Improving SUVR quantification by correcting for radiotracer clearance in tissue

Standardized Uptake Value Ratio (SUVR) is a widely reported semi-quantitative positron emission tomography (PET) outcome measure, partly because of its ease of measurement from short scan durations. However, in brain, SUVR is often a biased estimator of the gold-standard distribution volume ratio (DVR) due to non-equilibrium conditions, i.e., clearance of the radiotracer in relevant tissues. Factors that affect radiotracer metabolism and clearance such as medication or subject groups could lead to artificial differences in SUVR. This work developed a correction that reduces the bias in SUVR (estimated from a short 15-30 min PET imaging session) by accounting for the effects of tracer clearance observed during the late SUVR time window. The proposed correction takes the form of a one-step non-linear algebraic transform of SUVR that is a function of radiotracer dependent parameters such as clearance rates from the reference and target tissues, and population averaged reference region clearance rate (k 2 , ref ). An important observation was the need for accurate estimation of radiotracer clearance rate in target tissue, which was addressed with a regression based model. Simulations and human data from two different radiotracers (healthy controls for [11C]LSN3172176, healthy controls and Parkinson's disease subjects for [18F]FE-PE2I) were used to validate the correction and evaluate its benefits and limitations. SUVR correction in human data significantly reduced mean SUVR bias across brain regions and subjects (from ∼25% for SUVR to <10% for corrected SUVR). This correction also significantly reduced the variability of this bias across brain regions for both tracers (approximately 50% for [11C]LSN3172176, 20% for [18F]FE-PE2I). Future work should investigate the benefits of using corrected SUVR in other populations and with different tracers.

Comparison of SUVA/V and SUVA-V for Evaluating Atherosclerotic Inflammation in 18F-FDG PET/CT

Purpose

This study aimed to compare the clinical significance of two parameters, division of standardized uptake value (SUV) of target arterial activity by background venous blood pool activity (SUVA/V) and subtraction of background venous blood pool activity from SUV of target arterial activity (SUVA-V) of carotid arteries with atherosclerotic plaques using 18F-fluorodeoxyglucose (FDG) positron emission tomography and computed tomography (PET/CT).

Methods

Patients aged 50 years or more who were diagnosed with carotid artery stenosis of 50% or more with carotid Doppler ultrasonography and had torso 18F-FDG PET/CT were enrolled retrospectively and classified patients who developed cerebrovascular events (CVEs) within 5 years after 18F-FDG PET/CT scan as the active group and patients who did not experience the CVE within 5 years as an inactive group. We calculated SUVA/V and SUVA-V using measurements of SUVmax of carotid arteries and mean SUV of superior vena cava (SVC).

Results

SUVA-V, SUVA-V_high, and SUVA-V_low were significantly higher in the active group than in the inactive group, but neither SUVA/V, SUVA/V_high, nor SUVA/V_low showed significant differences between the active and inactive groups. The difference in rank between groups of SUVA/V_high and SUVA/V_low was greater than the difference in rank between groups of SUVA-V_high and SUVA-V_low. The CVE incidence differed between SUVA/V_high and SUVA/V_low of high carotid FDG uptake, but the CVE incidence did not differ between SUVA-V_high and SUVA-V_low of high carotid FDG uptake.

Conclusion

SUVA-V may be a more rational solution than SUVA/V for evaluating atherosclerotic plaque inflammation on 18F-FDG PET/CT.

Comparison of quantitative [11C]PE2I brain PET studies between an integrated PET/MR and a stand-alone PET system

PET/MR systems demanded great efforts for accurate attenuation correction (AC) but differences in technology, geometry and hardware attenuation may also affect quantitative results. Dedicated PET systems using transmission-based AC are regarded as the gold standard for quantitative brain PET. The study aim was to investigate the agreement between quantitative PET outcomes from a PET/MR scanner against a stand-alone PET system. Nine patients with Parkinsonism underwent two 80-min dynamic PET scans with the dopamine transporter ligand [11C]PE2I. Images were reconstructed with resolution-matched settings using 68Ge-transmission (stand-alone PET), and zero-echo-time MR (PET/MR) scans for AC. Non-displaceable binding potential (BPND) and relative delivery (R1) were evaluated using volumes of interest and voxel-wise analysis. Correlations between systems were high (r ≥ 0.85) for both quantitative outcome parameters in all brain regions. Striatal BPND was significantly lower on PET/MR than on stand-alone PET (-7%). R1 was significantly overestimated in posterior cortical regions (9%) and underestimated in striatal (-9%) and limbic areas (-6%). The voxel-wise evaluation revealed that the MR-safe headphones caused a negative bias in both parametric BPND and R1 images. Additionally, a significant positive bias of R1 was found in the auditory cortex, most likely due to the acoustic background noise during MR imaging. The relative bias of the quantitative [11C]PE2I PET data acquired from a SIGNA PET/MR system was in the same order as the expected test-retest reproducibility of [11C]PE2I BPND and R1, compared to a stand-alone ECAT PET scanner. MR headphones and background noise are potential sources of error in functional PET/MR studies.

PET imaging and quantification of small animals using a clinical SiPM-based camera

BACKGROUND

Small-animal PET imaging is an important tool in preclinical oncology. This study evaluated the ability of a clinical SiPM-PET camera to image several rats simultaneously and to perform quantification data analysis.

METHODS

Intrinsic spatial resolution was measured using 18F line sources, and image quality was assessed using a NEMA NU 4-2018 phantom. Quantification was evaluated using a fillable micro-hollow sphere phantom containing 4 spheres of different sizes (ranging from 3.95 to 7.86 mm). Recovery coefficients were computed for the maximum (Amax) and the mean (A50) pixel values measured on a 50% isocontour drawn on each sphere. Measurements were performed first with the phantom placed in the centre of the field of view and then in the off-centre position with the presence of three scattering sources to simulate the acquisition of four animals simultaneously. Quantification accuracy was finally validated using four 3D-printed phantoms mimicking rats with four subcutaneous tumours each. All experiments were performed for both 18F and 68Ga radionuclides.

