Mahdjoub Hamdi

I currently hold a Staff Scientist position at Washington University, Department of Radiological Sciences, School of Medicine. This role follows a fruitful five-year postdoctoral research associate position at the same institution. My PhD thesis was a result of a collaboration between the Department of Electrical Engineering at the University of Mostaganem and the Department of Nuclear Medicine and Radiobiology, where I developed and validated a Monte Carlo Simulation model of a Small Animal Radiation Research Platform (SARRP) with zooming capabilities. The SARRP model has imaging and radiation treatment capabilities. During my postdoctoral traineeship, I have a multi-research project. I have worked on the evaluation of advanced PET/MRI attenuation correction approaches in the context of PET/MRI qualification for clinical use. I have worked on the development of highly innovative, non-conventional PET systems. PET image quantification and image analysis. As a staff scientist within the Preclinical Imaging Facility. My responsibilities revolve around the operation, maintenance, and technical troubleshooting of cutting-edge imaging modalities, including PET, CT, and MRI. My daily objective is to ensure the production of high-quality images. My role is critical for maintaining the high standards of the Preclinical Imaging Facility. My duties will involve maintaining fully calibrated cameras for absolute activity, optimizing data acquisition, image reconstruction, and processing methodologies for specific applications. I am also involved in the development of novel imaging procedures and technologies employing the imaging equipment.

• Peer-reviewed papers, An automatic pipeline for evaluating brain PET/MRI attenuation correction approaches using synthetic imaging and Freesurfer, Mahdjoub Hamdi, Chunwei Ying, An Hongyu, Richard Laforest, EJNMMI Physics, 10, 71, 2023
• Peer-reviewed papers, Phase 1 Evaluation of 11C-CS1P1 to Assess Safety and Dosimetry in Human Participants, Matthew R. Brier, Mahdjoub Hamdi, Jayashree Rajamanikam, Haiyang Zhao, Syahir Mansor, Lynne Jones, Farzaneh Rahmani, Saurabh Jindal, Deborah Koudelis, Joel S. Perlmutter, Dean F. Wong, Michael Nickels, Joseph Ippolito, Robert J. Gropler, Thomas H. Schindler, Richard Laforest, Zhude Tu, Tammie L. S. Benzinger, Journal of Nuclear Medicine, March, 2022
• Peer-reviewed papers, Evaluation of attenuation correction in PET/MRI with synthetic lesion insertion, Mahdjoub Hamdi, Yutaka Natsuaki, Kristen A Wangerin, Hongyu An, Sarah St James, Paul E Kinahan, John J Sunderland, Peder EZ Larson, Thomas A Hope, Richard Laforest, Journal of Medical Imaging, 8, 05, 2021
• Peer-reviewed papers, Comparison between X-ray spectra and their effective energies in small animal CT tomographic imaging and dosimetry, Mahdjoub Hamdi, Mimi Malika, M'hamed Bentourkia, Australasian Physical & Engineering Sciences in Medicine, 40, 1, 29-37, 2017
• Book chapters, Applications of computational animal models in radiation therapy research, M'hamed Bentourkia, Mahdjoub Hamdi, Faiçal A. A. Slimani, IOP Publishing, 2018, 978-0-7503-1344-5
• Book chapters, Dose Calculation in a Mouse Lung Tumor and in Secondary Organs During Radiotherapy Treatment: A Monte Carlo Study, Mahdjoub Hamdi, Mimi Malika, M'hamed Bentourkia, Bioinformatics and Biomedical Engineering, IWBBIO 2015, 9043, Springer, 2015
• Conference papers, Comparison of X-ray beam energy spectrum and effective energy in small animal imaging and dosimetry, Mahdjoub Hamdi, Mimi Malika, M'hamed Bentourkia, IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), San Diego, CA, 2015, 1-4
• Conference papers, Design and Implementation of a Graphical User Interface for Dosimetry Calculation in Radiotherapy, Faiçal A. A. Slimani, Mahdjoub Hamdi, M'hamed Bentourkia, IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Atlanta, Georgia, 2016, 1-4
• Conference papers, Effect of scatter underestimation on SUV uptake using the DIXON attenuation map in PET/MRI, Mahdjoub Hamdi, Yasheng Chen, Richard Laforest, Journal of Nuclear Medicine, May, 2021, 62, 1, 1556
• Conference papers, Evaluation of different attenuation approaches in PET/MRI on quantification in the brain using a lesion simulator, Mahdjoub Hamdi, Chunwei Ying, Hongyu An, Thomas A Hope, Richard Laforest, Journal of Nuclear Medicine, May, 2020, 61, 1, 1468
• Conference papers, Impact of Reconstruction Algorithms on the Quantitative Evaluation of 11C-PiB PET/CT Studie, Syahir Mansor, Mahdjoub Hamdi, Richard Laforest, Journal of Nuclear Medicine, May, 2020, 61, 1, 1459
• Conference papers, Quantitative Evaluation of three Siemens Biograph PET scanners using different reconstruction algorithms and parameters, Mahdjoub Hamdi, Syahir Mansor, Richard Laforest, Journal of Nuclear Medicine, May, 2020, 61, 1, 1503

