Faculty Bibliography

In the last two decades, it has been shown that anatomically-guided PET reconstruction can lead to improved bias-noise characteristics in brain PET imaging. However, despite promising results in simulations and first studies, anatomically-guided PET reconstructions are not yet available for use in routine clinical because of several reasons. In light of this, we investigate whether the improvements of anatomically-guided PET reconstruction methods can be achieved entirely in the image domain with a convolutional neural network (CNN). An entirely image-based CNN post-reconstruction approach has the advantage that no access to PET raw data is needed and, moreover, that the prediction times of trained CNNs are extremely fast on state of the art GPUs which will substantially facilitate the evaluation, fine-tuning and application of anatomically-guided PET reconstruction in real-world clinical settings. In this work, we demonstrate that anatomically-guided PET reconstruction using the asymmetric Bowsher prior can be well-approximated by a purely shift-invariant convolutional neural network in image space allowing the generation of anatomically-guided PET images in almost real-time. We show that by applying dedicated data augmentation techniques in the training phase, in which 16 [¹⁸F]FDG and 10 [¹⁸F]PE2I data sets were used, lead to a CNN that is robust against the used PET tracer, the noise level of the input PET images and the input MRI contrast. A detailed analysis of our CNN in 36 [¹⁸F]FDG, 18 [¹⁸F]PE2I, and 7 [¹⁸F]FET test data sets demonstrates that the image quality of our trained CNN is very close to the one of the target reconstructions in terms of regional mean recovery and regional structural similarity.

INTRODUCTION/BACKGROUND:Connectome analysis of the human brain's structural and functional architecture provides a unique opportunity to understand the organization of the brain's functional architecture. In previous studies, connectome fingerprinting using brain functional connectivity profiles as an individualized trait was able to predict an individual's neurocognitive performance from the Human Connectome Project (HCP) neurocognitive datasets. MATERIALS AND METHODS/METHODS:In the present study, we extend connectome fingerprinting from functional connectivity (FC) to structural connectivity (SC), identifying multiple relationships between behavioral traits and brain connectivity. Higher-order neurocognitive tasks were found to have a weaker association with structural connectivity than its functional connectivity counterparts. RESULTS:Neurocognitive tasks with a higher sensory footprint were, however, found to have a stronger association with structural connectivity than their functional connectivity counterparts. Language behavioral measurements had a particularly stronger correlation, especially between performance on the picture language test (Pic Vocab) and both FC (r = .28, p < .003) and SC (r = 0.27, p < .00077). CONCLUSIONS:At the neural level, we found that the pattern of structural brain connectivity related to high-level language performance is consistent with the language white matter regions identified in presurgical mapping. We illustrate how this approach can be used to generalize the connectome fingerprinting framework to structural connectivity and how this can help understand the connections between cognitive behavior and the white matter connectome of the brain.

OBJECTIVES/OBJECTIVE:The aim of this study was to develop a method for tracking respiratory motion throughout full MR or PET/MR studies that requires only minimal additional hardware and no modifications to the sequences. MATERIALS AND METHODS/METHODS:Patient motion that is caused by respiration affects the quality of the signal of the individual radiofrequency receive coil elements. This effect can be detected as a modulation of a monofrequent signal that is emitted by a small portable transmitter placed inside the bore (Pilot Tone). The frequency is selected such that it is located outside of the frequency band of the actual MR readout experiment but well within the bandwidth of the radiofrequency receiver, that is, the oversampling area. Temporal variations of the detected signal indicate motion. After extraction of the signal from the raw data, principal component analysis was used to identify respiratory motion. The approach and potential applications during MR and PET/MR examinations that rely on a continuous respiratory signal were validated with an anthropomorphic, PET/MR-compatible motion phantom as well as in a volunteer study. RESULTS:Respiratory motion detection and correction were presented for MR and PET data in phantom and volunteer studies. The Pilot Tone successfully recovered the ground-truth respiratory signal provided by the phantom. CONCLUSIONS:The presented method provides reliable respiratory motion tracking during arbitrary imaging sequences throughout a full PET/MR study. All results can directly be transferred to MR-only applications as well.