RESULTS

Radial spatial resolutions measured using the PSF reconstruction algorithm were 1.80 mm and 1.78 mm for centred and off-centred acquisitions, respectively. Spill-overs in air and water and uniformity computed with the NEMA phantom centred in the FOV were 0.05, 0.1 and 5.55% for 18F and 0.08, 0.12 and 2.81% for 68Ga, respectively. Recovery coefficients calculated with the 18F-filled micro-hollow sphere phantom for each sphere varied from 0.51 to 1.43 for Amax and from 0.40 to 1.01 for A50. These values decreased from 0.28 to 0.92 for Amax and from 0.22 to 0.66 for A50 for 68 Ga acquisition. The results were not significantly different when imaging phantoms in the off-centre position with 3 scattering sources. Measurements performed with the four 3D-printed phantoms showed a good correlation between theoretical and measured activity in simulated tumours, with r2 values of 0.99 and 0.97 obtained for 18F and 68Ga, respectively.

CONCLUSION

We found that the clinical SiPM-based PET system was close to that obtained with a dedicated small-animal PET device. This study showed the ability of such a system to image four rats simultaneously and to perform quantification analysis for radionuclides commonly used in oncology.

Is there more than meets the eye in PSMA imaging in prostate cancer with PET/MRI? Looking closer at uptake time, correlation with PSA and Gleason score

BACKGROUND

In patients with increasing PSA and suspicion for prostate cancer, but previous negative biopsies, PET/MRI is used to test for tumours and target potential following biopsy. We aimed to determine different PSMA PET timing effects on signal kinetics and test its correlation with the patients' PSA and Gleason scores (GS).

METHODS

A total of 100 patients were examined for 900 s using PET/MRI approximately 1-2 h p.i. depending on the tracer used (⁶⁸Ga-PSMA-11, ¹⁸F-PSMA-1007 or ¹⁸F-rhPSMA7). The scans were reconstructed in static and dynamic mode (6 equal frames capturing "late" PSMA dynamics). TACs were computed for detected lesions as well as linear regression plots against time for static (SUV) and dynamic (SUV, SUL, and percent injected dose per gram) parameters. All computed trends were tested for correlation with PSA and GS.

RESULTS

Static and dynamic scans allowed unchanged lesion detection despite the difference in statistics. For all tracers, the lesions in the pelvic lymph nodes and bones had a mostly negative activity concentration trend (78% and 68%, resp.), while a mostly positive, stronger trend was found for the lesions in the prostate and prostatic fossa following RPE (84% and 83%, resp.). In case of ⁶⁸Ga-PSMA-11, a strong negative (R_min = - 0.62, R_max = - 0.73) correlation was found between the dynamic parameters and the PSA. ¹⁸F-PSMA-1007 dynamic data showed no correlation with PSA, while for ¹⁸F-rhPSMA7 dynamic data, it was consistently low positive (R_min = 0.29, R_max = 0.33). All tracers showed only moderate correlation against GS (R_min = 0.41, R_max = 0.48). The static parameters showed weak correlation with PSA (R_min = 0.24, R_max = 0.36) and no correlation with GS.

CONCLUSION

"Late" dynamic PSMA data provided additional insight into the PSMA kinetics. While a stable moderate correlation was found between the PSMA kinetics in pelvic lesions and GS, a significantly variable correlation with the PSA values was shown depending on the radiotracer used, the highest being consistently for ⁶⁸Ga-PSMA-11. We reason that with such late dynamics, the PSMA kinetics are relatively stable and imaging could even take place at earlier time points as is now in the clinical routine.

Method to determine the statistical technical variability of SUV metrics

BACKGROUND

The Standardized Uptake Value (SUV) Max, SUVMean, and SUVPeak are metrics used to quantify positron emission tomography (PET) images. In order to assess the significance of a change in these metrics for diagnostic purposes, it is relevant to know their variation. The sources of variation can be biological or technical. In this study, we present a method to determine the statistical technical variation of SUV in PET images.

RESULTS

This method was tested on a NEMA quality phantom with spheres of various diameters with a full-length acquisition time of 150 s per bed position and foreground-to-background activity ratio of F¹⁸-2-fluoro-2-deoxy-D-glucose (FDG) of 10:1. Our method divides the 150 s acquisition into subsets with statistically independent frames of shorter reconstruction length. SUVMax, Mean and Peak were calculated for each reconstructed image in a subset. The coefficient of variation of SUV within each subset has been used to estimate the expected coefficient of variation at 150 s reconstruction length. We report the largest coefficient of variation of the SUV metrics for the smallest sphere and the smallest variation for the largest sphere. The expected variation at 150 s reconstruction length does not exceed 6% for the smallest sphere and 2% for the largest sphere.

CONCLUSIONS

With the presented method, we aim to determine the statistical technical variation of SUV. The method enables the evaluation of the effect of SUV metric choice (Max, Mean, Peak) and lesion size on the technical variation and, therefore, to evaluate its relevance on the total variation of the SUV value between clinical studies.

Implementation of a Spatially-Variant and Tissue-Dependent Positron Range Correction for PET/CT Imaging

Aim

To develop and evaluate a new approach for spatially variant and tissue-dependent positron range (PR) correction (PRC) during the iterative PET image reconstruction.

Materials and Methods

The PR distributions of three radionuclides (¹⁸F, ⁶⁸Ga, and ¹²⁴I) were simulated using the GATE (GEANT4) framework in different material compositions (lung, water, and bone). For every radionuclide, the uniform PR kernel was created by mapping the simulated 3D PR point cloud to a 3D matrix with its size defined by the maximum PR in lung (¹⁸F) or water (⁶⁸Ga and ¹²⁴I) and the PET voxel size. The spatially variant kernels were composed from the uniform PR kernels by analyzing the material composition of the surrounding medium for each voxel before implementation as tissue-dependent, point-spread functions into the iterative image reconstruction. The proposed PRC method was evaluated using the NEMA image quality phantom (¹⁸F, ⁶⁸Ga, and ¹²⁴I); two unique PR phantoms were scanned and evaluated following OSEM reconstruction with and without PRC using different metrics, such as contrast recovery, contrast-to-noise ratio, image noise and the resolution evaluated in terms of full width at half maximum (FWHM).

