An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor burden determinations. We developed and evaluated an automated deep learning (DL)-based framework that segments and classifies uptake on PSMA PET/CT. We identified 193 [18F] DCFPyL PET/CT scans of patients with biochemically recurrent prostate cancer from two institutions, including 137 [18F] DCFPyL PET/CT scans for training and internally testing, and 56 scans from another institution for external testing. Two radiologists segmented and labelled foci as suspicious or non-suspicious for malignancy. A DL-based segmentation was developed with two independent CNNs. An anatomical prior guidance was applied to make the DL framework focus on PSMA-avid lesions. Segmentation performance was evaluated by Dice, IoU, precision, and recall. Classification model was constructed with multi-modal decision fusion framework evaluated by accuracy, AUC, F1 score, precision, and recall. Automatic segmentation of suspicious lesions was improved under prior guidance, with mean Dice, IoU, precision, and recall of 0.700, 0.566, 0.809, and 0.660 on the internal test set and 0.680, 0.548, 0.749, and 0.740 on the external test set. Our multi-modal decision fusion framework outperformed single-modal and multi-modal CNNs with accuracy, AUC, F1 score, precision, and recall of 0.764, 0.863, 0.844, 0.841, and 0.847 in distinguishing suspicious and non-suspicious foci on the internal test set and 0.796, 0.851, 0.865, 0.814, and 0.923 on the external test set. DL-based lesion segmentation on PSMA PET is facilitated through our anatomical prior guidance strategy. Our classification framework differentiates suspicious foci from those not suspicious for cancer with good accuracy.

Deep Semisupervised Transfer Learning for Fully Automated Whole-Body Tumor Quantification and Prognosis of Cancer on PET/CT.

Automatic detection and characterization of cancer are important clinical needs to optimize early treatment. We developed a deep, semisupervised transfer learning approach for fully automated, whole-body tumor segmentation and prognosis on PET/CT. Methods: This retrospective study consisted of 611 18F-FDG PET/CT scans of patients with lung cancer, melanoma, lymphoma, head and neck cancer, and breast cancer and 408 prostate-specific membrane antigen (PSMA) PET/CT scans of patients with prostate cancer. The approach had a nnU-net backbone and learned the segmentation task on 18F-FDG and PSMA PET/CT images using limited annotations and radiomics analysis. True-positive rate and Dice similarity coefficient were assessed to evaluate segmentation performance. Prognostic models were developed using imaging measures extracted from predicted segmentations to perform risk stratification of prostate cancer based on follow-up prostate-specific antigen levels, survival estimation of head and neck cancer by the Kaplan-Meier method and Cox regression analysis, and pathologic complete response prediction of breast cancer after neoadjuvant chemotherapy. Overall accuracy and area under the receiver-operating-characteristic (AUC) curve were assessed. Results: Our approach yielded median true-positive rates of 0.75, 0.85, 0.87, and 0.75 and median Dice similarity coefficients of 0.81, 0.76, 0.83, and 0.73 for patients with lung cancer, melanoma, lymphoma, and prostate cancer, respectively, on the tumor segmentation task. The risk model for prostate cancer yielded an overall accuracy of 0.83 and an AUC of 0.86. Patients classified as low- to intermediate- and high-risk had mean follow-up prostate-specific antigen levels of 18.61 and 727.46 ng/mL, respectively (P < 0.05). The risk score for head and neck cancer was significantly associated with overall survival by univariable and multivariable Cox regression analyses (P < 0.05). Predictive models for breast cancer predicted pathologic complete response using only pretherapy imaging measures and both pre- and posttherapy measures with accuracies of 0.72 and 0.84 and AUCs of 0.72 and 0.76, respectively. Conclusion: The proposed approach demonstrated accurate tumor segmentation and prognosis in patients across 6 cancer types on 18F-FDG and PSMA PET/CT scans.

Correlation of SUV on Early Interim PET with Recurrence-Free Survival and Overall Survival in Primary Operable HER2-Positive Breast Cancer (the TBCRC026 Trial).

