images

The aim of this study was to develop and validate an automated pipeline that could assist the diagnosis of active aortitis using radiomic imaging biomarkers derived from [18F]-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography (FDG PET-CT) images. The aorta was automatically segmented by convolutional neural network (CNN) on FDG PET-CT of aortitis and control patients. The FDG PET-CT dataset was split into training (43 aortitis:21 control), test (12 aortitis:5 control) and validation (24 aortitis:14 control) cohorts. Radiomic features (RF), including SUV metrics, were extracted from the segmented data and harmonized. Three radiomic fingerprints were constructed: A-RFs with high diagnostic utility removing highly correlated RFs; B used principal component analysis (PCA); C-Random Forest intrinsic feature selection. The diagnostic utility was evaluated with accuracy and area under the receiver operating characteristic curve (AUC). Several RFs and Fingerprints had high AUC values (AUC > 0.8), confirmed by balanced accuracy, across training, test and external validation datasets. Good diagnostic performance achieved across several multi-centre datasets suggests that a radiomic pipeline can be generalizable. These findings could be used to build an automated clinical decision tool to facilitate objective and standardized assessment regardless of observer experience.

Image Reconstruction Analysis for Positron Emission Tomography With Heterostructured Scintillators

The concept of structure engineering has been proposed for exploring the next generation of radiation detectors with improved performance. A TOF-PET geometry with heterostructured scintillators with a pixel size of 3.0 × 3.1 × 15 mm3 was simulated using Monte Carlo. The heterostructures consisted of alternating layers of BGO as a dense material with high stopping power and plastic (EJ232) as a fast light emitter. The detector time resolution was calculated as a function of the deposited and shared energy in both materials on an event-by-event basis. While sensitivity was reduced to 32% for 100-μm thick plastic layers and 52% for 50 μm, the coincidence time resolution (CTR) distribution improved to 204 ± 49 and 220 ± 41 ps, respectively, compared to 276 ps that we considered for bulk BGO. The complex distribution of timing resolutions was accounted for in the reconstruction. We divided the events into three groups based on their CTR and modeled them with different Gaussian TOF kernels. On an NEMA IQ phantom, the heterostructures had better contrast recovery in early iterations. On the other hand, BGO achieved a better contrast-to-noise ratio (CNR) after the 15th iteration due to the higher sensitivity. The developed simulation and reconstruction methods constitute new tools for evaluating different detector designs with complex time responses.

Will extended field-of-view PET/CT depopulate the graveyard of failed PET radiopharmaceuticals?

With the rapid emergence of extended Field-of-View PET-cameras several new applications for radiopharmaceuticals become within reach. Main reason is the significant increase of the sensitivity of the PET-camera so that much less radioactivity can be administered. Issues that that hampered development or use of PET-radiopharmaceuticals become realistic again. Molar activity requirements can become less strict. New low-yielding radiochemistry methods may become applicable. Carbon-11 labelled compounds can revive and potentially be shipped to nearby PET-facilities. PET-radiopharmaceuticals with slow kinetics in comparison to their half life can still be used. As additional infrastructure and equipment will likely remain unchanged and keep the same sensitivity therefore there will be issues with kinetic modelling requiring analysis of plasma or metabolites samples with lower count rate. Besides the potential revival of failed radiopharmaceuticals, novel challenges are ahead to develop novel radiochemistry based on thus far unsuitable (low yielding or time consuming) reactions.

Extending the clinical capabilities of short- and long-lived positron-emitting radionuclides through high sensitivity PET/CT

This review describes the main benefits of using long axial field of view (LAFOV) PET in clinical applications. As LAFOV PET is the latest development in PET instrumentation, many studies are ongoing that explore the potentials of these systems, which are characterized by ultra-high sensitivity. This review not only provides an overview of the published clinical applications using LAFOV PET so far, but also provides insight in clinical applications that are currently under investigation. Apart from the straightforward reduction in acquisition times or administered amount of radiotracer, LAFOV PET also allows for other clinical applications that to date were mostly limited to research, e.g., dual tracer imaging, whole body dynamic PET imaging, omission of CT in serial PET acquisition for repeat imaging, and studying molecular interactions between organ systems. It is expected that this generation of PET systems will significantly advance the field of nuclear medicine and molecular imaging.

A methodological framework for AI-assisted diagnosis of active aortitis using radiomic analysis of FDG PET-CT images: Initial analysis

BACKGROUND

The aim of this study was to explore the feasibility of assisted diagnosis of active (peri-)aortitis using radiomic imaging biomarkers derived from [18F]-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography (FDG PET-CT) images.

METHODS

The aorta was manually segmented on FDG PET-CT in 50 patients with aortitis and 25 controls. Radiomic features (RF) (n = 107), including SUV (Standardized Uptake Value) metrics, were extracted from the segmented data and harmonized using the ComBat technique. Individual RFs and groups of RFs (i.e., signatures) were used as input in Machine Learning classifiers. The diagnostic utility of these classifiers was evaluated with area under the receiver operating characteristic curve (AUC) and accuracy using the clinical diagnosis as the ground truth.