Results

The effect of PRC on ¹⁸F-imaging was negligible. In contrast, PRC improved image contrast for the 10-mm sphere of the NEMA image quality phantom filled with ⁶⁸Ga and ¹²⁴I by 33 and 24%, respectively. While the effect of PRC was less noticeable for the larger spheres, contrast recovery still improved by 5%. The spatial resolution was improved by 26% for ¹²⁴I (FWHM of 4.9 vs. 3.7 mm).

Conclusion

For high energy positron-emitting radionuclides, the proposed PRC method helped recover image contrast with reduced noise levels and with improved spatial resolution. As such, the PRC approach proposed here can help improve the quality of PET data in clinical practice and research.

Critical review of PET imaging for detection and characterization of the atherosclerotic plaques with emphasis on limitations of FDG-PET compared to NaF-PET in this setting

Applications of various positron emission tomography (PET) tracers for assessing atherosclerosis have been evolving over the years. ¹⁸F-fluorodeoxyglucose (FDG)-PET was introduced in 2001 as a probe for this purpose. During the past decade, numerous papers have described a major role for sodium ¹⁸F-fluoride (NaF) as another tracer for assessing this vascular disease. We have reviewed the existing data about the merits of both techniques for assessing atherosclerosis. We have to emphasize that our team has been actively involved in conducting research with both tracers over many years. In this review, we have relied upon the data from the CAMONA study which has become a gold standard for defining the role of PET imaging in atherosclerosis. This study was one of the largest of any in recent years and has allowed comprehensive comparison between these two tracers in detecting and quantifying atherosclerosis. Based on what we have learned from this major undertaking, we believe the role of FDG-PET will be limited in assessing atherosclerosis in clinical work-up. This is relevant to both major and coronary arteries. In contrast to NaF-PET, the role of FDG-PET in assessing coronary artery atherosclerosis is almost non-existent. Based on the existing data in this domain, NaF-PET is an ideal imaging modality for both research and clinical assessment of atherosclerosis. The aim of this review is to describe the pros and cons of both approaches based on the existing data in the literature.

Evaluation of Deep Learning-based Approaches to Segment Bowel Air Pockets and Generate Pelvis Attenuation Maps from CAIPIRINHA-accelerated Dixon MR Images

Attenuation correction (AC) remains a challenge in pelvis PET/MR imaging. In addition to the segmentation/model-based approaches, deep learning methods have shown promise in synthesizing accurate pelvis attenuation maps (μ-maps). However, these methods often misclassify air pockets in the digestive tract, which can introduce bias in the reconstructed PET images. The aims of this work were to develop deep learning-based methods to automatically segment air pockets and generate pseudo-CT images from CAIPIRINHA-accelerated MR Dixon images. Methods: A convolutional neural network (CNN) was trained to segment air pockets using 3D CAIPIRINHA-accelerated MR Dixon datasets from 35 subjects and was evaluated against semi-automated segmentations. A separate CNN was trained to synthesize pseudo-CT μ-maps from the Dixon images. Its accuracy was evaluated by comparing the deep learning-, model- and CT-based μ-maps using data from 30 of the subjects. Finally, the impact of different μ-maps and air pocket segmentation methods on the PET quantification was investigated. Results: Air pockets segmented using the CNN agreed well with semi-automated segmentations, with a mean Dice similarity coefficient of 0.75. Volumetric similarity score between two segmentations was 0.85 ± 0.14. The mean absolute relative change (RCs) with respect to the CT-based μ-maps were 2.6% and 5.1% in the whole pelvis for the deep learning and model-based μ-maps, respectively. The average RC between PET images reconstructed with deep learning and CT-based μ-maps was 2.6%. Conclusion: We presented a deep learning-based method to automatically segment air pockets from CAIPIRINHA-accelerated Dixon images with comparable accuracy to semi-automatic segmentations. We also showed that the μ-maps synthesized using a deep learning-based method from CAIPIRINHA-accelerated Dixon images are more accurate than those generated with the model-based approach available on integrated PET/MRI scanner.

A dual-time-window protocol to reduce acquisition time of dynamic tau PET imaging using [18F]MK-6240

Background

[¹⁸F]MK-6240 is a PET tracer with sub-nanomolar affinity for neurofibrillary tangles. Therefore, tau quantification is possible with [¹⁸F]MK-6240 PET/CT scans, and it can be used for assessment of Alzheimer’s disease. However, long acquisition scans are required to provide fully quantitative estimates of pharmacokinetic parameters. Therefore, on the present study, dual-time-window (DTW) acquisitions was simulated to reduce PET/CT acquisition time, while taking into consideration perfusion changes and possible scanning protocol non-compliance. To that end, time activity curves (TACs) representing a 120-min acquisition (TAC₁₂₀) were simulated using a two-tissue compartment model with metabolite corrected arterial input function from 90-min dynamic [¹⁸F]MK-6240 PET scans of three healthy control subjects and five subjects with mild cognitive impairment or Alzheimer’s disease. Therefore, TACs corresponding to different levels of specific binding were generated and then various perfusion changes were simulated. Next, DTW acquisitions were simulated consisting of an acquisition starting at tracer injection, a break and a second acquisition starting at 90 min post-injection. Finally, non-compliance with the PET/CT scanning protocol were simulated to assess its impact on quantification. All TACs were quantified using reference Logan’s distribution volume ratio (DVR) and standardized uptake value ratio (SUVR₉₀) using the cerebellar cortex as reference region.

Results

It was found that DVR from a DTW protocol with a 60-min break between two 30-min dynamic scans closely approximates the DVR from the uninterrupted TAC₁₂₀, with a regional bias smaller than 2.5%. Moreover, SUVR₉₀ estimates were more susceptible (regional bias ≤ 19%) to changes in perfusion compared to DVR from a DTW TAC (regional bias ≤ 10%). Similarly, SUVR₉₀ was affected by late-time scanning protocol delays reaching an increase of 8% for a 20-min delay, while DVR was not affected (regional bias < 1.5%) by DTW protocol non-compliance.