Predictive biomarkers of response to human epidermal growth factor receptor 2 (HER2)-directed therapy are essential to inform treatment decisions. The TBCRC026 trial reported that early declines in tumor SUVs corrected for lean body mass (SULmax) on 18F-FDG PET/CT predicted a pathologic complete response (pCR) to HER2 therapy with neoadjuvant trastuzumab and pertuzumab (HP) without chemotherapy in estrogen receptor (ER)-negative, HER2-positive breast cancer. We hypothesized that 18F-FDG PET/CT SULmax parameters would predict recurrence-free survival (RFS) and overall survival (OS). Methods: Patients with stage II/III ER-negative, HER2-positive breast cancer received neoadjuvant HP (n = 88). pCR after HP alone was 22% (18/83), additional nonstudy neoadjuvant therapy was administered in 28% (25/88), and the majority received adjuvant therapy per physician discretion. 18F-FDG PET/CT was performed at baseline and at cycle 1, day 15 (C1D15). RFS and OS were summarized using the Kaplan-Meier method and compared between subgroups using logrank tests. Associations between 18F-FDG PET/CT (≥40% decline in SULmax between baseline and C1D15, or C1D15 SULmax ≤ 3) and pCR were evaluated using Cox regressions, where likelihood ratio CIs were reported because of the small numbers of events. Results: Median follow-up was 53.7 mo (83/88 evaluable), with 6 deaths and 14 RFS events. Estimated RFS and OS at 3 y was 84% (95% CI, 76%-92%) and 92% (95% CI, 87%-98%), respectively. A C1D15 SULmax of 3 or less was associated with improved RFS (hazard ratio [HR], 0.36; 95% CI, 0.11-1.05; P = 0.06) and OS (HR, 0.14; 95% CI, 0.01-0.85; P = 0.03), the latter statistically significant. The association of an SULmax decline of at least 40% (achieved in 59%) with RFS and OS did not reach statistical significance. pCR was associated with improved RFS (HR, 0.25; 95% CI, 0.01-1.24; P = 0.10) but did not reach statistical significance. Conclusion: For the first time, we report a potential association between a C1D15 SULmax of 3 or less on 18F-FDG PET/CT and RFS and OS outcomes in patients with ER-negative, HER2-positive breast cancer receiving neoadjuvant HP alone. If confirmed in future studies, this imaging-based biomarker may facilitate early individualization of therapy.

Deep learning and radiomics framework for PSMA-RADS classification of prostate cancer on PSMA PET.

BACKGROUND: Accurate classification of sites of interest on prostate-specific membrane antigen (PSMA) positron emission tomography (PET) images is an important diagnostic requirement for the differentiation of prostate cancer (PCa) from foci of physiologic uptake. We developed a deep learning and radiomics framework to perform lesion-level and patient-level classification on PSMA PET images of patients with PCa. METHODS: This was an IRB-approved, HIPAA-compliant, retrospective study. Lesions on [18F]DCFPyL PET/CT scans were assigned to PSMA reporting and data system (PSMA-RADS) categories and randomly partitioned into training, validation, and test sets. The framework extracted image features, radiomic features, and tissue type information from a cropped PET image slice containing a lesion and performed PSMA-RADS and PCa classification. Performance was evaluated by assessing the area under the receiver operating characteristic curve (AUROC). A t-distributed stochastic neighbor embedding (t-SNE) analysis was performed. Confidence and probability scores were measured. Statistical significance was determined using a two-tailed t test. RESULTS: PSMA PET scans from 267 men with PCa had 3794 lesions assigned to PSMA-RADS categories. The framework yielded AUROC values of 0.87 and 0.90 for lesion-level and patient-level PSMA-RADS classification, respectively, on the test set. The framework yielded AUROC values of 0.92 and 0.85 for lesion-level and patient-level PCa classification, respectively, on the test set. A t-SNE analysis revealed learned relationships between the PSMA-RADS categories and disease findings. Mean confidence scores reflected the expected accuracy and were significantly higher for correct predictions than for incorrect predictions (P < 0.05). Measured probability scores reflected the likelihood of PCa consistent with the PSMA-RADS framework. CONCLUSION: The framework provided lesion-level and patient-level PSMA-RADS and PCa classification on PSMA PET images. The framework was interpretable and provided confidence and probability scores that may assist physicians in making more informed clinical decisions.

Automated lesion detection of breast cancer in [18F] FDG PET/CT using a novel AI-Based workflow.

