Atomic Emission Tomography: Secrets of the Human Body
Overview
Atomic Emission Tomography (AET) stands at the forefront of modern medical imaging technologies, providing unparalleled insights into the inner workings of the human body. This sophisticated imaging technique has revolutionized diagnostic medicine, allowing clinicians to visualize and understand physiological processes at the atomic level. In this comprehensive guide by Academic Block, we will examine the principles, advancements, applications, and future prospects of Atomic Emission Tomography, shedding light on its significance in the realm of healthcare.
The Foundation of Atomic Emission Tomography
Basics of Atomic Emission Tomography:
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Definition and Evolution: Atomic Emission Tomography is a non-invasive imaging technique that captures the distribution of radiotracers within the body to create detailed three-dimensional images. The roots of AET trace back to the mid-20th century, with significant advancements leading to the development of positron emission tomography (PET) and single-photon emission computed tomography (SPECT).
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Principles of AET: AET relies on the detection of emitted radiation from radiotracers introduced into the body. These tracers, often composed of radioisotopes, undergo decay processes, emitting gamma rays or positrons. Detectors surrounding the body capture these emissions, enabling the reconstruction of detailed images through tomographic algorithms.
Types of Atomic Emission Tomography:
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Positron Emission Tomography (PET): PET utilizes positron-emitting radioisotopes, such as fluorine-18, to trace metabolic and biochemical processes in the body. By detecting pairs of gamma photons resulting from positron-electron annihilation, PET provides high-resolution images that aid in cancer diagnosis, neurology, and cardiology.
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Single-Photon Emission Computed Tomography (SPECT): SPECT employs gamma-emitting isotopes like technetium-99m to study organ function and blood flow. The rotational acquisition of gamma ray data allows the creation of detailed 3D images, making SPECT an invaluable tool in cardiovascular imaging, bone scans, and neuroimaging.
Technological Advancements in AET
Instrumentation and Detectors:
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Detector Technologies: Recent advancements in detector technologies, such as solid-state detectors and photomultiplier tubes, have enhanced the sensitivity and spatial resolution of AET systems. These improvements contribute to more accurate and detailed imaging, enabling earlier detection of diseases.
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Hybrid Imaging Systems: Combining AET with other imaging modalities, such as computed tomography (CT) or magnetic resonance imaging (MRI), has led to the development of hybrid systems like PET/CT and SPECT/CT. These integrated platforms provide comprehensive anatomical and functional information in a single imaging session, improving diagnostic accuracy.
Radiotracers and Radiochemistry:
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Novel Radiotracers: Ongoing research in radiochemistry has resulted in the development of novel radiotracers with improved properties, including shorter half-lives, higher specificity, and reduced radiation exposure. These advancements expand the range of applications for AET, particularly in personalized medicine and targeted therapies.
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Theranostics: The concept of theranostics involves using radiotracers for both diagnostic imaging and targeted therapy. AET plays a crucial role in theranostics by guiding the administration of therapeutic agents to specific tissues, optimizing treatment outcomes while minimizing side effects.
Clinical Applications of Atomic Emission Tomography
Oncology:
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Cancer Diagnosis and Staging: AET has become a cornerstone in oncology, allowing for precise cancer diagnosis, staging, and monitoring of treatment response. PET/CT is widely employed to visualize metabolic activity in tumors, aiding in treatment planning and assessment of therapeutic efficacy.
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Radiation Therapy Planning: The integration of AET into radiation therapy planning enhances the accuracy of treatment targeting. PET/CT helps identify tumor boundaries and assess the response to therapy, optimizing the delivery of radiation doses and minimizing damage to surrounding healthy tissues.
Neurology:
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Brain Imaging: PET and SPECT play crucial roles in neuroimaging, offering insights into brain metabolism, blood flow, and neurotransmitter activity. AET is instrumental in diagnosing neurodegenerative disorders, such as Alzheimer's disease, and in mapping brain functions before surgical interventions.
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Epilepsy Localization: In cases of drug-resistant epilepsy, AET assists in localizing the epileptogenic focus within the brain. By visualizing abnormal metabolic activity, clinicians can tailor surgical interventions for improved seizure control.
Cardiology:
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Myocardial Perfusion Imaging: SPECT is extensively used in cardiology for myocardial perfusion imaging, providing valuable information about blood flow to the heart muscle. This aids in the diagnosis and risk stratification of coronary artery disease, guiding interventions like angioplasty or coronary artery bypass grafting.
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Viability Studies: AET helps assess myocardial viability by evaluating the metabolic activity of damaged heart tissue. This information is critical in determining whether revascularization procedures, such as coronary artery bypass surgery, would be beneficial for patients with ischemic heart disease.