Conclusions

Therefore, such DTW protocol has the potential to increase patient comfort and throughput without compromising quantitative accuracy and is more reliable against SUVR in terms of perfusion changes and protocol deviations, which could prove beneficial for drug effect assessment and patient follow-up using longitudinal [¹⁸F]MK-6240 PET imaging.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13550-021-00790-x.

Parametric imaging of dual-time window [18F]flutemetamol and [18F]florbetaben studies

Optimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [¹⁸F]flutemetamol and [¹⁸F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [¹⁸F]flutemetamol and [¹⁸F]florbetaben scans. Forty-six participants were scanned on a PET/MR scanner using a dual-time window protocol and either [¹⁸F]flutemetamol (N=24) or [¹⁸F]florbetaben (N=22). The following parametric approaches were used to derive DVR estimates: reference Logan (RLogan), receptor parametric mapping (RPM), two-step simplified reference tissue model (SRTM2) and multilinear reference tissue models (MRTM0, MRTM1, MRTM2), all with cerebellar grey matter as reference tissue. In addition, a standardized uptake value ratio (SUVR) was calculated for the 90-110 min post injection interval. All parametric images were assessed visually. Regional outcome measures were compared with those from a validated ROI method, i.e. DVR derived using RLogan. Visually, RPM, and SRTM2 performed best across tracers and, in addition to SUVR, provided highest AUC values for differentiating between Aβ-positive vs Aβ-negative scans ([¹⁸F]flutemetamol: range AUC=0.96-0.97 [¹⁸F]florbetaben: range AUC=0.83-0.85). Outcome parameters of most methods were highly correlated with the reference method (R²≥0.87), while lowest correlation were observed for MRTM2 (R²=0.71-0.80). Furthermore, bias was low (≤5%) and independent of underlying amyloid burden for MRTM0 and MRTM1. The optimal parametric method differed per evaluated aspect; however, the best compromise across aspects was found for MRTM0 followed by SRTM2, for both tracers. SRTM2 is the preferred method for parametric imaging because, in addition to its good performance, it has the advantage of providing a measure of relative perfusion (R₁), which is useful for measuring disease progression.

Repeatability of parametric methods for [18F]florbetapir imaging in Alzheimer's disease and healthy controls: A test-retest study

Accumulation of amyloid beta (Aβ) is one of the pathological hallmarks of Alzheimer's disease (AD), which can be visualized using [¹⁸F]florbetapir positron emission tomography (PET). The aim of this study was to evaluate various parametric methods and to assess their test-retest (TRT) reliability. Two 90 min dynamic [¹⁸F]florbetapir PET scans, including arterial sampling, were acquired (n = 8 AD patient, n = 8 controls). The following parametric methods were used; (reference:cerebellum); Logan and spectral analysis (SA), receptor parametric mapping (RPM), simplified reference tissue model2 (SRTM2), reference Logan (rLogan) and standardized uptake value ratios (SUV_r(50-70)). BP_ND+1, DVR, V_T and SUVr were compared with corresponding estimates (V_T or DVR) from the plasma input reversible two tissue compartmental (2T4k_V_B) model with corresponding TRT values for 90-scan duration. RPM (r² = 0.92; slope = 0.91), Logan (r² = 0.95; slope = 0.84) and rLogan (r² = 0.94; slope = 0.88), and SRTM2 (r² = 0.91; slope = 0.83), SA (r² = 0.91; slope = 0.88), SUVr (r² = 0.84; slope = 1.16) correlated well with their 2T4k_V_B counterparts. RPM (controls: 1%, AD: 3%), rLogan (controls: 1%, AD: 3%) and SUV_r(50-70) (controls: 3%, AD: 8%) showed an excellent TRT reliability. In conclusion, most parametric methods showed excellent performance for [¹⁸F]florbetapir, but RPM and rLogan seem the methods of choice, combining the highest accuracy and best TRT reliability.

Almost 10 years of PET/MR attenuation correction: the effect on lesion quantification with PSMA: clinical evaluation on 200 prostate cancer patients

Purpose

After a decade of PET/MR, the case of attenuation correction (AC) remains open. The initial four-compartment (air, water, fat, soft tissue) Dixon-based AC scheme has since been expanded with several features, the latest being MR field-of-view extension and a bone atlas. As this potentially changes quantification, we evaluated the impact of these features in PET AC in prostate cancer patients.

Methods

Two hundred prostate cancer patients were examined with either ¹⁸F- or ⁶⁸Ga-prostate-specific membrane antigen (PSMA) PET/MR. Qualitative and quantitative analysis (SUV_mean, SUV_max, correlation, and statistical significance) was performed on images reconstructed using different AC schemes: Dixon, Dixon+MLAA, Dixon+HUGE, and Dixon+HUGE+bones for ¹⁸F-PSMA data; Dixon and Dixon+bones for ⁶⁸Ga-PSMA data. Uptakes were compared using linear regression against standard Dixon.

Results

High correlation and no visually perceivable differences between all evaluated methods (r > 0.996) were found. The mean relative difference in lesion uptake of ¹⁸F-PSMA and ⁶⁸Ga-PSMA remained, respectively, within 4% and 3% in soft tissue, and within 10% and 9% in bones for all evaluated methods. Bone registration errors were detected, causing mean uptake change of 5% in affected lesions.

Conclusions

Based on these results and the encountered bone atlas registration inaccuracy, we deduce that including bones and extending the MR field-of-view did not introduce clinically significant differences in PSMA diagnostic accuracy and tracer uptake quantification in prostate cancer pelvic lesions, facilitating the analysis of serial studies respectively. However, in the absence of ground truth data, we advise against atlas-based methods when comparing serial scans for bone lesions.