Applications based on artificial intelligence (AI) and deep learning (DL) are rapidly being developed to assist in the detection and characterization of lesions on medical images. In this study, we developed and examined an image-processing workflow that incorporates both traditional image processing with AI technology and utilizes a standards-based approach for disease identification and quantitation to segment and classify tissue within a whole-body [18F]FDG PET/CT study. Methods: One hundred thirty baseline PET/CT studies from two multi-institutional preoperative clinical trials in early-stage breast cancer were semi-automatically segmented using techniques based on PERCIST v1.0 thresholds and the individual segmentations classified as to tissue type by an experienced nuclear medicine physician. These classifications were then used to train a convolutional neural network (CNN) to automatically accomplish the same tasks. Results: Our CNN-based workflow demonstrated Sensitivity at detecting disease (either primary lesion or lymphadenopathy) of 0.96 (95% CI [0.9, 1.0], 99% CI [0.87,1.00]), Specificity of 1.00 (95% CI [1.0,1.0], 99% CI [1.0,1.0]), DICE score of 0.94 (95% CI [0.89, 0.99], 99% CI [0.86, 1.00]), and Jaccard score of 0.89 (95% CI [0.80, 0.98], 99% CI [0.74, 1.00]). Conclusion: This pilot work has demonstrated the ability of AI-based workflow using DL-CNNs to specifically identify breast cancer tissue as determined by [18F]FDG avidity in a PET/CT study. The high sensitivity and specificity of the network supports the idea that AI can be trained to recognize specific tissue signatures, both normal and disease, in molecular imaging studies using radiopharmaceuticals. Future work will explore the applicability of these techniques to other disease types and alternative radiotracers, as well as explore the accuracy of fully automated and quantitative detection and response assessment.

Photorealistic three-dimensional visualization of fusion datasets: cinematic rendering of PET/CT.

PURPOSE: Cinematic rendering (CR) is a method of photorealistic 3D visualization of volumetric imaging data. We applied this technique to fusion PET/CT data. METHODS: Two recent PET/CT cases were selected, one each of prostate-specific membrane antigen (PSMA)-targeted 18F-DCFPyL, and somatostatin-receptor-targeted 68 Ga-DOTATATE. Targeted radiotracers were selected in order to provide high-contrast images for this proof-of-principle study. Cinematic rendering was performed with an enhanced algorithm that incorporated internal lighting within the PET-avid organs and lesions to allow for a distinct visual signature. RESULTS: The use of internal lighting for PET data provided CR of fused PET/CT scans. The interpreting radiologist must make judicious use of presets and cut planes in order to ensure important findings are not missed. CONCLUSIONS: CR of PET/CT data provides a photorealistic means of visualizing complex fusion imaging datasets. Such visualizations may aid anatomic understanding for surgical or procedural applications, may improve teaching of trainees, and may allow improved communication with patients.

Prognostic value of baseline metabolic tumor volume in children and adolescents with intermediate-risk Hodgkin lymphoma treated with chemo-radiation therapy: FDG-PET parameter analysis in a subgroup from COG AHOD0031.

BACKGROUND: Positron emission tomography (PET)-based measures of baseline total-body tumor burden may improve risk stratification in intermediate-risk Hodgkin lymphoma (HL). MATERIALS AND METHODS: Evaluable patients were identified from a cohort treated homogeneously with the same combined modality regimen on the Children's Oncology Group AHOD0031 study. Eligible patients had high-quality baseline PET scans. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were each measured based on 15 thresholds for every patient. Univariate and multivariable Cox regression and Kaplan-Meier survival analyses assessed for an association of MTV and TLG with event-free survival (EFS). RESULTS: From the AHOD0031 cohort (n = 1712), 86 patients were identified who (i) were treated with four cycles of doxorubicin, bleomycin, vincristine, etoposide, prednisone, cyclophosphamide (ABVE-PC) chemotherapy followed by involved field radiotherapy, and (ii) had a baseline PET scan that was amenable to quantitative analysis. Based on univariate Cox regression analysis, six PET-derived parameters were significantly associated with EFS. For each of these, Kaplan-Meier analyses and the log-rank test were used to compare patients with highest tumor burden (i.e., highest 15%) to the remainder of the cohort. EFS was significantly associated with all six PET parameters (all p < .029). In a multivariable model controlling for important covariates including disease bulk and response to chemotherapy, MTV2BP was significantly associated with EFS (p = .012). CONCLUSION: Multiple baseline PET-derived volumetric parameters were associated with EFS. MTV2BP was highly associated with EFS when controlling for disease bulk and response to chemotherapy. Incorporation of baseline MTV into risk-based treatment algorithms may improve outcomes in intermediate-risk HL.

Updated Results of TBCRC026: Phase II Trial Correlating Standardized Uptake Value With Pathological Complete Response to Pertuzumab and Trastuzumab in Breast Cancer.