RESULTS

Several RFs had high accuracy, 84% to 86%, and AUC scores 0.83 to 0.97 when used individually. Radiomic signatures performed similarly, AUC 0.80 to 1.00.

CONCLUSION

A methodological framework for a radiomic-based approach to support diagnosis of aortitis was outlined. Selected RFs, individually or in combination, showed similar performance to the current standard of qualitative assessment in terms of AUC for identifying active aortitis. This framework could support development of a clinical decision-making tool for a more objective and standardized assessment of aortitis.

Shortened duration whole body 18F-FDG PET Patlak imaging on the Biograph Vision Quadra PET/CT using a population-averaged input function

Background

Excellent performance characteristics of the Vision Quadra PET/CT, e.g. a substantial increase in sensitivity, allow for precise measurements of image-derived input functions (IDIF) and tissue time activity curves. Previously we have proposed a method for a reduced 30 min (as opposed to 60 min) whole body ¹⁸F-FDG Patlak PET imaging procedure using a previously published population-averaged input function (PIF) scaled to IDIF values at 30–60 min post-injection (p.i.). The aim of the present study was to apply this method using the Vision Quadra PET/CT, including the use of a PIF to allow for shortened scan durations.

Methods

Twelve patients with suspected lung malignancy were included and received a weight-based injection of ¹⁸F-FDG. Patients underwent a 65-min dynamic PET acquisition which were reconstructed using European Association of Nuclear Medicine Research Ltd. (EARL) standards 2 reconstruction settings. A volume of interest (VOI) was placed in the ascending aorta (AA) to obtain the IDIF. An external PIF was scaled to IDIF values at 30–60, 40–60, and 50–60 min p.i., respectively, and parametric ¹⁸F-FDG influx rate constant (K_i) images were generated using a t* of 30, 40 or 50 min, respectively. Herein, tumour lesions as well as healthy tissues, i.e. liver, muscle tissue, spleen and grey matter, were segmented.

Results

Good agreement between the IDIF and corresponding PIF scaled to 30–60 min p.i. and 40–60 min p.i. was obtained with 7.38% deviation in K_i. Bland–Altman plots showed excellent agreement in K_i obtained using the PIF scaled to the IDIF at 30–60 min p.i. and at 40–60 min p.i. as all data points were within the limits of agreement (LOA) (− 0.004–0.002, bias: − 0.001); for the 50–60 min p.i. K_i, all except one data point fell in between the LOA (− 0.021–0.012, bias: − 0.005).

Conclusions

Parametric whole body ¹⁸F-FDG Patlak K_i images can be generated non-invasively on a Vision Quadra PET/CT system. In addition, using a scaled PIF allows for a substantial (factor 2 to 3) reduction in scan time without substantial loss of accuracy (7.38% bias) and precision (image quality and noise interference).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-022-00504-9.

Utility of pre-treatment FDG PET/CT-derived machine learning models for outcome prediction in classical Hodgkin lymphoma

Objectives

Relapse occurs in ~20% of patients with classical Hodgkin lymphoma (cHL) despite treatment adaption based on 2-deoxy-2-[¹⁸F]fluoro-d-glucose positron emission tomography/computed tomography response. The objective was to evaluate pre-treatment FDG PET/CT–derived machine learning (ML) models for predicting outcome in patients with cHL.

Methods

All cHL patients undergoing pre-treatment PET/CT at our institution between 2008 and 2018 were retrospectively identified. A 1.5 × mean liver standardised uptake value (SUV) and a fixed 4.0 SUV threshold were used to segment PET/CT data. Feature extraction was performed using PyRadiomics with ComBat harmonisation. Training (80%) and test (20%) cohorts stratified around 2-year event-free survival (EFS), age, sex, ethnicity and disease stage were defined. Seven ML models were trained and hyperparameters tuned using stratified 5-fold cross-validation. Area under the curve (AUC) from receiver operator characteristic analysis was used to assess performance.

Results

A total of 289 patients (153 males), median age 36 (range 16–88 years), were included. There was no significant difference between training (n = 231) and test cohorts (n = 58) (p value > 0.05). A ridge regression model using a 1.5 × mean liver SUV segmentation had the highest performance, with mean training, validation and test AUCs of 0.82 ± 0.002, 0.79 ± 0.01 and 0.81 ± 0.12. However, there was no significant difference between a logistic model derived from metabolic tumour volume and clinical features or the highest performing radiomic model.

Conclusions

Outcome prediction using pre-treatment FDG PET/CT–derived ML models is feasible in cHL patients. Further work is needed to determine optimum predictive thresholds for clinical use.

Key points

• A fixed threshold segmentation method led to more robust radiomic features.

• A radiomic-based model for predicting 2-year event-free survival in classical Hodgkin lymphoma patients is feasible.

• A predictive model based on ridge regression was the best performing model on our dataset.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-09039-0.

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.