68Ga-PSMA-11 PET has the potential to improve patient selection for extended pelvic lymph node dissection in intermediate to high-risk prostate cancer

INTRODUCTION

Radical prostatectomy with extended pelvic lymph node dissection (ePLND) is a curative treatment option for patients with clinically significant localised prostate cancer. The decision to perform an ePLND can be challenging because the overall incidence of lymph node metastasis is relatively low and ePLND is not free of complications. Using current clinical nomograms to identify patients with nodal involvement, approximately 75-85% of ePLNDs performed are negative. The aim of this study was to assess the added value of ⁶⁸Ga-PSMA-11 PET in predicting lymph node metastasis in men with intermediate- or high-risk prostate cancer.

METHODS

⁶⁸Ga-PSMA-11 PET scans of 60 patients undergoing radical prostatectomy with ePLND were reviewed for qualitative (visual) assessment of suspicious nodes and assessment of quantitative parameters of the primary tumour in the prostate (SUV_max, total activity (PSMA_total) and PSMA positive volume (PSMA_vol)). Ability of quantitative PET parameters to predict nodal metastasis was assessed with receiver operating characteristics (ROC) analysis. A multivariable logistic regression model combining PSA, Gleason score, visual nodal status on PET and primary tumour PSMA_total was built. Net benefit at each risk threshold was compared with five nomograms: MSKCC nomogram, Yale formula, Roach formula, Winter nomogram and Partin tables (2016).

RESULTS

Overall, pathology of ePLND specimens revealed 31 pelvic metastatic lymph nodes in 12 patients. ⁶⁸Ga-PSMA-11 PET visual analysis correctly detected suspicious nodes in 7 patients, yielding a sensitivity of 58% and a specificity of 98%. The area under the ROC curve for primary tumour SUV_max was 0.70, for PSMA_total 0.76 and for PSMA_vol 0.75. The optimal cut-off for nodal involvement was PSMA_total > 49.1. The PET model including PSA, Gleason score and quantitative PET parameters had a persistently higher net benefit compared with all clinical nomograms.

CONCLUSION

Our model combining PSA, Gleason score and visual lymph node analysis on ⁶⁸Ga-PSMA-11 PET with PSMA_total of the primary tumour showed a tendency to improve patient selection for ePLND over the currently used clinical nomograms. Although this result has to be validated, ⁶⁸Ga-PSMA-11 PET showed the potential to reduce unnecessary surgical procedures in patients with intermediate- or high-risk prostate cancer.

Futility of attempts to detect and quantify beta cells by PET imaging in the pancreas: why it is time to abandon the approach

In this commentary, we describe the limitations of positron emission tomography (PET) in visualising and characterising beta cell mass in the native pancreas in healthy individuals and those diagnosed with diabetes. Imaging with PET requires a large mass of targeted cells or other structures in the range of approximately 8-10 cm³. Since islets occupy only 1% of the pancreatic volume and are dispersed throughout the organ, it is our view that uptake of PET tracers, including [¹⁸F]fluoropropyl-(+)-dihydrotetrabenazine, in islets cannot be successfully detected by current imaging modalities. Therefore, we dispute the feasibility of PET imaging for the detection of loss of beta cells in the native pancreas in individuals with diabetes. However, we believe this novel approach can be successfully employed to visualise beta cell mass in individuals with hyperinsulinism and transplanted islets.

Reference tissue models in the assessment of 11 C-DTBZ binding to the VMAT2 in rat striatum: A test-retest reproducibility study

Dopaminergic PET imaging is a useful tool to assess the dopaminergic integrity and to follow-up longitudinal studies. The aim of this study was to evaluate the reliability and reproducibility of different reference tissue-based methods to determine the non-displaceable binding potential (BP_ND ) as a quantitative measure of ¹¹ C-DTBZ binding to the VMAT2 in rat striatum using cerebellum as reference region. Eight healthy Wistar rats underwent two microPET scans at the age of 12 (test) and 20 weeks (retest). BP_ND was determined using the simplified reference tissue model, Logan reference tissue model, and multilinear reference tissue models (MRTMo and MRTM2). Additionally, a striatal-to-cerebellar-ratio (SCR) analysis was performed. The reproducibility between the two scans was assessed using the interclass correlation coefficients (ICC) and the variability index. Repeatability indices showed acceptable ICC = 0.66 (SCR) to excellent ICC = 0.98 (MRTM2) reliability for this study and a variability ranging from 12.26% (SCR) to 3.28% (MRTM2). To the best of our knowledge, this is the first report on longitudinal studies for ¹¹ C-DTBZ in rats using reference tissue methods. Excellent intersubject and intrasubject reproducibility was obtained with the multilinear reference MRTM2, suggesting this as the best method to compare longitudinal studies, whereas the SCR method had poor reliability. Logan method, however, is a method simple to compute that shows accurate reproducibility with a reasonable level of inter- and intra-subject variability allowing crossover studies to follow-up the uptake of ¹¹ C-DTBZ in rat striatum.

Generation of Structural MR Images from Amyloid PET: Application to MR-Less Quantification

Structural MR images concomitantly acquired with PET images can provide crucial anatomic information for precise quantitative analysis. However, in the clinical setting, not all the subjects have corresponding MR images. Here, we developed a model to generate structural MR images from amyloid PET using deep generative networks. We applied our model to quantification of cortical amyloid load without structural MR. Methods: We used florbetapir PET and structural MR data from the Alzheimer Disease Neuroimaging Initiative database. The generative network was trained to generate realistic structural MR images from florbetapir PET images. After the training, the model was applied to the quantification of cortical amyloid load. PET images were spatially normalized to the template space using the generated MR, and then SUV ratio (SUVR) of the target regions was measured by predefined regions of interest. A real MR-based quantification was used as the gold standard to measure the accuracy of our approach. Other MR-less methods-a normal PET template-based, a multiatlas PET template-based, and a PET segmentation-based normalization/quantification-were also tested. We compared the performance of quantification methods using generated MR with that of MR-based and MR-less quantification methods. Results: Generated MR images from florbetapir PET showed signal patterns that were visually similar to the real MR. The structural similarity index between real and generated MR was 0.91 ± 0.04. The mean absolute error of SUVR of cortical composite regions estimated by the generated MR-based method was 0.04 ± 0.03, which was significantly smaller than other MR-less methods (0.29 ± 0.12 for the normal PET template, 0.12 ± 0.07 for the multiatlas PET template, and 0.08 ± 0.06 for the PET segmentation-based methods). Bland-Altman plots revealed that the generated MR-based SUVR quantification was the closest to the SUVRs estimated by the real MR-based method. Conclusion: Structural MR images were successfully generated from amyloid PET images using deep generative networks. Generated MR images could be used as templates for accurate and precise amyloid quantification. This generative method might be used to generate multimodal images of various organs for further quantitative analyses.