PURPOSE: Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake value corrected for lean body mass (SULmax) on 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) would predict pathologic complete response (pCR) to pertuzumab and trastuzumab (PT). PATIENTS AND METHODS: Patients with stage II or III, estrogen receptor-negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percent change in SULmax by C1D15 predicting pCR is ≤ 0.65, with a one-sided type I error rate of 10%. RESULTS: Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 22%. Receiver operator characteristic analysis of percent change in SULmax by C1D15 yielded an area under the curve of 0.72 (80% CI, 0.64 to 0.80; one-sided P = .12), which did not reject the null hypothesis. However, between patients who obtained pCR and who did not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 41.8%; P = .004) and SULmax reduction ≥ 40% was more prevalent (83% v 52%; P = .03; positive predictive value, 31%). Participants not obtaining a 40% reduction in SULmax by C1D15 were unlikely to obtain pCR (negative predictive value, 91%). CONCLUSION: Although the primary objective was not met, early changes in SULmax predict response to PT in estrogen receptor-negative and HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate tailoring of therapy in this setting.

Effect of Point-Spread Function Reconstruction for Indeterminate PSMA-RADS-3A Lesions on PSMA-Targeted PET Imaging of Men with Prostate Cancer.

PURPOSE: Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) is emerging as an important modality for imaging patients with prostate cancer (PCa). As with any imaging modality, indeterminate findings will arise. The PSMA reporting and data system (PSMA-RADS) version 1.0 codifies indeterminate soft tissue findings with the PSMA-RADS-3A moniker. We investigated the role of point-spread function (PSF) reconstructions on categorization of PSMA-RADS-3A lesions. METHODS: This was a post hoc analysis of an institutional review board approved prospective trial. Around 60 min after the administration of 333 MBq (9 mCi) of PSMA-targeted 18F-DCFPyL, patients underwent PET/computed tomography (CT) acquisitions from the mid-thighs to the skull vertex. The PET data were reconstructed with and without PSF. Scans were categorized according to PSMA-RADS version 1.0, and all PSMA-RADS-3A lesions on non-PSF images were re-evaluated to determine if any could be re-categorized as PSMA-RADS-4. The maximum standardized uptake values (SUVs) of the lesions, mean SUVs of blood pool, and the ratios of those values were determined. RESULTS: A total of 171 PSMA-RADS-3A lesions were identified in 30 patients for whom both PSF reconstructions and cross-sectional imaging follow-up were available. A total of 13/171 (7.6%) were re-categorized as PSMA-RADS-4 lesions with PSF reconstructions. A total of 112/171 (65.5%) were found on follow-up to be true positive for PCa, with all 13 of the re-categorized lesions being true positive on follow-up. The lesions that were re-categorized trended towards having higher SUVmax-lesion and SUVmax-lesion/SUVmean-blood-pool metrics, although these relationships were not statistically significant. CONCLUSIONS: The use of PSF reconstructions for 18F-DCFPyL PET can allow the appropriate re-categorization of a small number of indeterminate PSMA-RADS-3A soft tissue lesions as more definitive PSMA-RADS-4 lesions. The routine use of PSF reconstructions for PSMA-targeted PET may be of value at those sites that utilize this technology.

Quantitation of cancer treatment response by 2-[18F]FDG PET/CT: multi-center assessment of measurement variability using AUTO-PERCIST™.

BACKGROUND: The aim of this study was to assess the reader variability in quantitatively assessing pre- and post-treatment 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) scans in a defined set of images of cancer patients using the same semi-automated analytical software (Auto-PERCIST™), which identifies tumor peak standard uptake value corrected for lean body mass (SULpeak) to determine [18F]FDG PET quantitative parameters. METHODS: Paired pre- and post-treatment [18F]FDG PET/CT images from 30 oncologic patients and Auto-PERCIST™ semi-automated software were distributed to 13 readers across US and international sites. One reader was aware of the relevant medical history of the patients (readreference), whereas the 12 other readers were blinded to history but had access to the correlative images. Auto-PERCIST™ was set up to first automatically identify the liver and compute the threshold for tumor measurability (1.5 × liver mean) + (2 × liver standard deviation [SD]) and then detect all sites with SULpeak greater than the threshold. Next, the readers selected sites they believed to represent tumor lesions. The main performance metric assessed was the percent change in the SULpeak (%ΔSULpeak) of the hottest tumor identified on the baseline and follow-up images. RESULTS: The intra-class correlation coefficient (ICC) for the %ΔSULpeak of the hottest tumor was 0.87 (95%CI: [0.78, 0.92]) when all reads were included (n = 297). Including only the measurements that selected the same target tumor as the readreference (n = 224), the ICC for %ΔSULpeak was 1.00 (95%CI: [1.00, 1.00]). The Krippendorff alpha coefficient for response (complete or partial metabolic response, versus stable or progressive metabolic disease on PET Response Criteria in Solid Tumors 1.0) was 0.91 for all reads (n = 380) and 1.00 including for reads with the same target tumor selection (n = 270). CONCLUSION: Quantitative tumor [18F]FDG SULpeak changes measured across multiple global sites and readers utilizing Auto-PERCIST™ show very high correlation. Harmonization of methods to single software, Auto-PERCIST™, resulted in virtually identical extraction of quantitative tumor response data from [18F]FDG PET images when the readers select the same target tumor.

