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A total of 47 abstracts by our Qurit lab and our collaborators (including 21 oral talks, 20 scientific posters, and 6 educational posters) were accepted to the Annual Meeting of the Society of Nuclear Medicine & Molecular Imaging (SNMMI) to be held in Vancouver in June 11-14, 2022. We will be eagerly looking forward to this great meeting.
Oral:
- C. Uribe, J. Brosch-Lenz, A. Peterson, B. Van, R. Fedrigo, J. Carlson, J. Sunderland. E. Frey, Y. Dewaraja
Variability in dosimetry calculations: An analysis of the results submitted to the SNMMI Lu-177 dosimetry challenge - J. Brosch-Lenz, A. Delker, L. Kaiser, S. Ziegler, P. Bartenstein, A. Rahmim, C. Uribe, G. Boning
Feasibility of single time point image-based dosimetry using prior knowledge: Application to Lu-PSMA-617 and Lu-PSMA-I&T therapy of prostate cancer - F. Yousefirizi, C. Holloway, A. Alexander, P. Tonseth, C. Uribe, A. Rahmim
Tumor segmentation of multi-centric whole-body PET/CT images from different cancers using a 3D convolutional neural network - F. Yousefirizi, A.K. Jha, S. Ahamed, I. Bloise, J.H. O, L.H. Sehn, K.J. Savage, C. Uribe, A. Rahmim
A novel loss function for improved deep learning-based segmentation: Implications of TMTV computation - F. Yousefirizi, S. Ahamed, J.H. O, I. Bloise, B. Saboury, A. Rahmim
Semi-supervised and unsupervised convolutional neural networks for automated lesion segmentation in PET imaging of lymphoma - A. Toosi, G. Chausse, C. Chen, I. Klyuzhin, F. Benard, A. Rahmim
Multi-modal, multi-organ deep segmentation of salivary and lacrimal glands in PSMA PET/CT images - M.R. Salmanpour, M. Hosseinzadeh, M. Bakhtiari, A.R. Gholami, M.M. Ghaemi, A.H. Nabizadeh, S.M. Rezaejo, A. Rahmim
Drug amount prediction in Parkinson's disease using hybrid machine learning systems and radiomics features - C. Miller, I. Klyuzhin, G. Chausse, J. Brosch-Lenz, G. Birindelli, K. Shi, B. Saboury, A. Rahmim, C. Uribe
Assessing the impact of tumor phenotype and size on dose rates of Ac using computational modeling of tumour growth - C. Miller, J. Brosch-Lenz, G. Chausse, A. Rahmim, C. Uribe
A novel computationally-effective absorbed dose kernel generation method for cellular dosimetry - S. Ahamed, A. Toosi, C. Uribe, A. Rahmim, F. Yousefirizi
Towards enhanced automated tumor detection using background slice annotation methods in clincial PET imaging of lymphoma - G. Hajanfar, S. Kalayinia, M. Hosseinzadeh, S. Samanian, M. Malek, S.M. Rezaeijo, V. Sossi, A. Rahmim, M.R. Salmanpour
Hybrid machine learning systems for prediction of Parkinson's disease pathogenic variants using clincial information and radiomics features - R. Fedrigo, G. Chausse, F. Yousefirizi, A. Rahmim, F. Benard, C. Uribe
Feasibility of enhanced salivary gland delination using PSMA PET imaging using a novel method to create a salivary gland phantom - H. Koniar, C. Rodriguez-Rodriguez, V. Radchenko, H. Yang, P. Kunz, C. Uribe, A. Rahmim, P. Schaffer
SPECT imaging of Ac-226 for radiopharmaceutical development: Performance evaluation as a theranostic isotope pair for Ac-225 - I. Shiri, M. Amini, Y. Salimi, A. Saanat, A. Saberi, B. Razeghi, S. Ferowsi, A. Vafaei Sadr, S. Voloshynovskiy, D. Gunduz, A. Rahmim, H. Zaidi