Introduction: Neuroaxonal loss and demyelination are the main substrate of disability in multiple sclerosis (MS). In this study, we assessed the potential of sodium and

Objectives: To demonstrate the development and use of an acute imaging protocol for the metabolic assessment of tissue viability during acute stroke.
Method(s): The DAWN and DEFUSE 3 trials (1,2) have demonstrated that there is much to gain from the use of physiologically based guidelines to extend the use of mechanical recanalization. Literature reports provide strong data supporting the use of brain tissue sodium concentration (TSC) as a biomarker for identifying physiologically non-viable tissue during evolving brain ischemia (3,4). Testing this hypothesis in vivo, in humans, have been previously hampered by acquisition times that were long for routine clinical use. Recent developments in MRI data acquisition and hardware make it possible to acquire the data to provide the aforementioned assessment in under 5 minutes at a level of signal-to-noise ratio (SNR) and spatial resolution compatible with physiologically driven MRI scans such as diffusion weighted imaging and perfusion imaging. This was achieved using an Ultra-Short-Echo Time sequence with optimal acquisition throughput (TPI, TE/TR 0.3/100 ms, p 0.2). Signal excitation/reception was performed using a patient-friendly double-tuned (¹H/²³Na) birdcage coil (Quality Electrodynamics Inc., Mayfield Heights, Ohio). The protocol was implemented on a MAGNETOM Skyra 3 Tesla scanner at NYU's Tisch hospital. The scanner is located adjacent (20 feet) to the neuro interventional suite where patients are recanalized. Subject's anesthesia was maintained (FabiusMRI, DraegerInc., Telford, PA) and physiological status continuously monitored using MRI-compatible equipment (Expression MR400, Phillips Healthcare, Andover, MA).
Result(s): After phantom validation and healthy volunteer studies to determine the quantitative performance of the data acquisition techniques the protocol was used on post-endovascular thrombectomy subjects (n 3), immediately upon procedure completion and under its own IRB approved protocol. During these studies, the use of the proposed methodology was found to be compatible with the clinical care of the subjects. Specifically, performing the required scans was not found to interfere with the subject's post-recanalization care. Tissue sodium concentration data were, likewise, found to meet the required levels of SNR to provide the quantitative assessment mentioned above. A representative data set from one of these sessions is shown in figure 1. This mechanically-recanalized patient had an area of non-salvaged tissue in the left parietal lobe that is clearly depicted on the ²³Na MRI scan. The TSC in this area was 76 mM at the time of the scan. (Figure presented)
Conclusion(s): This work demonstrates that state-of-the-art MRI methodology can be used to provide a clinically viable imaging protocol for evaluating the use of sodium MRI as a quantitative biomarker for identifying physiologically viable tissue during evolving brain ischemia

Diffusion tractography is routinely used to study white matter architecture and brain connectivity in vivo. A key step for successful tractography of neuronal tracts is the correct identification of tract directions in each voxel. Here we propose a fingerprinting-based methodology to identify these fiber directions in Orientation Distribution Functions, dubbed ODF-Fingerprinting (ODF-FP). In ODF-FP, fiber configurations are selected based on the similarity between measured ODFs and elements in a pre-computed library. In noisy ODFs, the library matching algorithm penalizes the more complex fiber configurations. ODF simulations and analysis of bootstrapped partial and whole-brain in vivo datasets show that the ODF-FP approach improves the detection of fiber pairs with small crossing angles while maintaining fiber direction precision, which leads to better tractography results. Rather than focusing on the ODF maxima, the ODF-FP approach uses the whole ODF shape to infer fiber directions to improve the detection of fiber bundles with small crossing angle. The resulting fiber directions aid tractography algorithms in accurately displaying neuronal tracts and calculating brain connectivity.