Impact of improved attenuation correction featuring a bone atlas and truncation correction on PET quantification in whole-body PET/MR

PURPOSE

Recent studies have shown an excellent correlation between PET/MR and PET/CT hybrid imaging in detecting lesions. However, a systematic underestimation of PET quantification in PET/MR has been observed. This is attributable to two methodological challenges of MR-based attenuation correction (AC): (1) lack of bone information, and (2) truncation of the MR-based AC maps (μmaps) along the patient arms. The aim of this study was to evaluate the impact of improved AC featuring a bone atlas and truncation correction on PET quantification in whole-body PET/MR.

METHODS

The MR-based Dixon method provides four-compartment μmaps (background air, lungs, fat, soft tissue) which served as a reference for PET/MR AC in this study. A model-based bone atlas provided bone tissue as a fifth compartment, while the HUGE method provided truncation correction. The study population comprised 51 patients with oncological diseases, all of whom underwent a whole-body PET/MR examination. Each whole-body PET dataset was reconstructed four times using standard four-compartment μmaps, five-compartment μmaps, four-compartment μmaps + HUGE, and five-compartment μmaps + HUGE. The SUV_max for each lesion was measured to assess the impact of each μmap on PET quantification.

RESULTS

All four μmaps in each patient provided robust results for reconstruction of the AC PET data. Overall, SUV_max was quantified in 99 tumours and lesions. Compared to the reference four-compartment μmap, the mean SUV_max of all 99 lesions increased by 1.4 ± 2.5% when bone was added, by 2.1 ± 3.5% when HUGE was added, and by 4.4 ± 5.7% when bone + HUGE was added. Larger quantification bias of up to 35% was found for single lesions when bone and truncation correction were added to the μmaps, depending on their individual location in the body.

CONCLUSION

The novel AC method, featuring a bone model and truncation correction, improved PET quantification in whole-body PET/MR imaging. Short reconstruction times, straightforward reconstruction workflow, and robust AC quality justify further routine clinical application of this method.

A new method to quantify tau pathologies with (11)C-PBB3 PET using reference tissue voxels extracted from brain cortical gray matter

Background

Quantitative in vivo imaging of tau pathologies potentially improves diagnostic accuracy of neurodegenerative tauopathies and would facilitate evaluation of disease-modifying drugs targeting tau lesions in these diseases. Tau pathology can be quantified by reference tissue models without arterial blood sampling when reference tissue devoid of target binding sites is available. The cerebellar cortex has been used as a reference region in analyses of tau positron emission tomography (PET) data in Alzheimer’s disease (AD). However, in a significant subset of tauopathies such as progressive supranuclear palsy and corticobasal degeneration, tau accumulation may occur in diverse brain regions including the cerebellar cortex. This hampers selection of a distinctive reference region lacking binding sites for a tau PET ligand. The purpose of this study was to develop a new method to quantify specific binding of a PET radioligand, ¹¹C-PBB3, to tau deposits using reference voxels extracted from cortical gray matter, which have a low likelihood of containing tau accumulations.

Methods

We reanalyzed ¹¹C-PBB3 PET data of seven mild AD patients (ADs) and seven elderly healthy control subjects (HCs) acquired in a previous study. As a standard method, parametric images of binding potential (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {BP}_{\mathsf{ND}}^{\ast } $$\end{document}BPND∗) were initially generated using reference tissue manually defined on the cerebellar cortex. We then constructed a frequency histogram of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {BP}_{\mathsf{ND}}^{\ast } $$\end{document}BPND∗ values in these parametric images and selected cortical gray matter voxels contained in a certain range of the histogram with a low likelihood of having ¹¹C-PBB3 binding sites. Finally, these reference voxels were used for generating new \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {BP}_{\mathsf{ND}}^{\ast } $$\end{document}BPND∗ parametric images.

Results

Reference tissue voxels defined by the histogram analysis spread throughout the cortical gray matter of AD and HC brains. The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {BP}_{\mathsf{ND}}^{\ast } $$\end{document}BPND∗ values determined by our new method correlated very well with those estimated by the standard method (r² = 0.94), although the binding estimates by the current method were slightly higher by ~0.14 than those by the standard method.

Conclusions

We developed and validated a new method enabling quantification of tau lesions that can accumulate in the cerebellum and other extensive brain areas. This method may be applicable to all tauopathy subtypes and various tau PET ligands besides ¹¹C-PBB3.

Trial registration

The number is UMIN000009052

[(11)C]TASP457, a novel PET ligand for histamine H3 receptors in human brain

PURPOSE

The histamine H3 receptors are presynaptic neuroreceptors that inhibit the release of histamine and other neurotransmitters. The receptors are considered a drug target for sleep disorders and neuropsychiatric disorders with cognitive decline. We developed a novel PET ligand for the H3 receptors, [(11)C]TASP0410457 ([(11)C]TASP457), with high affinity, selectivity and favorable kinetic properties in the monkey, and evaluated its kinetics and radiation safety profile for quantifying the H3 receptors in human brain.

METHODS

Ten healthy men were scanned for 120 min with a PET scanner for brain quantification and three healthy men were scanned for radiation dosimetry after injection of 386 ± 6.2 MBq and 190 ± 7.5 MBq of [(11)C]TASP457, respectively. For brain quantification, arterial blood sampling and metabolite analysis were performed using high-performance liquid chromatography. Distribution volumes (V T) in brain regions were determined by compartment and graphical analyses using the Logan plot and Ichise multilinear analysis (MA1). For dosimetry, radiation absorbed doses were estimated using the Medical Internal Radiation Dose scheme.