Mathematical equations behind the Atomic Emission Tomography
The mathematical equations behind Atomic Emission Tomography (AET), specifically Positron Emission Tomography (PET), involve principles of physics, probability, and signal processing. The fundamental equations for PET focus on the detection and reconstruction of gamma ray emissions resulting from positron annihilation. Here, we'll provide a simplified overview of the key equations involved:
Decay of Positron-Emitting Radioisotopes:
The process begins with the decay of a positron-emitting radioisotope, such as fluorine-18. The decay process can be described using the equation for radioactive decay:
N(t) = N0 ⋅ e−λt ;
where:
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- N(t) is the number of radioactive atoms at time tt.
- N0 is the initial number of radioactive atoms.
- λ is the decay constant.
Positron Annihilation:
Positrons emitted from the radioactive isotope travel through the tissue until they encounter electrons. When a positron and an electron collide, they annihilate each other, producing two gamma-ray photons. These photons travel in opposite directions and are detected by the PET scanner.
Coincidence Detection:
PET scanners use detectors arranged in a ring around the patient. When two detectors simultaneously detect gamma rays (coincidence detection), it is likely that they originated from the same positron annihilation event. The probability of detecting two gamma rays simultaneously is proportional to the number of positron annihilations in a specific region.
Pcoincidence ∝ Number of positron annihilations in the region ;
Sinogram Formation:
The data collected from coincidence events are typically organized into a sinogram. The sinogram represents the likelihood of coincident gamma-ray detection as a function of the angle between the detectors.
Reconstruction Algorithms:
The sinogram data are used in reconstruction algorithms to create a three-dimensional image of the distribution of the positron-emitting radiotracer within the body. One common reconstruction algorithm is the filtered back projection, which involves mathematical operations to transform the sinogram into a voxel-based image.
I(x,y,z) = ∫∫∫S(θ,r)⋅P(θ,r,x,y,z) dθ dr ;
where:
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- I(x,y,z) is the intensity of the reconstructed image at position (x,y,z).
- S(θ,r) is the sinogram data.
- P(θ,r,x,y,z) is the back projection function.
These equations represent a simplified overview of the mathematical principles behind PET. The actual reconstruction process involves more sophisticated algorithms, corrections for factors like attenuation and scatter, and considerations for the specific geometry and characteristics of the PET scanner. Advanced iterative reconstruction methods are also employed in modern PET imaging for improved image quality and quantitative accuracy.
Challenges and Future Directions
Radiation Exposure and Safety:
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Optimizing Radiation Doses: While AET is invaluable in diagnosis and treatment planning, concerns about radiation exposure persist. Ongoing research focuses on optimizing radiotracer doses to maintain diagnostic efficacy while minimizing radiation risks, especially in pediatric and vulnerable populations.
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Advancements in Imaging Technologies: Emerging technologies, such as time-of-flight PET and advanced reconstruction algorithms, aim to further reduce scan times and radiation exposure. These innovations will contribute to making AET more patient-friendly without compromising image quality.
Artificial Intelligence in AET:
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Image Reconstruction and Processing: The integration of artificial intelligence (AI) in AET holds immense promise for image reconstruction and processing. Machine learning algorithms can enhance the speed and accuracy of image interpretation, aiding clinicians in diagnosing and monitoring diseases more efficiently.
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Predictive Modeling: AI-based predictive modeling can analyze AET data to identify patterns and predict disease progression. This approach has the potential to revolutionize personalized medicine by guiding treatment decisions based on an individual's unique physiological response.
Expanding Clinical Applications:
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Infectious Disease Imaging: AET's sensitivity to metabolic changes opens avenues for imaging infectious diseases. Research is underway to explore the role of AET in visualizing inflammation, tracking infectious agents, and monitoring treatment responses in conditions such as tuberculosis and HIV.
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Functional Connectomics: Advancements in neuroimaging techniques, including AET, contribute to the field of functional connectomics. Mapping brain connectivity and understanding the dynamics of neural networks could lead to breakthroughs in understanding and treating neurological disorders.
Final Words
In this article by Academic Block, we have seen that, the Atomic Emission Tomography has emerged as a cornerstone in modern medical imaging, providing clinicians with unprecedented insights into the intricate workings of the human body. From its humble beginnings to the present, AET has continuously evolved, driven by technological advancements and innovative applications across various medical disciplines. As research and development in AET continue, the future holds promise of enhanced safety, broader clinical applications, and a deeper understanding of the complex interactions within the human body. The journey of AET underscores the remarkable progress in medical imaging and serves as a testament to the ongoing commitment to advancing healthcare through cutting-edge technologies. Please provide your comments below, it will help us in improving this article. Thanks for reading!
