Nicolas A Karakatsanis

Weill Cornell Medicine, Radiology, Faculty Member

Weill Cornell Medicine, Division of Radiopharmaceutical Sciences, Department of Radiology, Faculty Member

Université de Genève, Nuclear Medicine, Research Associate / Software Engineer

Mount Sinai School of Medicine, Translational Molecular Imaging Institute, Adjunct

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Dr. Nikolaos (Nicolas) A. Karakatsanis is currently Assistant Professor of Biomedical Engineering in the Radiology Department of Weill Cornell Medical College, Cornell University in New York, NY, USA. Dr Karakatsanis is also certified from the American Board of Science in Nuclear Medicine (ABSNM) with a specialty in Nuclear Medicine Physics and Instrumentation. Nicolas is also a Senior IEEE member and appointed as the executive Secretary in the Nuclear Medical Imaging Sciences Council (NMISC) of the IEEE Nuclear and Plasma Sciences Society (NPSS). Previously he was elected as a board member of NMISC (3-year term, 2017-2020) by the NPSS members. Moreover, Nicolas currently serves as the executive Secretary in the Physics, Instrumentation and Data Sciences Council (PIDSC) of the Society of Nuclear Medicine and Molecular Imaging (SNMMI). Previously he served in the Council as elected intern (2-year term, 2017-2019) and board member (2-year term, 2019-2021) of PIDSC. Nicolas is also serving as Associate Editor in Clinical Imaging journal and the Nuclear Medicine subsection of the Frontiers in Medicine journal.

Nicolas is aiming to enhance the diagnostic, prognostic and theranostic value of pre-clinical and clinical Positron Emission Tomography (PET) imaging for cardiovascular, oncologic and neurologic diseases. His main research focus has been the development of clinically feasible and quantitative PET/CT and PET/MR imaging methodologies, using:
- PET/CT and simultaneous PET/MR clinical systems
- novel and clinically adoptable whole-body dynamic PET acquisition protocols
- dual-tracer 4D PET/MR cardiovascular imaging
- whole-body multi-parametric SUV/Patlak-4D PET imaging
- data-driven respiratory and cardiac motion estimation and correction techniques within and after PET image reconstruction
- synergistic PET/MR image reconstruction for partial volume error (PVE) correction
- Time-of-Flight, Continuous Bed Motion & Resolution Modeling technologies for the benefit of PET-guided diagnostic, prognostic and theranostic clinical assessments
- NECR-based PET dosage optimization

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Address: Assistant Professor of Biomedical Engineering in Radiology
Division of Radiopharmaceutical Sciences, Department of Radiology
Weill Cornell Medical College, Cornell University
515 East 71st St., S-120, New York, NY, 10021

Adjunct Assistant Professor
Translational and Molecular Imaging Institute
Icahn School of Medicine at Mount Sinai
1470 Madison Ave, New York, NY, 10029

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Judith L Green

University of California, Santa Barbara

Natalie Baddour

University of Ottawa | Université d'Ottawa

Μιχαήλ Τσαγρής

University of Crete

Anoop Chaturvedi

University of Allahabad

Armando Marques-Guedes

UNL - New University of Lisbon

Lisa Gualtieri

Tufts University

Catherine Duynslaegher

UCLouvain (University of Louvain)

Jacobo Cal_González

Universidad Complutense de Madrid

Lev Manovich

Graduate Center of the City University of New York

Fikri gökpınar

Gazi University

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Papers by Nicolas A Karakatsanis

Comparison of the Physical Performance of two Siemens Biograph Vision PET models with Extended Axial Field-Of-View Using Sparse Detector Blocks

The Journal of Nuclear Medicine, May 1, 2021

多重クラスタ化実現を用いた新しい定量的全身パラメトリックPETイメージング【Powered by NICT】

IEEE Conference Proceedings, 2016

Prospective study of dynamic whole-body 68Ga-DOTATOC-PET/CT acquisition in patients with well-differentiated neuroendocrine tumors

Scientific Reports, Mar 1, 2021

To present the feasibility of a dynamic whole-body (DWB) 68 Ga-DOTATOC-PET/CT acquisition in pati... more To present the feasibility of a dynamic whole-body (DWB) 68 Ga-DOTATOC-PET/CT acquisition in patients with well-differentiated neuroendocrine tumors (WD-NETs). Sixty-one patients who underwent a DWB 68 Ga-DOTATOC-PET/CT for a histologically proven/highly suspected WD-NET were prospectively included. The acquisition consisted in single-bed dynamic acquisition centered on the heart, followed by the DWB and static acquisitions. For liver, spleen and tumor (1-5/patient), Ki values (in ml/min/100 ml) were calculated according to Patlak's analysis and tumor-to-liver (TLR-Ki) and tumor-to-spleen ratios (TSR-Ki) were recorded. Ki-based parameters were compared to static parameters (SUVmax/SUVmean, TLR/TSRmean, according to liver/spleen SUVmean), in the wholecohort and according to the PET system (analog/digital). A correlation analysis between SUVmean/ Ki was performed using linear and non-linear regressions. Ki-liver was not influenced by the PET system used, unlike SUVmax/SUVmean. The regression analysis showed a non-linear relation between Ki/SUVmean (R 2 = 0.55,0.68 and 0.71 for liver, spleen and tumor uptake, respectively) and a linear relation between TLRmean/TLR-Ki (R 2 = 0.75). These results were not affected by the PET system, on the contrary of the relation between TSRmean/TSR-Ki (R 2 = 0.94 and 0.73 using linear and non-linear regressions in digital and analog systems, respectively). Our study is the first showing the feasibility of a DWB 68 Ga-DOTATOC-PET/CT acquisition in WD-NETs. Abbreviations 18FDG 18-Fluorodesoxyglucose 68Ga-DOTA-SST Gallium-68 DOTA-conjugated somatostatin receptor-targeting peptide AUC Area under the curve DCB Dynamic cardiac-bed DWB Dynamic whole-body IF Input function Ki Net uptake rate KSR Ki-tumor to SUVmean-tumor ratio NECs Neuroendocrine carcinomas NETs Neuroendocrine tumors PET/CT Positron-emission tomography computed tomography PRRT Peptide-receptor radionuclide therapy ROI Region of interest

Nicolas A Karakatsanis

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