Single-voxel delay map from long-axial field-of-view PET scans

ObjectiveWe present an algorithm to estimate the delay between a tissue time-activity curve and a blood input curve at a single-voxel level tested on whole-body data from a long-axial field-of-view scanner with tracers of different noise characteristics.MethodsWhole-body scans of 15 patients divided equally among three tracers, namely [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, which were used in development and testing of the algorithm. Delay times were estimated by fitting the cumulatively summed input function and tissue time-activity curve with special considerations for noise. To evaluate the performance of the algorithm, it was compared against two other algorithms also commonly applied in delay estimation: name cross-correlation and a one-tissue compartment model with incorporated delay. All algorithms were tested on both synthetic time-activity curves produced with the one-tissue compartment model with increasing levels of noise and delays between the tissue activity curve and the blood input curve. Whole-body delay maps were also calculated for each of the three tracers with data acquired on a long-axial field-of-view scanner with high time resolution.ResultsOur proposed model performs better for low signal-to-noise ratio time-activity curves compared to both cross-correlation and the one-tissue compartment models for non-[15O]H2O tracers. Testing on synthetically produced time-activity curves showed only a small and even residual delay, while the one-tissue compartment model with included delay showed varying residual delays.ConclusionThe algorithm is robust to noise and proves applicable on a range of tracers as tested on [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, and hence is a viable option offering the ability for delay correction across various organs and tracers in use with kinetic modeling

DeepDixon synthetic CT for [18F]FET PET/MRI attenuation correction of post-surgery glioma patients with metal implants

PurposeConventional magnetic resonance imaging (MRI) can for glioma assessment be supplemented by positron emission tomography (PET) imaging with radiolabeled amino acids such as O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET), which provides additional information on metabolic properties. In neuro-oncology, patients often undergo brain and skull altering treatment, which is known to challenge MRI-based attenuation correction (MR-AC) methods and thereby impact the simplified semi-quantitative measures such as tumor-to-brain ratio (TBR) used in clinical routine. The aim of the present study was to examine the applicability of our deep learning method, DeepDixon, for MR-AC in [18F]FET PET/MRI scans of a post-surgery glioma cohort with metal implants.MethodsThe MR-AC maps were assessed for all 194 included post-surgery glioma patients (318 studies). The subgroup of 147 patients (222 studies, 200 MBq [18F]FET PET/MRI) with tracer uptake above 1 ml were subsequently reconstructed with DeepDixon, vendor-default atlas-based method, and a low-dose computed tomography (CT) used as reference. The biological tumor volume (BTV) was delineated on each patient by isocontouring tracer uptake above a TBR threshold of 1.6. We evaluated the MR-AC methods using the recommended clinical metrics BTV and mean and maximum TBR on a patient-by-patient basis against the reference with CT-AC.ResultsNinety-seven percent of the studies (310/318) did not have any major artifacts using DeepDixon, which resulted in a Dice coefficient of 0.89/0.83 for tissue/bone, respectively, compared to 0.84/0.57 when using atlas. The average difference between DeepDixon and CT-AC was within 0.2% across all clinical metrics, and no statistically significant difference was found. When using DeepDixon, only 3 out of 222 studies (1%) exceeded our acceptance criteria compared to 72 of the 222 studies (32%) with the atlas method.ConclusionWe evaluated the performance of a state-of-the-art MR-AC method on the largest post-surgical glioma patient cohort to date. We found that DeepDixon could overcome most of the issues arising from irregular anatomy and metal artifacts present in the cohort resulting in clinical metrics within acceptable limits of the reference CT-AC in almost all cases. This is a significant improvement over the vendor-provided atlas method and of particular importance in response assessment

Deep Learning Based Attenuation Correction of PET/MRI in Pediatric Brain Tumor Patients: Evaluation in a Clinical Setting

