Adjusting the Low Energy Threshold for Large Bodies in PET

The performance of a PET scanner on three different phantom sizes was studied as a function of low energy threshold (LET). Phantom cross sections ranged from 20 cm diameter circular to 28 cm x 43 cm oval and LET\u27\u27s ranged from 350 keV to 475 keV, in 25 keV increments. System sensitivity, scatter fraction, and NEC were measured over a wide range of radioactivity levels. Increasing the low energy threshold lowered both sensitivity and scatter fraction. The statistical quality of the raw data was maximized for the 425 keV setting for all three phantoms. System stability and uniformity of response was also studied for 375 keV to 450 keV thresholds, and indicated acceptable performance for this system through 425 keV

Investigating the Optimum Lower Energy Threshold of a New Research PET/CT Scanner

An investigation of the optimum 3D lower energy threshold (LET) setting of the Discovery-RX, a new LYSO based GE research PET/CT scanner is conducted. Sensitivity and noise equivalent count rate (NECR) performance of the scanner in 3D mode were evaluated at multiple LET settings: 400, 425, 450, 460, 470 and 480 KeV. The performance evaluations were conducted according to the NEMA NU2-2001 standard. In addition, the NECR was also evaluated for the same LET settings using the Data Spectrum whole body phantom in order to more accurately simulate a true clinical setting. For the sensitivity measurements, the line source was filled with 9.25 MBq of F-18. For the NECR measurements, the NEMA and the Data Spectrum phantoms were fitted with a line source having an initial activity of 1400 MBq of F-18. As expected, the sensitivity decreases with increasing LET. The sensitivity at 400 and 450 keV was 13.2% higher and 18.9% lower than the sensitivity at the scanners default LET of 425 keV. Also as expected, the scatter fraction (SF) decreased with increasing LET for both NECR phantoms. The NECR curve corresponding to the 450 keV had the highest values over the clinical range of activity concentration usually used. Initial performance evaluation suggests that a LET of 450 keV is the best setting for the phantoms tested. Further clinical tests are needed to validate this observation

Image Quality vs. NEC in 2D and 3D PET

To investigate the relationship between NEC and image quality to 2D and 3D PET, while simultaneously optimizing 3D low energy threshold (LET), we have performed a series of phantom measurements. The phantom consisted of 46 1 cm fillable hollow spheres on a random grid inside a water-filled oval cylinder, 21 cm tall, 36 cm wide, and 40 cm long. The phantom was imaged on a Discovery ST PET/CT system (GE Healthcare, Milwaukee, WI) in a series of 3 min scans as it decayed from an activity of 7.2 mCi. The scans included LET settings of 375,400, and 425 keV in 3D, and 375 keV in 2D. Image signal-to-noise (SNR) was calculated and compared wash NEC. While both NEC and image quality in 3D improved for LETs above the default of 375 keV, we found that there were significant differences between NEC and image quality for 2D and 3D. Most importantly, 3D image-quality was strongly dependent on the reconstruction algorithm and its associated parameters. In conclusion, a direct measure of image quality as necessary for comparing 2D vs. 3D performance

Optimizing Sequential Dual Tracer P.E.T. Studies using a Combined 2D/3D Imaging Protocol

We have investigated a combined 2D/3D protocol for minimizing contamination in dual tracer P.E.T. studies in which the tracers are administered on a timescale that is short compared to the half-lives. We have performed a series of phantom studies on an Advance and a Discovery ST (GE Healthcare Technologies), using a torso phantom with cardiac insert (Data Spectrum Corporation) to simulate a combined FDG and NH3 scan protocol for a patient with ischemia. The phantom was imaged in a series of alternating 2D/3D acquisitions as it decayed over 6 half-lives. By comparing 2D and 3D images, we have verified that 3D images are of comparable accuracy to 2D images, even with realistic out-of-field activity challenging the 3D scans. Based on scan and image statistical quality, we have recommended optimal doses for maximizing the image quality of both scans