Introduction: Breast cancer is a worldwide health issue with about 1 million new cases every year. Dysregulated cellular proliferation, a common feature to all human cancers, is a key player of aberrant proliferative signaling and is therefore considered as a "hallmark of cancer. In breast cancer, a lot of attention focuses on particular members of the cell cycle machinery, the D-type cyclins and their partner cyclin-D kinases 4 and 6 (CDK4/6). CDKs are serine/threonine kinases key in regulating cell cycle progression by associating with cyclins. Several studies have identified alterations of cell cycle regulators in human breast cancer and provide a strong rationale for a therapeutic role for CDK4/6 inhibition in this tumor type. Amplification of the cyclin-D1 occurs in about 20% of human breast cancers, while overexpression of the protein is above 60%. The subtype for which CDK4/6 inhibition has the strongest rationale is estrogen receptor (ER)-positive disease. These subtypes almost always retain Rb function, thereby CDK4 and CDK6 targeting agents can block pRb phosphorylation (in low nanomolar concentration) and induce G1 arrest in sensitive cell lines. It is often controversial whether CDK4/6 inhibitors are capable to prolong overall survival. Moreover, it is urgent to find a way to select which patients are most likely to benefit from these drugs and to monitor, non-invasively, the progress of the disease and the overall treatment response. To this aim, we developed a PET imaging agent ([¹⁸F]-CDKi) as an in vivo PET reporter of CDK4/6 status with the final aim to improve efficacy of breast cancer therapy. To generate our fluorine-18 inhibitor, we introduced an F-18 prosthetic group (¹⁸F-fluorobenzoic acid, [¹⁸F-FBA]), on the terminal piperazine and transformed palbociclib (Inbrance, Pfizer) into a different PET active functional molecule. The first in vitro experiment aiming to analyze pharmacokinetics (PK) and in vitro activity revealed that [¹⁸F]-CDKican be a successful PET agent with nearly ideal imaging characteristics. Moreover, we demonstrated that [¹⁸F]-CDKi is stable in vitro and in vivo (>98% at 4h post injection) and maintained a potent targeting affinity to CDK4/6. Cellular uptake experiments performed in MCF-7 breast cancer cell line (ER-positive/HER2-negative) demonstrated specific uptake. Similar significant uptake values were also observed in biodistributed MCF-7 bearing mouse models. The strong activation of CDK4/6 in cancer cells in concert with its low activation in untransformed healthy cells makes [¹⁸F]-CDKi a nearly ideal imaging agent for the early detection of malignant growth of the breast. Moreover, we also hypothesize it could be an excellent PET imaging agent for metastatic breast cancer due to their high proliferative rate. CDKi represents the first of a new generation of PET imaging agents critical to study how cancer cells escape the cell cycle arrest and develop resistance to conventional treatment

Aim: Determine if MR-guided FDG-PET reconstruction improves diagnostic accuracy and epileptogenic lesion localization for patients with focal epilepsy. Introduction: Abnormalities detected on MRI or FDG PET alter clinical management and prognosis in patients with focal epilepsy considering surgery (1). Concordant MRI findings are not always present, whereas -80% of adult patients with chronic seizures have FDG PET abnormalities. State-of-art FDG PET, however, remains limited by partial volume effects (PVEs) that reduce sensitivity particularly for extra-temporal epilepsy (2). MR-guided (MRG) PET reconstruction reduces PVEs (3). We tested the hypothesis that MRG PET reconstruction increases correct localization of epileptogenic lesions across readers with different levels of clinical experience.
Method(s): After IRB approval, a neuroradiologist with 1000+ brain PET interpretations identified 26 epilepsy subjects that underwent simultaneous FDG PET-MRI (Siemens Biograph mMR, Siemens Healthcare, Erlangen, Germany) with final adjudicated diagnosis either as normal (N=10) or cortical dysplasia (N=16). PET emission images were reconstructed using conventional OSEM and MRG PET reconstructions (asymmetric Bowsher prior with 3D MPRAGE as anatomical prior image). Then, 3 blinded readers (with 12, 6 & 18 years of experience; respectively) evaluated cases containing either OSEM or MRG PET in the sagittal, axial and coronal planes for each case (MRI data was not provided). Readers determined if there were focal FDG abnormalities consistent with an epileptogenic zone, then assigned ordinal values to image quality (0-3; where 3 was "excellent") and diagnostic confidence (1-3; where 3 = "definite" abnormality or normal study).
Result(s): The figure below shows coronal OSEM and MRG PET reconstructions (A & B respectively) with co-registered MRI (C) - MRG PET better demonstrated the focal FDG abnormality associated with right frontal cortical dysplasia. All 3 readers rated MRG PET images higher in overall quality (2.6 +/- 0.7 vs 2.0 +/- 0.5, Mann-Whitney test, P<0.00001). Reconstruction method did not affect diagnostic confidence (2.6 +/- 0.7 vs 2.9 +/- 0.4, Mann-Whitney test, P=0.555). Readers 2 & 3 (with less experience reading brain FDG PET), improved their localization of the seizure focus using MRG PET images from 42.9 to 75%, and 50 to 75% correct respectively. Reader 1, with the most experience, demonstrated no change in correct localization (85.7 vs 83.3%), but reported more confidence in the diagnosis (P=0.033). Global percentage correct for all 3 raters increased from 59.5% to 77.8% (chi-squared test, P=0.086). MRG PET images increased interpretation sensitivity from 69% to 75%, specificity from 70% to 83% and accuracy from 70% to 78%, but these changes did not reach statistical significance.
Conclusion(s): These initial results demonstrate that MRG PET reconstruction of FDG data can increase correct seizure localization for PET readers with less experience. Study limitations include that clinical history, anatomical correlation and non-attenuation corrected FDG PET images were not available to blinded readers. Future work will increase the number of subjects evaluated by the 3 readers to increase statistical power