Evaluation of STIR Library Adapted for PET Scanners with Non-Cylindrical Geometry

Software for Tomographic Image Reconstruction (STIR) is an open source C++ library used to reconstruct single photon emission tomography and positron emission tomography (PET) data. STIR has an experimental scanner geometry modelling feature to accurately model detector placement. In this study, we test and improve this new feature using several types of data: Monte Carlo simulations and measured phantom data acquired from a dedicated brain PET prototype scanner. The results show that the new geometry class applied to non-cylindrical PET scanners improved spatial resolution, uniformity, and image contrast. These are directly observed in the reconstructions of small features in the test quality phantom. Overall, we conclude that the revised "BlocksOnCylindrical" class will be a valuable addition to the next STIR software release with adjustments of existing features (Single Scatter Simulation, forward projection, attenuation corrections) to "BlocksOnCylindrical".

NEMA characterization of the SAFIR prototype PET insert

Background

The SAFIR prototype insert is a preclinical Positron Emission Tomography (PET) scanner built to acquire dynamic images simultaneously with a 7 T Bruker Magnetic Resonance Imaging (MRI) scanner. The insert is designed to perform with an excellent coincidence resolving time of 194 ps Full Width Half Maximum (FWHM) and an energy resolution of 13.8% FWHM. These properties enable it to acquire precise quantitative images at activities as high as 500 MBq suitable for studying fast biological processes within short time frames (< 5 s). In this study, the performance of the SAFIR prototype insert is evaluated according to the NEMA NU 4-2008 standard while the insert is inside the MRI without acquiring MRI data.

Results

Applying an energy window of 391–601 keV and a coincidence time window of 500 ps the following results are achieved. The average spatial resolution at 5 mm radial offset is 2.6 mm FWHM when using the Filtered Backprojection 3D Reprojection (FBP3DRP) reconstruction method, improving to 1.2 mm when using the Maximum Likelihood Expectation Maximization (MLEM) method. The peak sensitivity at the center of the scanner is 1.06%. The Noise Equivalent count Rate (NECR) is 799 kcps at the highest measured activity of 537 MBq for the mouse phantom and 121 kcps at the highest measured activity of 624 MBq for the rat phantom. The NECR peak is not yet reached for any of the measurements. The scatter fractions are 10.9% and 17.8% for the mouse and rat phantoms, respectively. The uniform region of the image quality phantom has a 3.0% STD, with a 4.6% deviation from the expected number of counts per voxel. The spill-over ratios for the water and air chambers are 0.18 and 0.17, respectively.

Conclusions

The results satisfy all the requirements initially considered for the insert, proving that the SAFIR prototype insert can obtain dynamic images of small rodents at high activities (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim$$\end{document}∼ 500 MBq) with a high sensitivity and an excellent count-rate performance.

Exploring the Utility of Radiomic Feature Extraction to Improve the Diagnostic Accuracy of Cardiac Sarcoidosis Using FDG PET

Background

This study aimed to explore the radiomic features from PET images to detect active cardiac sarcoidosis (CS).

Methods

Forty 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.

Results

For 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, &gt;0.85. Twenty-two (from segmentation A) and thirty-five (from segmentation B) of 75 radiomic features fulfilled the criteria: P-value &lt; 0.00061 (after Bonferroni correction), AUC &gt;0.5, and accuracy &gt;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 &gt;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).

Conclusions

Radiomic 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.

Assessment of different quantification metrics of [18F]-NaF PET/CT images of patients with abdominal aortic aneurysm

BACKGROUND

We aim to assess the spill-in effect and the benefit in quantitative accuracy for [18F]-NaF PET/CT imaging of abdominal aortic aneurysms (AAA) using the background correction (BC) technique.

METHODS

Seventy-two datasets of patients diagnosed with AAA were reconstructed with ordered subset expectation maximization algorithm incorporating point spread function (PSF). Spill-in effect was investigated for the entire aneurysm (AAA), and part of the aneurysm excluding the region close to the bone (AAAexc). Quantifications of PSF and PSF+BC images using different thresholds (% of max. SUV in target regions-of-interest) to derive target-to-background (TBR) values (TBRmax, TBR90, TBR70 and TBR50) were compared at 3 and 10 iterations.

RESULTS

TBR differences were observed between AAA and AAAexc due to spill-in effect from the bone into the aneurysm. TBRmax showed the highest sensitivity to the spill-in effect while TBR50 showed the least. The spill-in effect was reduced at 10 iterations compared to 3 iterations, but at the expense of reduced contrast-to-noise ratio (CNR). TBR50 yielded the best trade-off between increased CNR and reduced spill-in effect. PSF+BC method reduced TBR sensitivity to spill-in effect, especially at 3 iterations, compared to PSF (P-value ≤ 0.05).

CONCLUSION

TBR50 is robust metric for reduced spill-in and increased CNR.

SAFIR-I: Design and Performance of a High-Rate Preclinical PET Insert for MRI

(1) Background: Small Animal Fast Insert for MRI detector I (SAFIR-I) is a preclinical Positron Emission Tomography (PET) insert for the Bruker BioSpec 70/30 Ultra Shield Refrigerated (USR) preclinical 7T Magnetic Resonance Imaging (MRI) system. It is designed explicitly for high-rate kinetic studies in mice and rats with injected activities reaching 500MBq, enabling truly simultaneous quantitative PET and Magnetic Resonance (MR) imaging with time frames of a few seconds in length. (2) Methods: SAFIR-I has an axial field of view of 54.2mm and an inner diameter of 114mm. It employs Lutetium Yttrium OxyorthoSilicate (LYSO) crystals and Multi Pixel Photon Counter (MPPC) arrays. The Position-Energy-Timing Application Specific Integrated Circuit, version 6, Single Ended (PETA6SE) digitizes the MPPC signals and provides time stamps and energy information. (3) Results: SAFIR-I is MR-compatible. The system's Coincidence Resolving Time (CRT) and energy resolution are between separate-uncertainty 209.0(3)ps and separate-uncertainty 12.41(02) Full Width at Half Maximum (FWHM) at low activity and separate-uncertainty 326.89(12)ps and separate-uncertainty 20.630(011) FWHM at 550MBq, respectively. The peak sensitivity is ∼1.6. The excellent performance facilitated the successful execution of first in vivo rat studies beyond 300MBq. Based on features visible in the acquired images, we estimate the spatial resolution to be ∼2mm in the center of the Field Of View (FOV). (4) Conclusion: The SAFIR-I PET insert provides excellent performance, permitting simultaneous in vivo small animal PET/MR image acquisitions with time frames of a few seconds in length at activities of up to 500MBq.

Cell proliferation detected using [18F]FLT PET/CT as an early marker of abdominal aortic aneurysm

BACKGROUND

Abdominal aortic aneurysm (AAA) is a focal aortic dilatation progressing towards rupture. Non-invasive AAA-associated cell proliferation biomarkers are not yet established. We investigated the feasibility of the cell proliferation radiotracer, fluorine-18-fluorothymidine ([18F]FLT) with positron emission tomography/computed tomography (PET/CT) in a progressive pre-clinical AAA model (angiotensin II, AngII infusion).

METHODS AND RESULTS

Fourteen-week-old apolipoprotein E-knockout (ApoE-/-) mice received saline or AngII via osmotic mini-pumps for 14 (n = 7 and 5, respectively) or 28 (n = 3 and 4, respectively) days and underwent 90-minute dynamic [18F]FLT PET/CT. Organs were harvested from independent cohorts for gamma counting, ultrasound scanning, and western blotting. [18F]FLT uptake was significantly greater in 14- (n = 5) and 28-day (n = 3) AAA than in saline control aortae (n = 5) (P < 0.001), which reduced between days 14 and 28. Whole-organ gamma counting confirmed greater [18F]FLT uptake in 14-day AAA (n = 9) compared to saline-infused aortae (n = 4) (P < 0.05), correlating positively with aortic volume (r = 0.71, P < 0.01). Fourteen-day AAA tissue showed increased expression of thymidine kinase-1, equilibrative nucleoside transporter (ENT)-1, ENT-2, concentrative nucleoside transporter (CNT)-1, and CNT-3 than 28-day AAA and saline control tissues (n = 3 each) (all P < 0.001).

CONCLUSIONS

[18F]FLT uptake is increased during the active growth phase of the AAA model compared to saline control mice and late-stage AAA.

Prospect of positron emission tomography for abdominal aortic aneurysm risk stratification

Abdominal aortic aneurysm (AAA) disease is characterized by an asymptomatic, permanent, focal dilatation of the abdominal aorta progressing towards rupture, which confers significant mortality. Patient management and surgical decisions rely on aortic diameter measurements via abdominal ultrasound surveillance. However, AAA rupture can occur at small diameters or may never occur at large diameters, implying that anatomical size is not necessarily a sufficient indicator. Molecular imaging may help identify high-risk patients through AAA evaluation independent of aneurysm size, and there is the question of the potential role of positron emission tomography (PET) and emerging role of novel radiotracers for AAA. Therefore, this review summarizes PET studies conducted in the last 10 years and discusses the usefulness of PET radiotracers for AAA risk stratification. The most frequently reported radiotracer was [18F]fluorodeoxyglucose, indicating inflammatory activity and reflecting the biomechanical properties of AAA. Emerging radiotracers include [18F]-labeled sodium fluoride, a calcification marker, [64Cu]DOTA-ECL1i, an indicator of chemokine receptor type 2 expression, and [18F]fluorothymidine, a marker of cell proliferation. For novel radiotracers, preliminary trials in patients are warranted before their widespread clinical implementation. AAA rupture risk is challenging to evaluate; therefore, clinicians may benefit from PET-based risk assessment to guide patient management and surgical decisions.

Iterative reconstruction incorporating background correction improves quantification of [18F]-NaF PET/CT images of patients with abdominal aortic aneurysm

BACKGROUND

A confounding issue in [18F]-NaF PET/CT imaging of abdominal aortic aneurysms (AAA) is the spill in contamination from the bone into the aneurysm. This study investigates and corrects for this spill in contamination using the background correction (BC) technique without the need to manually exclude the part of the AAA region close to the bone.

METHODS

Seventy-two (72) datasets of patients with AAA were reconstructed with the standard ordered subset expectation maximization (OSEM) algorithm incorporating point spread function (PSF) modelling. The spill in effect in the aneurysm was investigated using two target regions of interest (ROIs): one covering the entire aneurysm (AAA), and the other covering the aneurysm but excluding the part close to the bone (AAAexc). ROI analysis was performed by comparing the maximum SUV in the target ROI (SUVmax(T)), the corrected cSUVmax (SUVmax(T) - SUVmean(B)) and the target-to-blood ratio (TBR = SUVmax(T)/SUVmean(B)) with respect to the mean SUV in the right atrium region.

RESULTS

There is a statistically significant higher [18F]-NaF uptake in the aneurysm than normal aorta and this is not correlated with the aneurysm size. There is also a significant difference in aneurysm uptake for OSEM and OSEM + PSF (but not OSEM + PSF + BC) when quantifying with AAA and AAAexc due to the spill in from the bone. This spill in effect depends on proximity of the aneurysms to the bone as close aneurysms suffer more from spill in than farther ones.

CONCLUSION

The background correction (OSEM + PSF + BC) technique provided more robust AAA quantitative assessments regardless of the AAA ROI delineation method, and thus it can be considered as an effective spill in correction method for [18F]-NaF AAA studies.

Multimodal phantoms for clinical PET/MRI

Phantoms are commonly used throughout medical imaging and medical physics for a multitude of applications, the designs of which vary between modalities and clinical or research requirements. Within positron emission tomography (PET) and nuclear medicine, phantoms have a well-established role in the validation of imaging protocols so as to reduce the administration of radioisotope to volunteers. Similarly, phantoms are used within magnetic resonance imaging (MRI) to perform quality assurance on clinical scanners, and gel-based phantoms have a longstanding use within the MRI research community as tissue equivalent phantoms. In recent years, combined PET/MRI scanners for simultaneous acquisition have entered both research and clinical use. This review explores the designs and applications of phantom work within the field of simultaneous acquisition PET/MRI as published over the period of a decade. Common themes in the design, manufacture and materials used within phantoms are identified and the solutions they provided to research in PET/MRI are summarised. Finally, the challenges remaining in creating multimodal phantoms for use with simultaneous acquisition PET/MRI are discussed. No phantoms currently exist commercially that have been designed and optimised for simultaneous PET/MRI acquisition. Subsequently, commercially available PET and nuclear medicine phantoms are often utilised, with CT-based attenuation maps substituted for MR-based attenuation maps due to the lack of MR visibility in phantom housing. Tissue equivalent and anthropomorphic phantoms are often developed by research groups in-house and provide customisable alternatives to overcome barriers such as MR-based attenuation correction, or to address specific areas of study such as motion correction. Further work to characterise materials and manufacture methods used in phantom design would facilitate the ability to reproduce phantoms across sites.

Synergistic tomographic image reconstruction: part 2

This special issue is the second part of a themed issue that focuses on synergistic tomographic image reconstruction and includes a range of contributions in multiple disciplines and application areas. The primary subject of study lies within inverse problems which are tackled with various methods including statistical and computational approaches. This volume covers algorithms and methods for a wide range of imaging techniques such as spectral X-ray computed tomography (CT), positron emission tomography combined with CT or magnetic resonance imaging, bioluminescence imaging and fluorescence-mediated imaging as well as diffuse optical tomography combined with ultrasound. Some of the articles demonstrate their utility on real-world challenges, either medical applications (e.g. motion compensation for imaging patients) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issues is to bring together different scientific communities which do not usually interact as they do not share the same platforms such as journals and conferences. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging

Subject motion in positron emission tomography (PET) is a key factor that degrades image resolution and quality, limiting its potential capabilities. Correcting for it is complicated due to the lack of sufficient measured PET data from each position. This poses a significant barrier in calculating the amount of motion occurring during a scan. Motion correction can be implemented at different stages of data processing either during or after image reconstruction, and once applied accurately can substantially improve image quality and information accuracy. With the development of integrated PET-MRI (magnetic resonance imaging) scanners, internal organ motion can be measured concurrently with both PET and MRI. In this review paper, we explore the synergistic use of PET and MRI data to correct for any motion that affects the PET images. Different types of motion that can occur during PET-MRI acquisitions are presented and the associated motion detection, estimation and correction methods are reviewed. Finally, some highlights from recent literature in selected human and animal imaging applications are presented and the importance of motion correction for accurate kinetic modelling in dynamic PET-MRI is emphasized. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Four-Dimensional Flow Magnetic Resonance Imaging in the Assessment of Blood Flow in the Heart and Great Vessels: A Systematic Review