RESULTS

[(11)C]TASP457 PET showed high uptake (standardized uptake values in the range of about 3 - 6) in the brain and fast washout in cortical regions and slow washout in the pallidum. The two-tissue compartment model and graphical analyses estimated V T with excellent identification using 60-min scan data (about 16 mL/cm(3) in the pallidum, 9 - 14 in the basal ganglia, 6 - 9 in cortical regions, and 5 in the pons), which represents the known distribution of histamine H3 receptors. For parametric imaging, MA1 is recommended because of minimal underestimation with small intersubject variability. The organs with the highest radiation doses were the pancreas, kidneys, and liver. The effective dose delivered by [(11)C]TASP457 was 6.9 μSv/MBq.

CONCLUSION

[(11)C]TASP457 is a useful novel PET ligand for the investigation of the density of histamine H3 receptors in human brain.

An open tool for input function estimation and quantification of dynamic PET FDG brain scans

PURPOSE

Positron emission tomography (PET) analysis of clinical studies is mostly restricted to qualitative evaluation. Quantitative analysis of PET studies is highly desirable to be able to compute an objective measurement of the process of interest in order to evaluate treatment response and/or compare patient data. But implementation of quantitative analysis generally requires the determination of the input function: the arterial blood or plasma activity which indicates how much tracer is available for uptake in the brain. The purpose of our work was to share with the community an open software tool that can assist in the estimation of this input function, and the derivation of a quantitative map from the dynamic PET study.

METHODS

Arterial blood sampling during the PET study is the gold standard method to get the input function, but is uncomfortable and risky for the patient so it is rarely used in routine studies. To overcome the lack of a direct input function, different alternatives have been devised and are available in the literature. These alternatives derive the input function from the PET image itself (image-derived input function) or from data gathered from previous similar studies (population-based input function). In this article, we present ongoing work that includes the development of a software tool that integrates several methods with novel strategies for the segmentation of blood pools and parameter estimation.

RESULTS

The tool is available as an extension to the 3D Slicer software. Tests on phantoms were conducted in order to validate the implemented methods. We evaluated the segmentation algorithms over a range of acquisition conditions and vasculature size. Input function estimation algorithms were evaluated against ground truth of the phantoms, as well as on their impact over the final quantification map. End-to-end use of the tool yields quantification maps with [Formula: see text] relative error in the estimated influx versus ground truth on phantoms.

CONCLUSIONS

The main contribution of this article is the development of an open-source, free to use tool that encapsulates several well-known methods for the estimation of the input function and the quantification of dynamic PET FDG studies. Some alternative strategies are also proposed and implemented in the tool for the segmentation of blood pools and parameter estimation. The tool was tested on phantoms with encouraging results that suggest that even bloodless estimators could provide a viable alternative to blood sampling for quantification using graphical analysis. The open tool is a promising opportunity for collaboration among investigators and further validation on real studies.

Impact of point spread function modelling and time of flight on FDG uptake measurements in lung lesions using alternative filtering strategies

BACKGROUND

The use of maximum standardised uptake value (SUVmax) is commonplace in oncology positron emission tomography (PET). Point spread function (PSF) modelling and time-of-flight (TOF) reconstructions have a significant impact on SUVmax, presenting a challenge for centres with defined protocols for lesion classification based on SUVmax thresholds. This has perhaps led to the slow adoption of these reconstructions. This work evaluated the impact of PSF and/or TOF reconstructions on SUVmax, SUVpeak and total lesion glycolysis (TLG) under two different schemes of post-filtering.

METHODS

Post-filters to match voxel variance or SUVmax were determined using a NEMA NU-2 phantom. Images from 68 consecutive lung cancer patients were reconstructed with the standard iterative algorithm along with TOF; PSF modelling - Siemens HD·PET (HD); and combined PSF modelling and TOF - Siemens ultraHD·PET (UHD) with the two post-filter sets. SUVmax, SUVpeak, TLG and signal-to-noise ratio of tumour relative to liver (SNR(T-L)) were measured in 74 lesions for each reconstruction. Relative differences in uptake measures were calculated, and the clinical impact of any changes was assessed using published guidelines and local practice.

RESULTS

When matching voxel variance, SUVmax increased substantially (mean increase +32% and +49% for HD and UHD, respectively), potentially impacting outcome in the majority of patients. Increases in SUVpeak were less notable (mean increase +17% and +23% for HD and UHD, respectively). Increases with TOF alone were far less for both measures. Mean changes to TLG were <10% for all algorithms for either set of post-filters. SNR(T-L) were greater than ordered subset expectation maximisation (OSEM) in all reconstructions using both post-filtering sets.

CONCLUSIONS

Matching image voxel variance with PSF and/or TOF reconstructions, particularly with PSF modelling and in small lesions, resulted in considerable increases in SUVmax, inhibiting the use of defined protocols for lesion classification based on SUVmax. However, reduced partial volume effects may increase lesion detectability. Matching SUVmax in phantoms translated well to patient studies for PSF reconstruction but less well with TOF, where a small positive bias was observed in patient images. Matching SUVmax significantly reduced voxel variance and potential variability of uptake measures. Finally, TLG may be less sensitive to reconstruction methods compared with either SUVmax or SUVpeak.

Is the standard uptake value (SUV) appropriate for quantification in clinical PET imaging? - Variability induced by different SUV measurements and varying reconstruction methods

INTRODUCTION

PET quantification using the standard uptake value (SUV) is very prone to variations by technical factors of the scanner system and patient specific characteristics. Aim of the study was to investigate the reproducibility of SUV values between different measures and different reconstruction algorithms in a PET/CT scanner of the newest generation.

METHODS

The time-of-flight PET datasets of 27 consecutive oncological patients were reconstructed with OSEM3D in two different matrix sizes (200 × 200 and 400 × 400) as well as in a matrix size of 400 × 400 and additional point-spread-reconstruction. The standardized uptake values SUVmax, SUVmean and SUVpeak in 60 lesions were compared concerning their variability in the three reconstructions.