An exploratory study of metformin with or without rapamycin as maintenance therapy after induction chemotherapy in patients with metastatic pancreatic adenocarcinoma.

PURPOSE: Metformin combined with the mTOR inhibitor rapamycin showed potential synergistic anti-tumor activity in preclinical studies in pancreatic ductal adenocarcinoma (PDA). This phase 1b study (NCT02048384) was conducted to evaluate the feasibility and activity of metformin +/- rapamycin in the maintenance setting for unselected patients with metastatic PDA (mPDA) treated with chemotherapy. MATERIALS AND METHODS: Eligible patients with stable or responding mPDA after ≥ 6 months on chemotherapy were randomized 1:1 to metformin alone (Arm A) or with rapamycin (Arm B), stratified by prior treatment with FOLFIRINOX. Fluorodeoxyglucose (FDG) PET scans and peripheral blood mononuclear cells were obtained for exploratory analyses. RESULTS: 22 subjects (11 per arm) received treatment per protocol. Median PFS/OS were 3.5 and 13.2 months respectively, with 2 year OS rate of 37%; there were no differences between arms. No responses were observed by RECIST; however, decreases in FDG avidity and/or CA19-9 were observed in several long-term survivors. Treatment related adverse events of Grade ≥ 3 occurred in 0% vs 27% of patients in Arm A vs B and were asymptomatic hematologic or electrolyte abnormalities that were not clinically significant. Improved survival was associated with low baseline neutrophil: lymphocyte ratio, baseline lack of assessable disease by PET, and greater expansion of dendritic cells following treatment. CONCLUSIONS: Metformin +/- rapamycin maintenance for mPDA was well-tolerated and several patients achieved stable disease associated with exceptionally long survival. Further prospective studies are needed to clarify the role of these agents in the maintenance setting and to enhance patient selection for such approaches.

Imager-4D: New Software for Viewing Dynamic PET Scans and Extracting Radiomic Parameters from PET Data.

Extensive research is currently being conducted into dynamic positron emission tomography (PET) acquisitions (including dynamic whole-body imaging) as well as extraction of radiomic features from imaging modalities. We describe a new PET viewing software known as Imager-4D that provides a facile means of viewing and analyzing dynamic PET data and obtaining associated quantitative metrics including radiomic parameters. The Imager-4D was programmed in the Java language utilizing the FX extensions. It is executable on any system for which a Java w/FX compliant virtual machine is available. The software incorporates the ability to view and analyze dynamic data acquired with different types of dynamic protocols. For image display, the program maintains a built-in library of 62 different lookup tables with monochromatic and full-color distributions. The Imager-4D provides multiple display layouts and can display fused images. Multiple methods of volume-of-interest (VOI) selection are available. Dynamic analysis features, such as image summation and full Patlak analysis, are also available. The user interface includes window width and level, blending, and zoom functionality. VOI sizes are adjustable and data from VOIs can either be displayed numerically or graphically within the software or exported. An example case of a 50-year-old woman with metastatic colorectal cancer and thyroiditis is included and demonstrates the steps for a user to obtain standard PET parameters, dynamic data, and radiomic features using selected VOIs. The Imager-4D represents a novel PET viewer that allows the user to view dynamic PET data, to derive dynamic and radiomic parameters from that data, and to combine dynamic data with radiomics ("dynomics"). The Imager-4D is available as a free download. This software has the potential to speed the adoption of advanced analysis of dynamic PET data into routine clinical use.

Impact of aging on semiquantitative uptake parameters in normal rated clinical baseline [123I]Ioflupane single photon emission computed tomography/computed tomography.