Four-dimensional (4D) flow magnetic resonance imaging (MRI) allows multidirectional quantification of blood flow in the heart and great vessels. Comparability of the technique to the current reference standards of flow assessment-two-dimensional (2D) flow MRI and Doppler echocardiography-varies in the literature. Image acquisition parameters likely impact upon the accuracy and reproducibility of 4D flow MRI. We therefore sought to review the current literature on 4D flow MRI in the heart and great vessels, in comparison to 2D flow MRI, Doppler echocardiography, and invasive catheterization. Using a predefined search strategy and inclusion and exclusion criteria, the databases EMBASE and Medline were searched in January 2021 for peer-reviewed research articles comparing cardiac 4D flow MRI to 2D flow MRI, Doppler echocardiography and/or invasive catheterization. The data from all relevant articles were assimilated and analyzed using Mann-Whitney U and chi χ² test. Forty-four manuscripts met the eligibility criteria and were included in the review. The review showed agreement of 4D flow MRI to the reference standard methods of flow assessment, particular in the measurement of peak velocity and stroke volume in 55% of manuscripts. The use of valve tracking significantly improves agreement between 4D flow MRI and the reference modalities (79% matching with the use of valve tracking vs. 50% without, P = 0.04). This review highlights that the impact of acquisition parameters on 4D flow MRI accuracy is multifactorial. It is therefore important that each center conducts its own quality assurance prior to using 4D flow MRI for clinical decision-making. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

[18F]Fluorothymidine Uptake in the Porcine Pancreatic Elastase-Induced Model of Abdominal Aortic Aneurysm

The porcine pancreatic elastase (PPE) model is a common preclinical model of abdominal aortic aneurysms (AAA). Some notable characteristics of this model include the low aortic rupture rate, non-progressive disease course, and infra-renal AAA formation. Enhanced [18F]fluorothymidine ([18F]FLT) uptake on positron emission tomography/computed tomography (PET/CT) has previously been reported in the angiotensin II-induced murine model of AAA. Here, we report our preliminary findings of investigating [18F]FLT uptake in the PPE murine model of AAA. [18F]FLT uptake was found to be substantially increased in the abdominal areas recovering from the surgery, whilst it was not found to be significantly increased within the PPE-induced AAA, as confirmed using in vivo PET/CT and ex vivo whole-organ gamma counting (PPE, n = 7; controls, n = 3). This finding suggests that the [18F]FLT may not be an appropriate radiotracer for this specific AAA model, and further studies with larger sample sizes are warranted to elucidate the pathobiology contributing to the reduced uptake of [18F]FLT in this model.

Synergistic tomographic image reconstruction: part 1

This special issue focuses on synergistic tomographic image reconstruction in a range of contributions in multiple disciplines and various application areas. The topic of image reconstruction covers substantial inverse problems (Mathematics) which are tackled with various methods including statistical approaches (e.g. Bayesian methods, Monte Carlo) and computational approaches (e.g. machine learning, computational modelling, simulations). The issue is separated in two volumes. This volume focuses mainly on algorithms and methods. Some of the articles will demonstrate their utility on real-world challenges, either medical applications (e.g. cardiovascular diseases, proton therapy planning) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issue is to bring together different scientific communities which do not usually interact as they do not share the same platforms (such as journals and conferences). This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Improved identification of abdominal aortic aneurysm using the Kernelized Expectation Maximization algorithm

Abdominal aortic aneurysm (AAA) monitoring and risk of rupture is currently assumed to be correlated with the aneurysm diameter. Aneurysm growth, however, has been demonstrated to be unpredictable. Using PET to measure uptake of [¹⁸F]-NaF in calcified lesions of the abdominal aorta has been shown to be useful for identifying AAA and to predict its growth. The PET low spatial resolution, however, can affect the accuracy of the diagnosis. Advanced edge-preserving reconstruction algorithms can overcome this issue. The kernel method has been demonstrated to provide noise suppression while retaining emission and edge information. Nevertheless, these findings were obtained using simulations, phantoms and a limited amount of patient data. In this study, the authors aim to investigate the usefulness of the anatomically guided kernelized expectation maximization (KEM) and the hybrid KEM (HKEM) methods and to judge the statistical significance of the related improvements. Sixty-one datasets of patients with AAA and 11 from control patients were reconstructed with ordered subsets expectation maximization (OSEM), HKEM and KEM and the analysis was carried out using the target-to-blood-pool ratio, and a series of statistical tests. The results show that all algorithms have similar diagnostic power, but HKEM and KEM can significantly recover uptake of lesions and improve the accuracy of the diagnosis by up to 22% compared to OSEM. The same improvements are likely to be obtained in clinical applications based on the quantification of small lesions, like for example cancer. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Long axial field of view PET scanners: a road map to implementation and new possibilities

In this contribution, several opportunities and challenges for long axial field of view (LAFOV) PET are described. It is an anthology in which the main issues have been highlighted. A consolidated overview of the camera system implementation, business and financial plan, opportunities and challenges is provided. What the nuclear medicine and molecular imaging community can expect from these new PET/CT scanners is the delivery of more comprehensive information to the clinicians for advancing diagnosis, therapy evaluation and clinical research.