Aim: Positron emission tomography (PET) imaging is a useful tool for assisting in correct differentiation of tumor progression from reactive changes. O-(2-18F-fluoroethyl)-L-tyrosine (FET)-PET in combination with MRI can add valuable information for clinical decision making. Acquiring FET-PET/MRI simultaneously allows for a one-stop-shop that limits the need for a second sedation or anesthesia as with PET and MRI in sequence. PET/MRI is challenged by lack of a direct measure of photon attenuation. Accepted solutions for attenuation correction (AC) might not be applicable to pediatrics. The aim of this study was to evaluate the use of the subject-specific MR-derived AC method RESOLUTE, modified to a pediatric cohort, against the performance of an MR-AC technique based on deep learning in a pediatric brain tumor cohort.Methods: The modifications to RESOLUTE and the implementation of a deep learning method were performed using 79 pediatric patient examinations. We analyzed the 36 of these with active brain tumor area above 1 mL. We measured background (B), tumor mean and maximal activity (TMEAN, TMAX), biological tumor volume (BTV), and calculated the clinical metrics TMEAN/B and TMAX/B.Results: Overall, we found both RESOLUTE and our DeepUTE methodologies to accurately reproduce the CT-AC clinical metrics. Regardless of age, both methods were able to obtain AC maps similar to the CT-AC, albeit with DeepUTE producing the most similar based on both quantitative metrics and visual inspection. In the patient-by-patient analysis DeepUTE was the only technique with all patients inside the predefined acceptable clinical limits. It also had a higher precision with relative %-difference to the reference CT-AC (TMAX/B mean: -0.1%, CI: [-0.8%, 0.5%], p = 0.54) compared to RESOLUTE (TMAX/B mean: 0.3%, CI: [-0.6%, 1.2%], p = 0.67) and DIXON-AC (TMAX/B mean: 5.9%, CI: [4.5%, 7.4%], p < 0.0001).Conclusion: Overall, we found DeepUTE to be the AC method that most robustly reproduced the CT-AC clinical metrics per se, closely followed by RESOLUTE modified to pediatric cohorts. The added accuracy due to better noise handling of DeepUTE, ease of use, as well as the improved runtime makes DeepUTE the method of choice for PET/MRI attenuation correction

Intravenous contrast-enhanced CT can be used for CT-based attenuation correction in clinical ¹¹¹In-octreotide SPECT/CT

BACKGROUND: CT-based attenuation correction (CT-AC) using contrast-enhancement CT impacts (111)In-SPECT image quality and quantification. In this study we assessed and evaluated the effect. METHODS: A phantom (5.15 L) was filled with an aqueous solution of In-111. Three SPECT/CT scans were performed: (A) no IV contrast, (B) with 100-mL IV contrast, and (C) with 200-mL IV contrast added. Scan protocol included a localization CT, a low-dose CT (LD), and a full-dose CT (FD). Phantom, LD and FD scan series were performed at 90, 120, and 140 kVp. Phantom data were evaluated looking at mean counts in a central volume. Ten patients referred for (111)In-octreotide scintigraphy were scanned according to our clinical (111)In-SPECT/CT protocol including a topogram, a LD (140 kVp), and a FD (120 kVp). The FD/contrast-enhanced CT was acquired in both arterial (FDAP) and venous phase (FDVP) following a mono-phasic IV injection of 125-mL Optiray (4.5 mL/s). For patient data, we report image quality, Krenning scores, and mean/max values for liver and tumor regions. RESULTS: Phantoms: in uncorrected emission data, mean counts (average ± SD) decreased with increasing IV concentration: (A) 119 ± 9, (B) 113 ± 8, and (C) 110 ± 9. For all attenuation correction (AC) scans, the mean values increased with increasing iodine concentration. Patients: there were no visible artifacts in single photon emission computed tomography (SPECT) following CT-AC with contrast-enhanced CT. The average score of image quality was 4.1 ± 0.3, 3.8 ± 0.4, and 4.2 ± 0.4 for LD, arterial phase, and venous phase, respectively. A total of 16 lesions were detected. The Krenning scores of 13/16 lesions were identical across all scan series. The max pixel values for the 16 lesions showed generally lower values for LD than for contrast-enhanced CT. CONCLUSIONS: In (111)In-SPECT/CT imaging of phantoms and patients, the use of IV CT contrast did neither degrade the SPECT image quality nor affect the clinical Krenning score. Reconstructed counts in healthy liver tissues were unaffected, and there was a generally lower count value in lesions following CT-AC based on the LD non-enhanced images. Overall, for clinical interpretation, no separate low-dose CT is required for CT-AC in (111)In-SPECT/CT