RESULTS

The addition of point-spread-reconstruction causes a significant increase of SUV values in comparison to OSEM 3D. SUVpeak showed the highest reproducibility between the different reconstruction algorithms. The variability of SUVmax and SUVmean increases in small lesions <5 ml, while SUVpeak remains more stable.

CONCLUSION

SUVmax, SUVmean and SUVpeak can be used for PET quantification in principle. However, quantification of small lesions is difficult. SUVpeak is the most robust method when using varying reconstruction methods, especially in small lesions.

Comparison of MR-less PiB SUVR quantification methods

(11)C-Pittsburgh compound B (PiB) is a positron emission tomography (PET) tracer designed to bind to amyloid-β (Aβ) plaques, one of the hallmarks of Alzheimer's disease (AD). The potential of PiB as an early marker of AD led to the increasing use of PiB in clinical research studies and development of several F-18-labeled Aβ radiotracers. Automatic quantification of PiB images requires an accurate parcellation of the brain's gray matter (GM). Typically, this relies on a coregistered magnetic resonance imaging (MRI) to extract the cerebellar GM, compute the standardized uptake value ratio (SUVR), and provide parcellation and segmentation for quantification of regional and global SUVR. However, not all subjects can undergo MRI, in which case, an MR-less method is desirable. In this study, we assess 3 PET-only quantification methods: a mean atlas, an adaptive atlas, and a multi-atlas approaches on a database of 237 subjects having been imaged with both PiB PET and MRI. The PET-only methods were compared against MR-based SUVR quantification and evaluated in terms of correlation, average error, and performance in classifying subjects with low and high Aβ deposition. The mean atlas method suffered from a significant bias between the estimated neocortical SUVR and the PiB status, resulting in an overall error of 5.6% (R(2) = 0.98), compared with the adaptive and multi-atlas approaches that had errors of 3.06% and 2.74%, respectively (R(2) = 0.98), and no significant bias. In classifying PiB-negative from PiB-positive subjects, the mean atlas had 10 misclassified subjects compared with 0 for the adaptive and 1 for the multi-atlas approach. Overall, the adaptive and the multi-atlas approaches performed similarly well against the MR-based quantification and would be a suitable replacements for PiB quantification when no MRI is available.

Impact of flexible body surface coil and patient table on PET quantification and image quality in integrated PET/MR

AIM

The surface coils of the Biograph mMR integrated PET/MR system were optimised for PET, but are otherwise unaccounted for. The patient table is still more massive than those of PET/CT devices. The goal was to assess those hardware effects on quantification, count statistics, image quality and scan time both with phantoms and in patients and to investigate their clinical relevance.

PATIENTS, MATERIAL, METHODS

PET phantom data were acquired with and without the patient table. Image noise was expressed as relative standard deviation and compared to a state-of-the-art PET/CT scanner. Protocols of the phantom/patient study regarding the surface coils were similar. Thoraces/abdomens of 11 patients were scanned with and without a coil (1 BP, 4 min). Mean uptake and standard deviation in a cubical VOI were derived and expressed as SUV.

RESULTS

The patient table reduced the number of true coincidences (trues) by 19% (PET/MR) and by 11% (PET/CT). The scan duration for the mMR had to be increased by approximately 30% to achieve a noise level comparable to that of the PET/CT. Decreased SUVs with coil observed in the phantom were confirmed by the patient study. By removing the coil, the mean liver SUV increased by (6 ± 2)%. With (+3 ± 14)%, the average change was similar in lesions, but exceeded 20% in almost one fifth of them. The number of trues grew by (6 ± 1)% for the patients and by 7% for the phantom.

CONCLUSION

Due to the additional attenuation caused by MR hardware, PET scan durations would have to be increased compared to current PET/CTs to provide similar image noise levels. The effect of the coils is mostly in the order of statistical fluctuations. In tumour lesions, it is more pronounced and shows a larger variability. Therefore, coils should be included in the attenuation correction to ensure accurate quantification and thus comparability across PET/MR and PET/CT scanners and within patient populations.

PET quantification with a histogram derived total activity metric: superior quantitative consistency compared to total lesion glycolysis with absolute or relative SUV thresholds in phantoms and lung cancer patients

INTRODUCTION

The increasing use of molecular imaging probes as biomarkers in oncology emphasizes the need for robust and stable methods for quantifying tracer uptake in PET imaging. The primary motivation for this research was to find an accurate method to quantify the total tumor uptake. Therefore we developed a histogram-based method to calculate the background subtracted lesion (BSL) activity and validated BSL by comparing the quantitative consistency with the total lesion glycolysis (TLG) in phantom and patient studies.

METHODS

A thorax phantom and a PET-ACR quality assurance phantom were scanned with increasing FDG concentrations. Volumes of interest (VOIs) were placed over each chamber. TLG was calculated with a fixed threshold at SUV 2.5 (TLG2.5) and a relative threshold at 42% of SUVmax (TLG42%). The histogram for each VOI was built and BSL was calculated. Comparison with the total injected FDG activity (TIA) was performed using concordance correlation coefficients (CCC) and the slope (a). Fifty consecutive patients with FDG-avid lung tumors were selected under an IRB waiver. TLG42%, TLG2.5 and BSL were compared to the reference standard calculating CCC and the slope.

RESULTS

In both phantoms, the CCC for lesions with a TIA ≤50ml*SUV between TIA and BSL was higher and the slope closer to 1 (CCC=0.933, a=1.189), than for TLG42% (CCC=0.350, a=0.731) or TLG2.5 (CCC=0.761, a=0.727). In 50 lung lesions BSL had a slope closer to 1 compared to the reference activity than TLG42% (a=1.084 vs 0.618 - for high activity lesions) and also closer to 1 than TLG2.5 (a=1.117 vs 0.548 - for low activity lesions).

CONCLUSION

The histogram based BSL correlated better with TIA in both phantom studies than TLG2.5 or TLG42%. Also in lung tumors, the BSL activity is overall more accurate in quantifying the lesion activity compared to the two most commonly applied TLG quantification methods.