• Qualification and Harmonization of PET/MRI for Cancer Clinical Trials, Develop a standard methodology to evaluate MRI-based attenuation correction techniques and the related PET quantitation accuracy to qualify PET/MRI scanners for clinical trials and clinical work, Development and validation of a computer-based synthetic lesion insertion tool for the Siemens PET/MRI system, named Biograph mMR, and used it to evaluate the effect of different PET/MRI attenuation correction (AC) approaches on the quantitative accuracy of PET/MRI reconstructed images using NEMA IEC phantom and patient data, Harmonize the developed Biograph mMR lesion insertion tool with an already developed synthetic lesion insertion tool for the GE SIGNA PET/MRI system, Brain ROIs based PET/MRI quantitative accuracy for neurodegenerative diseases, Make the lesion insertion tool available online for researchers to use, Led a peer-reviewed research paper on developing and validating the lesion insertion tool using phantom and patient data, Led and submitted a second research paper on the extension of the already developed lesion insertion tool to be used as part of an automatic pipeline to evaluate the quantitative accuracy of PET/MRI attenuation correction in brain regions of interest (ROIs), Using a synthetic lesion insertion tool to evaluate different PET/MRI attenuation correction approaches will decrease the needed number of acquired patients, hence accelerating the translation of newly developed PET/MRI attenuation correction approaches to the clinical routines. The developed ROI-based lesion insertion in the brain was validated experimentally and provided realistic radiotracer distribution. Thus, the developed tool can be used for data augmentation for training a deep learning algorithm for Alzheimer's disease classification purposes. Furthermore, this approach will help reduce the time and effort consumed by labeling PET images.
• Dosimetric and safety assessment of newly developed radiotracers, Dosimetric and safety assessment of newly developed radiotracers before use for large-scale clinical trials, Calculate the effective radiation dose delivered by the patient's administered radiotracer to different organs in a cohort of patients, Co-authored a peer-reviewed research paper on the dosimetric safety of 11C (Amoniac) based radiotracer named CS1P1 for the intended use in neurological investigations, Done the dosimetric calculation of an 18F (Fluor 18) tracer, named [18] VAT, dedicated for neurological applications, Ongoing dosimetric and safety assessment for other radiotracers
• Deep learning PET denoising, Develop a spatiotemporal denoising method to improve time activity accuracy, reduce noise, and enhance contrast in PET patient images, Adapt synthetic brain lesion insertion tool to provide the ground truth for the deep learning algorithm, Presented at multiple international conferences, In the process of writing a paper to be published in a high-rank scientific journal, In the process of submitting a patent for the developed approach
• Development of high resolution and High sensitivity brain dedicated PET scanner for neuroimaging research, Develop a high-resolution and high-sensitivity brain PET scanner combined and to be used simultaneously with the clinical state-of-the-art whole-body PET/CT scanner, Monte Carlo Simulations (computer simulation) of a brain-dedicated PET scanner reconstruct the images and compare their physical performances to the state-of-the-art whole-body clinical PET/CT scanner, Generate results for an RO1 NIH grant proposal, Generated results for U01 grant proposal for the Brain Initiative, Presented the results at different local and international meetings in the field of medical imaging, Developing a brain-dedicated PET scanner will allow better quantification of brain uptake and a better understanding of brain functions and neurological diseases
• Translation of virtual-pinhole magnifying PET technology to clinical whole-body cancer imaging, Develop and translate a novel imaging technology called the 'Augmented Whole-body Scanning via Magnifying PET (AWSM-PET) to enhance the native image resolution and quality of a clinical PET/CT scanner', Develop computer-based Monte Carlo Simulations of the proposed clinical whole-body PET scanner combined with our added PET scanner (named Outsert) to investigate the Scanner-Outsert imaging performances, contrast, and spatial resolution compared to the native scanner, which is the Whole body Siemens Biograph Vision PET/CT scanner and perform GPU-based PET image reconstruction, Results were published in multiple international scientific conferences, Will start the first patient study in June 2024, This new capability will improve the diagnostic accuracy of PET/CT for detecting very small metastasis in cancer patients. Accurate diagnosis and staging of cancer are critical for physicians to identify the best treatment options to manage the disease.

• M'hamed Bentourkia, Department of Nuclear Medicine and Radiobiology at Sherbrook University, Sherbrooke, Quebec, Canada, mhamed.bentourkia@usherbrooke.ca
• Samanta Suranjana, Senior Scientist at United imaging, suranjana.samanta@united-imaging.com