Multi-institutional PET/CT image segmentation using a decentralized federated deep transformer learning algorithm - S. Izadi, I. Shiri, C. Uribe, P. Geramifar, H. Zaidi, A. Rahmim, G. Hamarneh
Enhanced direct joint attenuation and scatter correction of whole-body PET images via context-aware deep networks - A. Bootherstone, L. Lee, L. Cristant, P. Kuo, C. Uribe, S.E. Black, K. Zukotynkki, V. Gaudet
A comparison of random forest and k-means clustering algorithms for classification of 18F-Florbetapir PET - T. O'Briain, C. Uribe, I. Sechopoulos, K. Yi, J. Teuwen, M. Bazalova-Carter
Unsupervised learning to perform respiratory motion correction in PET imaging - N. Jung, N. Aga, K. Selivanova, N. Colpo, M. Lu, C. Uribe
Whole Body and SPECT/CT imaging for dosimetry of 177Lu-labeled radiopharmaceutical therapies: A technologist's perspective - N. Colpo, C. Willliams, J. Brosch-Lenz, I. Bloisem A. Rahmim, F. Benard, C. Uribe
Exploring the Nuclear Medicine Technologist Role to Support Dosimetry in Radiophmaceutical Therapies - N. Colpo, R. Bahr, C. Uribe, P. Martineau
Supplemental email instructions for FDG PET/CT scans: Investigating the impact on preparation compliance rates - N. Colpo, T. Alden, R. Bahr, P. Petric, C. Uribe
Reducing the PET technologists' radiation exposure one autoinjector at a time
Scientific Posters:
- X. Hou, A. Hadjivassilou, I. Klyuzhin, F. Benard, D. Liu, A. Rahmim
Prediction of liver hypertrophy in patients undergoing Y-90 radioemboliation treatment - I. Klyuzhin, H.S.H. Ahn, A. Rahmim
Selection of optimal radiomics features for tumor phenotype differentaiton using stochastic tumor growth modeling - M.R. Salmanpour, M. Hosseinzadeh, S.M. Rezaeijo, C. Uribe, A. Rahmim
Robustnenss and reproducibility of radiomics features from fusions of PET-CT images - M.R. Salmanpour, M. Hosseinzadeh, M. Bakhtiari, M.M. Ghaemi, S.M. Rezaeijo, A.H. Nabizadeh, A. Rahmim
Cognitive outcome prediction in Parkinson's disease using hybrid machine learning systems and radiomics features - D. Du, I. Shiri, F. Yousefirizi, H. Zaidi, L. Lu, A. Rahmim
Effect of harmonization and oversampling methods on multi-center imbalanced PET datasets: Application to radiomics-based NSCLC-subtype prediction - S. Ahamed, G. Chausse, I. Klyuzhin, A. Rahmim, F. Yousefirizi
A comparative study of tumor detection models trained on coronal versus sagittal versal axial PET imaging slices - A. Fele-Paranj, J. Brosch-Lenz, C. Uribe, A. Rahmim, B. Saboury
Modular model architecture for radiopharmaceutical therapy planning: Physiologically-Based RadioPharmaoKinetics (PBRPK) implementation - A. Fele-Paranj, J. Brosch-Lenz, C. Uribe, B. Saboury, A. Rahmim
Non-linearities in the transition from imaging radiotracers to therapeutic radiopharmeceuticals - N. Shakourifar, M. Soltani, F.M. Kashkooli, J. Brosch-Lenz, B. Saboury, A. Rahmim
Effect of ligand amount and fraction of labeled peptides on internalized Lu-PSMA-I&T concentrations in tumors: Physiologically-based pharmacokinetic modeling - R. Fedrigo, R. Coope, A. Rahmim, F. Benard, C. Uribe
Canadian PET phantom for prostate oncology (C3PO): Effect of reconstruction parameters on quantification of PSMA PET images - R. Fedrigo, R. Coope, D.J. Kadrmas, J. Tang, I. Blouse, C. Gowdy, A. Rahmim, C. Uribe
Tumour quantification of [18F]FDG PET/CT in lymphoma using negative cast modelling - K.N. Lee, C. Uribe, A. Rahmim
A Matlab-based kinetic modeling tool for fast and robust estimation of Patlak-based parameters with uncertainty information - L. Polson, C. Uribe, A. Rahmim
Iterative PET reconstruction algorithms followed by non-local means denosing for improved quantitative imaging - I. Shiri, Y. Salimi, A. Sanaat, A. Saberi, A. Akhavanalaf, I. Mainta, A. Rahmim, H. Zaidi
Fully automated PET image artifacts detection and correction using deep neural networks - Y. Liu, Z. Liu, D. Du, J.M. Luna, A. Rahmim, A.K. Jha
Assessing linearity of PET-derived radiomics features accross scanners: Implications for ComBat harmonization - R. Bergen, J.F. Rajotte, F. Yousefirizi, A. Rahmim, T. Ng
3-D PET image generation with tumour masks using TGAN - G. Hajiadar, M. Sabouri, M. Mohebi, F. Arian, M. Yasemi, A. Bitarafan, M. Oveisi, A. Rahmim, I. Shiri, H. Zaidi
Harmonization of myocardial perfusion SPECT radiomics features: A patient study - S. Valavi, G. Hajianfar, F. Masoudi, M. Sohrabi, A. Bitarafan, M. Obeisi, A. Rahmim, I. Shiri, H. Zaidi
Parathyroid adenoma subtype decoding by using SPECT radiomic features and machine learning algorithms - M. Khateri, F. Babapour Mofrad, E. Jenabi, G. Hajianfar, E. Jafari, H. Dadgar, M. Asadi, A. Rahmim, I. Shiri, H. Zaidi
Non-invaisive prostate cancer histopathological subtype decoding using 68Ga-PSMA PET/CT radiomics features: A multi-centre study - A. Jabbarpour, I. Shiri, Y. Salimi, A. Sanaat, P. Geramifar, A. Rahmim, H. Zaidi
End-to-end unsupervised learning for direct attunation and scatter correction of whole-body 18F-FDG PET images using cycle GAN
Educational Posters:
- J. Brosch-Lenz, C. Uribe, A. Rahmim, B. Saboury
10 myths on the difficulties of implementing dosimetry-guided treatment planning and verification of radiopharmaceutical therapies - H. Abdollahi, B. Saboury, C. Uribe, A. Rahmim
Radiopharmacogenomics guided radiopharmaceutical therapy: Systems biology meets radiopharmaceuticals - B. Saboury, T. Bradshaw, R. Boellaard, I. Buvat, J. Dutta, M. Hatt, A.K. Jha, Q. Li, C. Liu, H. McMeekin, M.A. Morris, P.J.H. Scott, E. Siegel, J.J. Sutherland, R.L. Wahl, S. Zuehlsdorff, A. Rahmim
Artificial Intelligence ecosystem in nuclear medicine: Opportunities, challenges, and responsibilities - T.J. Bradshaw, R. Boellaard, I. Buvat, J. Dutta, A.K. Jha, P. Jacobs, Q. Li, C. Liu, A. Sitek, B. Saboury, P.J.H. Scott, P.J. Slomka, J.J. Sutherland, R.L. Wahl, F. Yousefirizi, S. Zuehlsdorff, A. Rahmim, I. Buvat
Pitfalls in the development of artificial intelligence algorithms in nuclear medicine and how to avoid them - A. K. Jha, T.J. Bradshaw, I. Buvat, M. Hatt, P. KC, C. Liu, N.F. Obuchowski, B. Saboury, P.J. Slomka, J.J. Sunderland, R.L. Wahl, Z. Yu, S. Zuehlsdorff, A. Rahmim, R. Boellaard
Best practices for evaluation of artificial intelligence-based algorithms for nuclear medicine: The RELAINCE guidelines - M. McCradden, J. Herington, K. Creel, R. Boellaard, A.K. Jha, A. Rahmim, PJ.H. Scott, J.J. Sunderland, R.L. Wahl, S. Zuehlsdorff, B. Saboury
Ethical risks in the development and deployment of artifical intelligence systems in nuclear medicine
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