OBJECTIVES: Studies investigating the age-related impact on dopamine transporter binding have previously omitted the use of attenuation correction by computed tomography (CT). We aimed to explore the impact of age and gender on dopamine transporter binding on [I]Ioflupane single photon emission CT (SPECT) imaging with simultaneously acquired CT. METHODS: Three hundred forty-two patients with clinically uncertain parkinsonian syndrome underwent [I]-Ioflupane SPECT/CT with CT-based attenuation correction. Two nuclear medicine physicians independently performed a visual evaluation of all scans and only visibly normal scans were included for further analysis. Moreover, the results of a fully automatic semiquantitative evaluation method were recorded. Thereafter, the obtained [I]Ioflupane binding ratio and the hemispheric asymmetry index were correlated with age and sex. RESULTS: Patient age range was 41-80 years with a balanced distribution over decades. Of 342 patients, 133 (38.9%, 66 females, median age, 64 years) were considered visually normal by both observers on the SPECT/CT images. A significant inverse correlation between age and [I]Ioflupane binding ratios in the striata (R = -0.38; P < 0.001), putamina (R = -0.39; P < 0.001) and caudate nuclei (R = -0.3; P < 0.001) was demonstrated. Linear regression of all included subjects demonstrated an average decrease of 0.19 per decade in the striatal binding ratio (6.6%). No significant sex differences were found in striatal binding ratios (P = 0.86). Moreover, no significant correlation was observed between age and striatal asymmetry index (r = 0.12; P = 0.16). CONCLUSION: In the present largest single-center analysis investigating [I]Ioflupane SPECT/CT in patients with clinical uncertain parkinsonian syndrome, a dopamine transporter loss of 6.6% per decade in visually normal scans was recorded.

The effect of ApoE ε4 on longitudinal brain region-specific glucose metabolism in patients with mild cognitive impairment: a FDG-PET study.

While the ApoE ε4 allele is a known risk factor for mild cognitive impairment (MCI) and Alzheimer's disease, brain region specific effects remain elusive. In this study, we investigate whether the ApoE ε4 allele exhibits brain region specific effects in longitudinal glucose uptake among patients with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed FDG PET images, MRIs, and demographic information were downloaded from the ADNI database. An iterative reblurred Van Cittertiteration method was used for partial volume correction (PVC) on all PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. Longitudinal changes in ROI FDG standardized uptake value ratio (SUVR) relative to cerebellum in 24 ApoE ε4 carriers and 24 age-matched ApoE ε4 non-carriers were measured for up to 84-months (median 72 months, SD = 11.2 months) and compared using a generalized linear mixed effects model controlling for gender, education, baseline age, and follow-up period. Additionally, voxelwise analysis was performed by implementing a paired t-test comparing matched baseline and 72 month FDG SUVR images in ApoE carriers and non-carriers separately. Results with PVC were compared with ones from non-PVC based analysis. After applying PVC, the superior fontal, parietal, lateral temporal, medial temporal, caudate, thalamus, and post-cingulate, and amygdala regions had greater longitudinal decreases in FDG uptake in ApoE ε4 carriers with MCI compared to non-carriers with MCI. Similar forebrain and limbic clusters were found through voxelwise analysis. Compared to the PVC based analysis, fewer significant ApoE-associated regions and clusters were found in the non-PVC based PET analysis. Our findings suggest that the ApoE ε4 genotype is associated with a longitudinal decline in glucose uptake in 8 forebrain and limbic brain regions in the context of MCI. In conclusion, this 84-months longitudinal FDG PET study demonstrates a novel ApoE ε4-associated brain-region specific glucose metabolism pattern in patients with MCI. Partial volume correction improved FDG PET quantification.

Association of PET-measured myocardial flow reserve with echocardiography-estimated pulmonary artery systolic pressure in patients with hypertrophic cardiomyopathy.

BACKGROUND: Pulmonary hypertension (PH) is a known complication of HCM and is a strong predictor of mortality. We aim to investigate the relationship between microvascular dysfunction measured by quantitative PET and PH in HCM patients. METHODS: Eighty-nine symptomatic HCM patients were included in the study. Each patient underwent two 20-min 13N-NH3 dynamic PET scans for rest and stress conditions, respectively. A 2-tissue irreversible compartmental model was used to fit the segments time activity curves for estimating segmental and global myocardial blood flow (MBF) and myocardial flow reserve (MFR). Echocardiographic derived PASP was utilized to estimate PH. RESULTS: Patients were categorized into two groups across PASP: PH (PASP > 36 mmHg) and no-PH (PASP ≤ 36 mmHg). patients with PH had larger left atrium, ratio of higher inflow early diastole (E) and atrial contraction (A) waves, E/A, and ratio of inflow and peak early diastolic waves, E/e', significantly reduced global stress MBF (1.85 ± 0.52 vs. 2.13 ± 0.56 ml/min/g; p = 0.024) and MFR (2.21 ± 0.57 vs. 2.62 ± 0.75; p = 0.005), while the MBFs at rest between the two groups were similar. There were significant negative correlations between global stress MBF/MFR and PASP (stress MBF: r = -0.23, p = 0.03; MFR: r = -0.32, p = 0.002); for regional MBF and MFR measurements, the highest linear correlation coefficients were observed in the septal wall (stress MBF: r = -0.27, p = 0.01; MFR: r = -0.31, p = 0.003). Global MFR was identified to be independent predictor for PH in multivariate regression analysis. CONCLUSION: Echocardiography-derived PASP is negatively correlated with global MFR measured by 13N-NH3 dynamic PET. Global MFR is suggested to be an index of PH in HCM patients.