Imaging Biological Pathways in Abdominal Aortic Aneurysms Using Positron Emission Tomography

[Figure: see text].

Baseline PET/CT imaging parameters for prediction of treatment outcome in Hodgkin and diffuse large B cell lymphoma: a systematic review

Purpose

To systematically review the literature evaluating clinical utility of imaging metrics derived from baseline fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) for prediction of progression-free (PFS) and overall survival (OS) in patients with classical Hodgkin lymphoma (HL) and diffuse large B cell lymphoma (DLBCL).

Methods

A search of MEDLINE/PubMed, Web of Science, Cochrane, Scopus and clinicaltrials.gov databases was undertaken for articles evaluating PET/CT imaging metrics as outcome predictors in HL and DLBCL. PRISMA guidelines were followed. Risk of bias was assessed using the Quality in Prognosis Studies (QUIPS) tool.

Results

Forty-one articles were included (31 DLBCL, 10 HL). Significant predictive ability was reported in 5/20 DLBCL studies assessing SUVmax (PFS: HR 0.13–7.35, OS: HR 0.83–11.23), 17/19 assessing metabolic tumour volume (MTV) (PFS: HR 2.09–11.20, OS: HR 2.40–10.32) and 10/13 assessing total lesion glycolysis (TLG) (PFS: HR 1.078–11.21, OS: HR 2.40–4.82). Significant predictive ability was reported in 1/4 HL studies assessing SUVmax (HR not reported), 6/8 assessing MTV (PFS: HR 1.2–10.71, OS: HR 1.00–13.20) and 2/3 assessing TLG (HR not reported). There are 7/41 studies assessing the use of radiomics (4 DLBCL, 2 HL); 5/41 studies had internal validation and 2/41 included external validation. All studies had overall moderate or high risk of bias.

Conclusion

Most studies are retrospective, underpowered, heterogenous in their methodology and lack external validation of described models. Further work in protocol harmonisation, automated segmentation techniques and optimum performance cut-off is required to develop robust methodologies amenable for clinical utility.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05233-2.

Hybrid PET- and MR-driven attenuation correction for enhanced 18F-NaF and 18F-FDG quantification in cardiovascular PET/MR imaging

BACKGROUND

The standard MR Dixon-based attenuation correction (AC) method in positron emission tomography/magnetic resonance (PET/MR) imaging segments only the air, lung, fat and soft-tissues (4-class), thus neglecting the highly attenuating bone tissues and affecting quantification in bones and adjacent vessels. We sought to address this limitation by utilizing the distinctively high bone uptake rate constant Ki expected from 18F-Sodium Fluoride (18F-NaF) to segment bones from PET data and support 5-class hybrid PET/MR-driven AC for 18F-NaF and 18F-Fluorodeoxyglucose (18F-FDG) PET/MR cardiovascular imaging.

METHODS

We introduce 5-class Ki/MR-AC for (i) 18F-NaF studies where the bones are segmented from Patlak Ki images and added as the 5th tissue class to the MR Dixon 4-class AC map. Furthermore, we propose two alternative dual-tracer protocols to permit 5-class Ki/MR-AC for (ii) 18F-FDG-only data, with a streamlined simultaneous administration of 18F-FDG and 18F-NaF at 4:1 ratio (R4:1), or (iii) for 18F-FDG-only or both 18F-FDG and 18F-NaF dual-tracer data, by administering 18F-NaF 90 minutes after an equal 18F-FDG dosage (R1:1). The Ki-driven bone segmentation was validated against computed tomography (CT)-based segmentation in rabbits, followed by PET/MR validation on 108 vertebral bone and carotid wall regions in 16 human volunteers with and without prior indication of carotid atherosclerosis disease (CAD).

RESULTS

In rabbits, we observed similar (< 1.2% mean difference) vertebral bone 18F-NaF SUVmean scores when applying 5-class AC with Ki-segmented bone (5-class Ki/CT-AC) vs CT-segmented bone (5-class CT-AC) tissue. Considering the PET data corrected with continuous CT-AC maps as gold-standard, the percentage SUVmean bias was reduced by 17.6% (18F-NaF) and 15.4% (R4:1) with 5-class Ki/CT-AC vs 4-class CT-AC. In humans without prior CAD indication, we reported 17.7% and 20% higher 18F-NaF target-to-background ratio (TBR) at carotid bifurcations wall and vertebral bones, respectively, with 5- vs 4-class AC. In the R4:1 human cohort, the mean 18F-FDG:18F-NaF TBR increased by 12.2% at carotid bifurcations wall and 19.9% at vertebral bones. For the R1:1 cohort of subjects without CAD indication, mean TBR increased by 15.3% (18F-FDG) and 15.5% (18F-NaF) at carotid bifurcations and 21.6% (18F-FDG) and 22.5% (18F-NaF) at vertebral bones. Similar TBR enhancements were observed when applying the proposed AC method to human subjects with prior CAD indication.