PURPOSE/OBJECTIVE:To develop a flexible method for tracking respiratory and cardiac motions throughout MR and PET-MR body examinations that requires no additional hardware and minimal sequence modification. METHODS:The incorporation of a contrast-neutral rosette navigator module following the RF excitation allows for robust cardiorespiratory motion tracking with minimal impact on the host sequence. Spatial encoding gradients are applied to the FID signal and the desired motion signals are extracted with a blind source separation technique. This approach is validated with an anthropomorphic, PET-MR-compatible motion phantom as well as in 13 human subjects. RESULTS:Both respiratory and cardiac motions were reliably extracted from the proposed rosette navigator in phantom and patient studies. In the phantom study, the MR-derived motion signals were additionally validated against the ground truth measurement of diaphragm displacement and left ventricle model triggering pulse. CONCLUSION/CONCLUSIONS:The proposed method yields accurate respiratory and cardiac motion-state tracking, requiring only a short (1.76 ms) additional navigator module, which is self-refocusing and imposes minimal constraints on sequence design.

Objectives: There is an urgent need for the development of Parkinson's disease (PD) treatments that can slow disease progression. LRRK2 (leucine-rich repeat kinase 2) has recently been identified as a causative gene for autosomal dominant Parkinson's disease (PD), with LRRK2 mutation G2019S linked to the most frequent familial form of PD. Several LRRK2 inhibitors have been developed and evaluated in vitro; however, in vivo target engagement has never been characterized. Despite research efforts invested to date, there is no radiotracer available for in vivo imaging of LRRK2 using PET. In our pilot studies, we synthesized and evaluated two tritium-labeled potent and selective kinase inhibitors, [³H]LRRK2-IN-1 (1^st generation) and [³H]GNE-9605 (second-generation LRRK2 inhibitors), via in vitro (IC50, Kd, Bmax) and in vivo/ex vivo methodologies (autoradiography, bio-distribution, and blocking experiments) in rodents and human striatum tissues. Comparative studies indicated that, although LRRK2-IN-1 has a lower DELTAG (lower free binding energy to the target enzyme determined via docking studies) than GNE-9605, GNE-9605 is more CNS permeable due to its higher lipophilicity than LRRK2-IN-1, suggesting more promising properties for ligands derived from second-generation LRRK2 inhibitors. We have, since then, identified candidates that are more potent and selective than current known LRRK2 inhibitors, based on in vitro assays. Radiolabeling and microPET evaluation studies are ongoing, preliminary results will be presented.
Method(s): We have prepared and evaluated several novel LRRK2 inhibitors and compared their in vitro properties (e.g., IC50 values,membrane permeability, and the P-glycoprotein liability) with those previously developed LRRK2 inhibitors, such as GNE compounds. We have also synthesized several corresponding precursors and carried out radiolabeling with either C-11 or F-18 to obtain the desired target molecules for further evaluation of their in vivo properties as PET ligands via microPET/CT studies, including in vivo/ex vivo bio-distribution and blocking studies.
Result(s): Several in vitro assays were conducted to compare IC50 values (for example, in HEK293 cells with transient overexpression of LRRK2 G2019S measuring decrease of phosphoserine 935 with an antibody in a robust Meso Scale Discovery assay) for LRRK2-a and LRRK2-b (novel inhibitors) vs. GNE-7915 and GNE-9605. The results are consistently indicated that LRRK2-b (10 nM) is more potent and selective than GNE-7915 (40 nM), and GNE-9605 (90 nM). The results of the low efflux ratio (<3) from the CNS permeability measurement via MDR assay in the absence or presence of a Pgp inhibitor suggested that LRRK2-b is a promising candidate as its BBB permeability may not be a concern and it is not a good Pgp substrate. Radiolabeling of LRRK2-a and LRRK2-b with F-18 has been accomplished via one-step fluoro-for-tosyl radiosynthesis. In vivo microPET/CT evaluation studies in mice are underway.
Conclusion(s): Potential in vivo imaging of LRRK2 with PET is an exciting, but at the same time uncharted research area, limited thus far by a lack of relevant information, resources and tools. Based on the in vitro and in vivo/ex vivo results, we have identified several candidates and will fine-tune the structure-activity relationship (SAR) to generate promising PET ligand candidates for in vivo imaging of brain LRRK2