The Correlation Between [68Ga]DOTATATE PET/CT and Cell Proliferation in Patients With GEP-NENs.

PURPOSE: Objectives of the study are to analyze the correlation between [68Ga]DOTATATE positron emission tomography (PET)/X-ray computed tomography (CT) measurements and various biological characteristics of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs), and to determine optimal cutoff value of SUVmax (standard uptake value) to differentiate neuroendocrine tumors (NETs) and neuroendocrine cancers (NECs). PROCEDURES: Of the GEP-NEN cases (73 males, 53 females; age 18-77 years) with pathologically proven primary and/or metastatic lesions, 126 were studied. All of the short axes of lesions were larger than 0.5 cm in order to avoid the partial volume effect. Patients fasted for 6 h before the PET/CT scans. The dose of [68Ga]DOTATATE was 100-200 MBq and the acquisition began at 1 h after injection. The lesion with the highest SUVmax in each patient was analyzed. RESULTS: In the total sample, the sensitivity of [68Ga]DOTATATE was 69.05 %. The sensitivities were significantly different among G1, G2, and G3 groups (72.22 %, 91.53 %, and 40.82 %, respectively; p < 0.01). The SUVmax of the G3 group was lowest. We also found that the sensitivity and SUVmax were significantly higher (p < 0.05) in patients with pancreatic NENs (Pan-NENs) than in patients with gastrointestinal NENs (Gi-NENs) and unknown primary NENs (Up-NENs). A significant negative correlation between SUVmax and Ki-67 was found (r = - 0.429, p < 0.01). Using SUVmax to differentiate neuroendocrine tumors (NETs) and neuroendocrine cancers (NECs), the area under the ROC curve (AUC) was 0.771 and the cutoff value of SUVmax was 11.25 (sensitivity 79.2 %, specificity 65.3 %). However, Pan-NENs did not show any statistical significance results in correlation and ROC analysis. CONCLUSION: [68Ga]DOTATATE PET/CT results showed a negative correlation with GEP-NEN cell proliferation and were complementary to Ki-67. Pan-NENs were different from Gi-NENs and Up-NENs when compared to somatostatin receptor expression.

Novel Functional Renal PET Imaging With 18F-FDS in Human Subjects.

The novel PET probe 2-deoxy-2-F-fluoro-D-sorbitol (F-FDS) has demonstrated favorable renal kinetics in animals. We aimed to elucidate its imaging properties in 2 human volunteers. F-FDS was produced by a simple 1-step reduction from F-FDG. On dynamic renal PET, the cortex was delineated and activity gradually transited in the parenchyma, followed by radiotracer excretion. No adverse effects were reported. Given the higher spatiotemporal resolution of PET relative to conventional scintigraphy, F-FDS PET offers a more thorough evaluation of human renal kinetics. Due to its simple production from F-FDG, F-FDS is virtually available at any PET facility with radiochemistry infrastructure.

TBCRC026: Phase II Trial Correlating Standardized Uptake Value With Pathologic Complete Response to Pertuzumab and Trastuzumab in Breast Cancer.

PURPOSE: Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake values corrected for lean body mass (SULmax) on [18F]fluorodeoxyglucose positron emission tomography/computed tomography would predict pathologic complete response (pCR) to neoadjuvant pertuzumab and trastuzumab (PT). PATIENTS AND METHODS: Patients with stage II/III, estrogen receptor-negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. [18F]Fluorodeoxyglucose positron emission tomography/computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percentage of change in SULmax by C1D15 predicting pCR is less than or equal to 0.65, with a one-sided type I error rate of 10%. RESULTS: Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 34%. Receiver operating characteristic analysis yielded an area under the curve of 0.76 (90% CI, 0.67 to 0.85), which rejected the null hypothesis. Between patients who obtained pCR versus not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 33.5%; P < .001), an SULmax reduction greater than or equal to 40% was more prevalent (86% v 46%; P < .001; negative predictive value, 88%; positive predictive value, 49%), and a significant difference in median C1D15 SULmax (1.6 v 3.9; P < .001) and higher proportion of C1D15 SULmax less than or equal to 3 (93% v 38%; P < .001; negative predictive value, 94%; positive predictive value, 55%) were observed. CONCLUSION: Early changes in SULmax predict response to four cycles of PT in estrogen receptor-negative, HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate a more tailored approach to therapy in this setting.

Impact of Tumor Burden on Quantitative [68Ga] DOTATOC Biodistribution.

PURPOSE: As has been previously reported, the somatostatin receptor (SSTR) imaging agent [68Ga]-labeled 1,4,7,10-tetraazacyclododecane-N,N',N″,N‴-tetraacetic acid-d-Phe(1)-Tyr(3)-octreotate ([68Ga]DOTATATE) demonstrates lower uptake in normal organs in patients with a high neuroendocrine tumor (NET) burden. Given the higher SSTR affinity of [68Ga] DOTATATE, we aimed to quantitatively investigate the biodistribution of [68Ga]-labeled 1,4,7,10-tetraazacyclododecane-N,N',N″,N‴-tetraacetic acid-d-Phe(1)-Tyr(3)-octreotide ([68Ga]DOTATOC) to determine a potential correlation between uptake in normal organs and NET burden. PROCEDURES: Of the 44 included patients, 36/44 (82 %) patients demonstrated suspicious radiotracer uptake on [68Ga] DOTATOC positron emission tomography (PET)/X-ray computed tomography (CT). Volumes of interest (VOIs) were defined for tumor lesions and normal organs (spleen, liver, kidneys, adrenals). Mean body weight corrected standardized uptake value (SUVmean) for normal organs was assessed and was used to calculate the corresponding mean specific activity uptake (Upt: fraction of injected activity per kg of tissue). For the entire tumor burden, SUVmean, maximum standardized uptake value (SUVmax), and the total mass (TBM) was calculated and the decay corrected tumor fractional uptake (TBU) was assessed. A Spearman's rank correlation coefficient was used to determine the correlations between normal organ uptake and tumor burden. RESULTS: The median SUVmean was 18.7 for the spleen (kidneys, 9.2; adrenals, 6.8; liver, 5.6). For tumor burden, the median values were SUVmean 6.9, SUVmax 35.5, TBM 42.6 g, and TBU 1.2 %. With increasing volume of distribution, represented by lean body mass and body surface area (BSA), Upt decreased in kidneys, liver, and adrenal glands and SUVmean increased in the spleen. Correlation improved only for both kidneys and adrenals when the influence of the tumor uptake on the activity available for organ uptake was taken into account by the factor 1/(1-TBU). TBU was neither predictive for SUVmean nor for Upt in any of the organs. The distribution of organ Upt vs. BSA/(1-TBU) were not different for patients with minor TBU (<3 %) vs. higher TBU (>7 %), indicating that the correlations observed in the present study are explainable by the body size effect. High tumor mass and uptake mitigated against G1 NET. CONCLUSIONS: There is no significant impact on normal organ biodistribution with increasing tumor burden on [68Ga] DOTATOC PET/CT. Potential implications include increased normal organ dose with [177Lu-DOTA]0-D-Phe1-Tyr3-Octreotide and decreased absolute lesion detection with [68Ga] DOTATOC in high NET burden.

Visual and Semiquantitative Accuracy in Clinical Baseline 123I-Ioflupane SPECT/CT Imaging.

PURPOSE: We aimed to (a) elucidate the concordance of visual assessment of an initial I-ioflupane scan by a human interpreter with comparison to results using a fully automatic semiquantitative method and (b) to assess the accuracy compared to follow-up (f/u) diagnosis established by movement disorder specialists. METHODS: An initial I-ioflupane scan was performed in 382 patients with clinically uncertain Parkinsonian syndrome. An experienced reader performed a visual evaluation of all scans independently. The findings of the visual read were compared with semiquantitative evaluation. In addition, available f/u clinical diagnosis (serving as a reference standard) was compared with results of the human read and the software. RESULTS: When comparing the semiquantitative method with the visual assessment, discordance could be found in 25 (6.5%) of 382 of the cases for the experienced reader (ĸ = 0.868). The human observer indicated region of interest misalignment as the main reason for discordance. With neurology f/u serving as reference, the results of the reader revealed a slightly higher accuracy rate (87.7%, ĸ = 0.75) compared to semiquantification (86.2%, ĸ = 0.719, P < 0.001, respectively). No significant difference in the diagnostic performance of the visual read versus software-based assessment was found. CONCLUSIONS: In comparison with a fully automatic semiquantitative method in I-ioflupane interpretation, human assessment obtained an almost perfect agreement rate. However, compared to clinical established diagnosis serving as a reference, visual read seemed to be slightly more accurate as a solely software-based quantitative assessment.