CONCLUSIONS

Ki-driven bone segmentation and 5-class hybrid PET/MR-driven AC is feasible and can significantly enhance 18F-NaF and 18F-FDG contrast and quantification in bone tissues and carotid walls.

Comparison of Correction Techniques for the Spill in Effect in Emission Tomography

In positron emission tomography (PET) imaging, accurate clinical assessment is often affected by the partial volume effect (PVE) leading to overestimation (spill-in) or underestimation (spill-out) of activity in various small regions. The spill-in correction, in particular, can be very challenging when the target region is close to a hot background region. Therefore, this study evaluates and compares the performance of various recently developed spill-in correction techniques, namely: background correction (BC), local projection (LP), and hybrid kernelized (HKEM) methods. We used a simulated digital phantom and [¹⁸F]-NaF PET data of three patients with abdominal aortic aneurysms (AAA) acquired with Siemens Biograph mMR™ and mCT™ scanners respectively. Region of Interest (ROI) analysis was performed and the extracted SUV _mean , SUV _max and target-to-background ratio (TBR) scores were compared. Results showed substantial spill-in effects from hot regions to targeted regions, which are more prominent in small structures. The phantom experiment demonstrated the feasibility of spill-in correction with all methods. For the patient data, large differences in SUV _mean , SUV _max and TBR _max scores were observed between the ROIs drawn over the entire aneurysm and ROIs excluding some regions close to the bone. Overall, BC yielded the best performance in spill-in correction in both phantom and patient studies.

PET image reconstruction using physical and mathematical modelling for time of flight PET-MR scanners in the STIR library

This work demonstrates how computational and physical modelling of the positron emission tomography (PET) image acquisition process for a state-of-the-art integrated PET and magnetic resonance imaging (PET-MR) system can produce images comparable to the manufacturer. The GE SIGNA PET/MR scanner is manufactured by General Electric and has time-of-flight (TOF) capabilities of about 390 ps. All software development took place in the Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) library, which is a widely used open source software to reconstruct data as exported from emission tomography scanners. The new software developments will be integrated into STIR, providing the opportunity for researchers worldwide to establish and expand their image reconstruction methods. Furthermore, this work is of particular significance as it provides the first validation of TOF PET image reconstruction for real scanner datasets using the STIR library. This paper presents the methodology, analysis, and critical issues encountered in implementing an independent reconstruction software package. Acquired PET data were processed via several appropriate algorithms which are necessary to produce an accurate and precise quantitative image. This included mathematical, physical and anatomical modelling of the patient and simulation of various aspects of the acquisition. These included modelling of random coincidences using 'singles' rates per crystals, detector efficiencies and geometric effects. Attenuation effects were calculated by using the STIR's attenuation correction model. Modelling all these effects within the system matrix allowed the reconstruction of PET images which demonstrates the metabolic uptake of the administered radiopharmaceutical. These implementations were validated using measured phantom and clinical datasets. The developments are tested using the ordered subset expectation maximisation (OSEM) and the more recently proposed kernelised expectation maximisation (KEM) algorithm which incorporates anatomical information from MR images into PET reconstruction.

Implementation of cylindrical PET scanners with block detector geometry in STIR

BACKGROUND

Software for Tomographic Image Reconstruction (STIR) is an open-source library for PET and SPECT image reconstruction, implementing iterative reconstruction as well as 2D- and 3D-filtered back projection. Quantitative reconstruction of PET data requires the knowledge of the scanner geometry. Typical scanners, clinical as well as pre-clinical ones, use a block-type geometry. Several rectangular blocks of crystals are arranged into regular polygons. Multiple of such polygons are arranged along the scanner axis. However, the geometrical representation of a scanner provided by STIR is a cylinder made of rings of individual crystals equally distributed in axial and transaxial directions. The data of realistic scanners are projected onto such virtual scanners prior to image reconstruction. This results in reduced quality of the reconstructed image. In this study, we implemented the above-described block geometry into the STIR library, permitting the image reconstruction without the interpolation step. In order to evaluate the difference in image quality, we performed Monte Carlo simulation studies of three different scanner designs: two scanners with multiple crystals per block and one with a single crystal per block. Simulated data were reconstructed using the standard STIR method and the newly implemented block geometry.

RESULTS

Visual comparison between the images reconstructed by the two models for the block-type scanners shows that the new implementation enhances the image quality to the extent that the results before normalization correction are comparable with those after normalization correction. The simulation result of a uniform cylinder shows that the coefficient of variation decreases from 25.8% to 20.9% by using the new implementation in STIR. Spatial resolution is enhanced resulting in a lower partial loss of intensity in sources of small size, e.g., the spill-over ratio for spherical sources of 1.8 mm diameter is 0.19 in the block and 0.34 in the cylindrical model.

CONCLUSIONS

Results indicate a significant improvement for the new model in comparison with the old one which mapped the polygonal geometry into a cylinder. The new implementation was tested and is available for use via the library of Swiss Federal Institute of Technology in Zurich (ETH).