Performance of a BGO PET/CT with Higher Resolution PET Detectors

A new PET detector block has been designed to replace the standard detector of the Discovery ST PET/CT system. The new detector block is the same size as the original, but consists of an 8/spl times/6 (tangential× axial) matrix of crystals rather than the original 6/spl times/6. The new crystal dimensions are 4.7× 6.3× 30 mm/sup 3/ (tangential× axial× radial). Full PET/CT systems have been built with these detectors (Discovery STE). Most other aspects of the system are identical to the standard Discovery ST, with differences including the low energy threshold for 3D imaging (now 425 keV) and front-end electronics. Initial performance evaluation has been done, including NEMA NU2-2001 tests and imaging of the 3D Hoffman brain phantom and a neck phantom with small lesions. The system sensitivity was 1.90 counts/s/kBq in 2D, and 9.35 counts/s/kBq in 3D. Scatter fractions measured for 2D and 3D, respectively, were 18.6% and 34.5%. In 2D, the peak NEC of 89.9 kcps occurred at 47.0 kBq/cc. In 3D, the peak NEC of 74.3 kcps occurred at 8.5 kBq/cc. Spatial resolution (all expressed in mm FWHM) measured in 2D for 1 cm off-axis source 5.06 transaxial, 5.14 axial and for 10 cm source 5.45 radial, 5.86 tangential, and 6.23 axial. In 3D for 1 cm off-axis source 5.13 transaxial, 5.74 axial, and for 10 cm source 5.92 radial, 5.54 tangential, and 6.16 axial. Images of the brain and neck phantom demonstrate some improvement, compared to measurements on a standard Discovery ST

Characterization of 3D PET systems for accurate quantification of myocardial blood flow

Three-dimensional (3D) mode imaging is the current standard for positron emission tomography-computed tomography (PET-CT) systems. Dynamic imaging for quantification of myocardial blood flow (MBF) with short-lived tracers, such as Rb-82- chloride (Rb-82), requires accuracy to be maintained over a wide range of isotope activities and scanner count-rates. We propose new performance standard measurements to characterize the dynamic range of PET systems for accurate quantitative imaging. Methods: 1100-3000 MBq of Rb-82 or N-13-ammonia was injected into the heart wall insert of an anthropomorphic torso phantom. A decaying isotope scan was performed over 5 half-lives on 9 different 3D PET-CT systems and 1 3D/twodimensional (2D) PET-only system. Dynamic images (28x15s) were reconstructed using iterative algorithms with all corrections enabled. Dynamic range was defined as the maximum activity in the myocardial wall with <10% bias, from which corresponding dead-time, count-rates and/or injected activity limits were established for each scanner. Scatter correction residual bias was estimated as the maximum cavity blood-tomyocardium activity ratio. Image quality was assessed via the coefficient of variation measuring non-uniformity of the left ventricle (LV) myocardium activity distribution. Results: Maximum recommended injected activity/body-weight, peak dead-time correction factor, count-rates and residual scatter bias for accurate cardiac MBF imaging were: 3-14 MBq/kg, 1.5-4.0, 22-64 Mcps singles and 4-14 Mcps prompt coincidence count-rates, and 2-10% on the investigated scanners. Non-uniformity of the myocardial activity distribution varied from 3-16%. Conclusion: Accurate dynamic imaging is possible on the 10 3D-PET systems if the maximum injected MBq/kg values are respected to limit peak dead-time losses during the bolus first-pass transit

Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

Abstract: The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy

A comparative analysis of whole genome sequencing of esophageal adenocarcinoma pre- and post-chemotherapy

The scientific community has avoided using tissue samples from patients that have been exposed to systemic chemotherapy to infer the genomic landscape of a given cancer. Esophageal adenocarcinoma is a heterogeneous, chemoresistant tumor for which the availability and size of pretreatment endoscopic samples are limiting. This study compares whole-genome sequencing data obtained from chemo-naive and chemo-treated samples. The quality of whole-genomic sequencing data is comparable across all samples regardless of chemotherapy status. Inclusion of samples collected post-chemotherapy increased the proportion of late-stage tumors. When comparing matched pre- and post-chemotherapy samples from 10 cases, the mutational signatures, copy number, and SNV mutational profiles reflect the expected heterogeneity in this disease. Analysis of SNVs in relation to allele-specific copy-number changes pinpoints the common ancestor to a point prior to chemotherapy. For cases in which pre- and post-chemotherapy samples do show substantial differences, the timing of the divergence is near-synchronous with endoreduplication. Comparison across a large prospective cohort (62 treatment-naive, 58 chemotherapy-treated samples) reveals no significant differences in the overall mutation rate, mutation signatures, specific recurrent point mutations, or copy-number events in respect to chemotherapy status. In conclusion, whole-genome sequencing of samples obtained following neoadjuvant chemotherapy is representative of the genomic landscape of esophageal adenocarcinoma. Excluding these samples reduces the material available for cataloging and introduces a bias toward the earlier stages of cancer.This study was partly funded by a project grant from Cancer Research UK. R.C.F. is funded by an NIHR Professorship and receives core funding from the Medical Research Council and infrastructure support from the Biomedical Research Centre and the Experimental Cancer Medicine Centre. We acknowledge the support of The University of Cambridge, Cancer Research UK (C14303/A17197) and Hutchison Whampoa Limited

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts