Review
Medicine, Research & Experimental
Julie Bolcaen, Janke Kleynhans, Shankari Nair, Jeroen Verhoeven, Ingeborg Goethals, Mike Sathekge, Charlot Vandevoorde, Thomas Ebenham
Summary: Despite challenges in treating glioblastoma, advancements in radiopharmaceuticals offer potential for individualized treatment options. The development of targeted radionuclide therapy promises personalized approaches based on molecular-level assessments of disease. This development opens new possibilities for tailored therapeutic modalities, although challenges remain in effectively treating glioblastoma.
Article
Oncology
Mengze Xu, Zhiyi Chen, Junxiao Zheng, Qi Zhao, Zhen Yuan
Summary: The use of artificial intelligence in biomedical imaging has shown its effectiveness in individualized cancer medicine. Optical imaging methods can provide detailed information of tumors with high contrast, low cost, and noninvasive property. However, there is a lack of systematic work on AI-aided optical imaging for cancer theranostics.
SEMINARS IN CANCER BIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
George Sgouros, Yuni K. Dewaraja, Freddy Escorcia, Stephen A. Graves, Thomas A. Hope, Amir Iravani, Neeta Pandit-Taskar, Babak Saboury, Sara St James, Pat B. Zanzonico
Summary: The study focuses on factors impacting the absorbed dose-response relationship for Radiopharmaceutical therapy (RPT) agents, including inflammation- or immune-mediated effects, the significance of theranostic imaging, radiobiology, differences in dosimetry methods, pharmacokinetic variances across patients, and the influence of tumor hypoxia on response to RPT.
JOURNAL OF NUCLEAR MEDICINE
(2021)
Review
Engineering, Biomedical
Manja Kubeil, Yota Suzuki, Maria Antonietta Casulli, Rozy Kamal, Takeshi Hashimoto, Michael Bachmann, Takashi Hayashita, Holger Stephan
Summary: Nanogels have a wide range of applications in the field of biomedicine, particularly in drug delivery, therapeutic applications, tissue engineering, and sensor systems. Cyclodextrin-based nanogels are highly biocompatible and customizable, making them especially important. While most biological investigations are currently carried out in vitro, in vivo applications are becoming more important. Radiolabeled nanogels have potential for imaging and therapy.
ADVANCED HEALTHCARE MATERIALS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Neeta Pandit-Taskar, Amir Iravani, Dan Lee, Heather Jacene, Dan Pryma, Thomas Hope, Babak Saboury, Jacek Capala, Richard L. Wahl
Summary: The use of radiopharmaceutical therapies in cancer treatment is growing rapidly, but there is a lack of patient-specific dosimetry in current clinical RPTs. This underutilization of dosimetry in practice could hinder the optimization of tumor-absorbed dose while maintaining safe levels in normal organs.
JOURNAL OF NUCLEAR MEDICINE
(2021)
Review
Genetics & Heredity
Deepti Malik, Saniya Mahendiratta, Harpinder Kaur, Bikash Medhi
Summary: Therapeutic options for cancer are increasing, but a definitive cure has not yet been found, highlighting the need for continuous innovation and exploration of various approaches to tackle cancer. Many patients require multiple lines of treatment, and advancements in treatment options are continuously evolving.
Review
Medicine, Research & Experimental
Paromita Sarbadhikary, Blassan P. George, Heidi Abrahamse
Summary: Photodynamic Therapy (PDT) has emerged as a promising alternative in cancer diagnosis and treatment, utilizing light-induced activation of photosensitizers to kill cancer cells. PDT offers advantages such as minimal invasiveness and spatio-temporal control, with proper planning of parameters being crucial for efficacy. The design of PS formulations for imaging-guided PDT has shown promising potential, with recent advances in activatable phototheranostic agents enhancing the specificity of treatment.
Review
Biochemistry & Molecular Biology
Daniela Miladinova
Summary: Targeting HER2 for imaging and therapy in nuclear medicine involves developing more powerful radiopharmaceuticals. Zirconium-89 is essential for immune PET imaging and can be labeled with anti-HER2 antibodies. Other PET tracers like Cuprum-64 and Galium-68, as well as SPECT radiopharmaceuticals Indium-111 and Technetium-99m, have also been attempted. Nanobodies, affibodies, and minibodies have been developed as smaller molecules with shorter residence times for imaging. Silica nanoparticles conjugated with anti-HER2 antibodies allow targeted delivery of antitumor agents with radioisotopes commonly used for radionuclide therapy.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2023)
Article
Oncology
Arman Rahmim, Julia Brosch-Lenz, Ali Fele-Paranj, Fereshteh Yousefirizi, Madjid Soltani, Carlos Uribe, Babak Saboury
Summary: This work highlights the importance of digital twins for patient data and virtual clinical operations in medical field. Theranostic digital twins (TDTs) are considered as a natural and feasible approach in personalized radiopharmaceutical therapies. Utilizing multi-modal multi-scale images and AI techniques, routine digital twinning of patients can enhance deliveries of RPTs and overall healthcare.
FRONTIERS IN ONCOLOGY
(2022)
Article
Medicine, General & Internal
Alexandra Foster, Shubhanchi Nigam, David S. Tatum, Itay Raphael, Jide Xu, Rajeev Kumar, Elizabeth Plakseychuk, Joseph D. Latoche, Sarah Vincze, Bo Li, Rajan Giri, Lauren H. McCarl, Robert Edinger, Murat Ak, Vishal Peddagangireddy, Lesley M. Foley, T. Kevin Hitchens, Rivka R. Colen, Ian F. Pollack, Ashok Panigrahy, Darren Magda, Carolyn J. Anderson, W. Barry Edwards, Gary Kohanbash
Summary: Researchers successfully labeled CD11b antibody using a bifunctional chelator Lumi804 to image and treat TAMCs in murine gliomas. The Lu-177-Lumi804-alpha CD11b treatment not only reduced TAMC population but also improved the efficacy of immunotherapy.
Article
Oncology
Samuel Nussbaum, Mira Shoukry, Mohammed Ali Ashary, Ali Abbaszadeh Kasbi, Mizba Baksh, Emmanuel Gabriel
Summary: This review discusses recent advances in cancer imaging, including artificial intelligence, molecular imaging, and intravital imaging. These technologies have the potential to improve the detection, monitoring, and treatment of cancer.
Review
Radiology, Nuclear Medicine & Medical Imaging
Dimitris Visvikis, Philippe Lambin, Kim Beuschau Mauridsen, Roland Hustinx, Michael Lassmann, Christoph Rischpler, Kuangyu Shi, Jan Pruim
Summary: This review explores the potential applications of artificial intelligence (AI) in the fields of nuclear medicine and molecular imaging, highlighting both the physical and clinical perspectives. It discusses the challenges of transferring AI research into clinical practice and the concept of explainable AI. Furthermore, it focuses on the challenges that need to be addressed to introduce AI in a reliable manner in this field.
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
(2022)
Review
Pharmacology & Pharmacy
Isabeau Vermeulen, Emre M. Isin, Patrick Barton, Berta Cillero-Pastor, Ron M. A. Heeren
Summary: In addition to individual imaging techniques, the combination and integration of several imaging techniques, known as multi-modal imaging, play a crucial role in drug discovery and development. They provide valuable information for understanding disease mechanisms, identifying new pharmacological targets, and evaluating potential drug candidates and treatment response.
DRUG DISCOVERY TODAY
(2022)
Review
Chemistry, Multidisciplinary
Yixin Wang, Zhaoting Li, Quanyin Hu
Summary: Self-regulated micro/nano drug delivery devices can sense physiological changes and adjust their performance based on internal biological signals, bringing convenience and treatment outcomes to patients. Breakthroughs have been made in developing these devices with advanced technology and a better understanding of physiology.
Article
Chemistry, Multidisciplinary
Vanessa Jing Xin Phua, Chang-Tong Yang, Bin Xia, Sean Xuexian Yan, Jiang Liu, Swee Eng Aw, Tao He, David Chee Eng Ng
Summary: Nuclear imaging is a rapidly developing non-invasive imaging technique that uses radiolabeled nanomaterials as probes. By modifying the surface of nanomaterials, multifunctional radio-labeled nanomaterials can be obtained, enabling high sensitivity, resolution, and specificity in multimodal molecular imaging.
Article
Psychology, Clinical
Franziska Maier, Andrea Greuel, Marius Hoock, Rajbir Kaur, Masoud Tahmasian, Frank Schwartz, Ilona Csoti, Frank Jessen, Alexander Drzezga, Thilo van Eimeren, Lars Timmermann, Carsten Eggers
Summary: This study investigated impaired self-awareness of cognitive deficits in Parkinson's disease (PD) and its associations with clinical-behavioral and neuroimaging markers. The results showed that PD patients with mild cognitive impairment (PD-MCI) had significantly higher impaired self-awareness than healthy controls and PD patients without MCI. Neuroimaging analysis revealed that glucose metabolism in the cingulate cortex was negatively correlated with impaired self-awareness. In PD-MCI patients, impaired self-awareness was associated with decreased metabolism in the right temporal lobe, insula, and midcingulate cortex. These findings suggest that impaired self-awareness of cognitive deficits in PD may be related to disruptions in the cognitive network and metabolic changes in specific brain regions.
PSYCHOLOGICAL MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Anne M. Smith, Nancy A. Obuchowski, Norman L. Foster, Gregory Klein, P. David Mozley, Adriaan A. Lammertsma, Richard L. Wahl, John J. Sunderland, Jean-Luc Vanderheyden, Tammie L. S. Benzinger, Paul E. Kinahan, Dean F. Wong, Eric S. Perlman, Satoshi Minoshima, Dawn Matthews
Summary: Standardized approach in acquiring amyloid PET images increases their value as disease and drug response biomarkers. The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments.
JOURNAL OF NUCLEAR MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Isaac Shiri, Alireza Vafaei Sadr, Azadeh Akhavan, Yazdan Salimi, Amirhossein Sanaat, Mehdi Amini, Behrooz Razeghi, Abdollah Saberi, Hossein Arabi, Sohrab Ferdowsi, Slava Voloshynovskiy, Deniz Gunduz, Arman Rahmim, Habib Zaidi
Summary: This study developed a deep learning (DL) model using federated learning (FL) for the attenuation correction and scatter compensation (AC/SC) of PET images in a multicenter setting. The FL-based models showed excellent performance in terms of relative error and image prediction accuracy, comparable to centralized and center-based models.
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Babak Saboury, Tyler Bradshaw, Ronald Boellaard, Irene Buvat, Joyita Dutta, Mathieu Hatt, Abhinav K. Jha, Quanzheng Li, Chi Liu, Helena McMeekin, Michael A. Morris, Peter J. H. Scott, Eliot Siegel, John J. Sunderland, Neeta Pandit-Taskar, Richard L. Wahl, Sven Zuehlsdorff, Arman Rahmim
Summary: Trustworthiness is crucial in medicine as the patient-physician relationship evolves in the era of artificial intelligence. This report provides a roadmap for establishing trustworthy AI ecosystems in nuclear medicine, discussing both the opportunities and challenges associated with AI applications in this field. The plan emphasizes the importance of engaging stakeholders while ensuring the rational and safe deployment of AI technology in order to protect patients and society.
JOURNAL OF NUCLEAR MEDICINE
(2023)
Article
Engineering, Biomedical
Mohammad R. Salmanpour, Mahya Bakhtiyari, Mahdi Hosseinzadeh, Mehdi Maghsudi, Fereshteh Yousefirizi, Mohammad M. Ghaemi, Arman Rahmim
Summary: This study aims to investigate the use of machine learning systems to improve the prediction performance of Montreal Cognitive Assessment (MoCA) in Parkinson's disease patients. The study used clinical features, conventional imaging features, and radiomics features for prediction, and found that using larger datasets and optimized machine learning systems can significantly improve the prediction performance.
PHYSICS IN MEDICINE AND BIOLOGY
(2023)
Article
Pharmacology & Pharmacy
Mohammad Souri, Mohammad Kiani Shahvandi, Mohsen Chiani, Farshad Moradi Kashkooli, Ali Farhangi, Mohammad Reza Mehrabi, Arman Rahmim, Van M. Savage, M. Soltani
Summary: This study introduces an efficient nanosized drug delivery system with programmable size changes, which improves the accumulation of drug-carrying nanoparticles in tumors and achieves higher penetration depths. Reducing the size of nanoparticles leads to higher cell death rate and longer inhibition of tumor growth. This drug delivery system shows great promise in clinical applications.
Article
Biology
Hamid Abdollahi, Tania Dehesh, Neda Abdalvand, Arman Rahmim
Summary: This study aimed to develop xerostomia predictive models based on radiomics-dosiomics features. The results showed that the models combining CT and dose (Delta CT2-1 + Dose, CT3) and the dose-volume histogram model (DVH) had the highest predictive accuracy. These predictive models provide prospects for personalized therapy.
INTERNATIONAL JOURNAL OF RADIATION BIOLOGY
(2023)
Editorial Material
Radiology, Nuclear Medicine & Medical Imaging
Prabhakar Shantha Rajiah, Maria Jose Sarda, Ravi Ashwath, Harold Goerne
Article
Radiology, Nuclear Medicine & Medical Imaging
Habibeh Vosoughi, Mehdi Momennezhad, Farshad Emami, Mohsen Hajizadeh, Arman Rahmim, Parham Geramifar
Summary: This study explores harmonization strategies for comparable and robust quantitative metrics in a multicenter setting. The results show that harmonizing PET/CT systems improves the reproducibility of quantification. RC10V and RCpeak outperform other indices in terms of accuracy and reproducibility.
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY
(2023)
Article
Medicine, General & Internal
Mohammad R. Salmanpour, Seyed Masoud Rezaeijo, Mahdi Hosseinzadeh, Arman Rahmim
Summary: This study demonstrated that the utilization of deep features extracted from deep learning algorithms, combined with appropriate machine learning approaches, improved the accuracy of survival prediction compared to conventional deep features, tensor and conventional radiomics features, and end-to-end CNN frameworks.
Article
Radiology, Nuclear Medicine & Medical Imaging
Cassandra Miller, Carlos Uribe, Xinchi Hou, Arman Rahmim, Anna Celler
Summary: This study investigates the accuracy of quantitative SPECT imaging of Lu-177 in the presence of Y-90 in dual-isotope radiopharmaceutical therapy. Phantom simulations were conducted using the GATE Monte Carlo simulation toolkit, and multiple configurations and combinations were simulated. The results show that the quantification error is within +/- 6% of the no-Y-90 case, and quantitative accuracy may slightly improve when Y-90 is present. Lesion detectability is not degraded by the presence of Y-90.
BIOMEDICAL PHYSICS & ENGINEERING EXPRESS
(2023)
Article
Computer Science, Interdisciplinary Applications
Robert V. Bergen, Jean-Francois Rajotte, Fereshteh Yousefirizi, Arman Rahmim, Raymond T. Ng
Summary: This article introduces a 3D generative model called TrGAN, which can generate medical images with important features and statistical properties while protecting privacy. By evaluating through a membership inference attack, the fidelity, utility, and privacy trade-offs of the model were studied.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Review
Radiology, Nuclear Medicine & Medical Imaging
Cyrus Ayubcha, Shashi B. Singh, Krishna H. Patel, Arman Rahmim, Jareed Hasan, Litian Liu, Thomas Werner, Abass Alavi
Summary: The utilization of machine learning techniques in medicine has exponentially increased over the last decades. Applications of machine learning techniques to neuroimaging have unveiled various hidden interactions, structures, and mechanisms related to neurological disorders. This review article provides an overview of the diverse applications of machine learning to PET imaging of Alzheimer's disease.
NUCLEAR MEDICINE COMMUNICATIONS
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Donna M. Peehl, Cristian T. Badea, Thomas L. Chenevert, Heike E. Daldrup-Link, Li Ding, Lacey E. Dobrolecki, A. McGarry Houghton, Paul E. Kinahan, John Kurhanewicz, Michael T. Lewis, Shunqiang Li, Gary D. Luker, Cynthia X. Ma, H. Charles Manning, Yvonne M. Mowery, Peter J. O'Dwyer, Robia G. Pautler, Mark A. Rosen, Raheleh Roudi, Brian D. Ross, Kooresh I. Shoghi, Renuka Sriram, Moshe Talpaz, Richard L. Wahl, Rong Zhou
Summary: The availability of high-fidelity animal models has increased, allowing for preclinical studies relevant to cancer research. Co-clinical trials conducted on animal models that mirror patients' tumors have seen increased opportunities. However, quantitative imaging in co-clinical trials still needs optimization.