This Article will answer your questions like:
Atomic Emission Tomography (AET) is an imaging technique that maps the distribution of elements and isotopes within a sample based on their atomic emission spectra. It utilizes spectroscopic principles to detect and spatially resolve elemental compositions, providing insights into material properties at a microscopic level. AET is particularly valuable for studying elemental distribution in complex samples without the need for extensive sample preparation.
AET differs from other tomographic techniques like CT and MRI by focusing on elemental rather than structural information. While CT and MRI visualize anatomical features using X-rays and magnetic fields respectively, AET maps elemental distributions using atomic emission spectra. This enables AET to reveal chemical composition and elemental changes in materials and biological samples with high sensitivity and spatial resolution.
Atomic Emission Tomography (AET) relies on the emission of characteristic wavelengths of light from excited atoms or ions in a sample. By detecting these emissions and mapping their spatial distribution, AET identifies and quantifies elements and isotopes present in the sample. This technique leverages the principles of spectroscopy and tomography to achieve high-resolution elemental imaging without the need for physical sectioning of the sample.
Atomic emission in AET involves inducing atoms or ions in the sample to emit characteristic wavelengths of light when excited by an external energy source, such as a laser or an electron beam. These emitted wavelengths are captured and analyzed to reconstruct spatial maps of elemental distribution within the sample. By scanning the sample from multiple angles, AET creates tomographic images that reveal the three-dimensional distribution of elements and isotopes, providing detailed insights into the sample's chemical composition and structure.
AET can image a wide range of elements and isotopes depending on their ability to emit characteristic wavelengths when excited. Common elements include metals such as iron, copper, and zinc, as well as non-metals like carbon and oxygen. Isotopes with distinct emission spectra, such as radioactive isotopes used in medical diagnostics and environmental monitoring, can also be imaged using AET. This versatility makes AET suitable for applications in materials science, environmental studies, and biomedical research.
AET enables precise mapping of elemental distribution in materials by detecting and visualizing the spatial arrangement of atoms and isotopes within a sample. This capability is crucial for understanding material properties, such as composition gradients, impurity concentrations, and phase distributions, at a microscopic level. By providing quantitative elemental data without destructive sampling, AET supports research in metallurgy, semiconductor manufacturing, and geological sciences, where detailed knowledge of elemental distribution influences material performance and processing strategies.
The main components of an Atomic Emission Tomography (AET) system include an excitation source (e.g., laser or electron beam) for inducing atomic emission, optical detectors (e.g., spectrometers or photomultiplier tubes) for capturing emitted light, and scanning mechanisms to acquire multiple projections of the sample. Signal processing units, such as data acquisition systems and computer algorithms, analyze emitted spectra and reconstruct three-dimensional images based on elemental emission patterns. AET systems are designed to operate under controlled environments to minimize background interference and optimize detection sensitivity, ensuring accurate spatial mapping of elemental distributions in various samples.
AET enhances sensitivity and spatial resolution by directly detecting elemental emissions, which are specific to each element and can be highly sensitive to minor concentrations. Unlike techniques focused solely on structural imaging, AET leverages spectroscopic principles to achieve high spatial resolution based on atomic emission wavelengths. This enables AET to discern elemental distributions at the microscopic scale, surpassing the spatial limitations of conventional tomographic methods. By optimizing excitation sources and detector technologies, AET systems maximize signal-to-noise ratios and minimize background interference, enhancing sensitivity and spatial resolution in elemental imaging applications across scientific research and industrial sectors.
AET finds primary applications in scientific research and industry for elemental analysis and mapping. In research, AET is used to study material composition, elemental changes in biological samples, and environmental monitoring of pollutants. In industry, AET contributes to quality control in manufacturing processes, analysis of metal alloys, and characterization of semiconductor materials. Its ability to provide non-destructive, three-dimensional elemental imaging supports advancements in materials science, environmental sciences, archaeology, and medical diagnostics, where precise knowledge of elemental distribution influences product development and scientific discoveries.
Data from Atomic Emission Tomography (AET) is reconstructed into three-dimensional images using computational algorithms that process emitted spectra from multiple projection angles. These algorithms analyze the intensity and wavelength of emitted signals to determine the spatial distribution of elements and isotopes within the sample. By integrating spectral information from different angles, AET reconstructs voxel-based images that depict elemental concentrations and distributions in three dimensions, facilitating detailed analysis of material properties and biological structures without physical sectioning.
Atomic Emission Tomography (AET) faces challenges such as limited elemental sensitivity for trace elements, background interference from sample matrix components, and the need for calibration standards to quantify elemental concentrations accurately. Spatial resolution may also be compromised in samples with heterogeneous compositions or complex geometries, impacting the accuracy of elemental mapping. Additionally, AET setups require sophisticated instrumentation and controlled environments to minimize spectral artifacts and optimize signal-to-noise ratios. Overcoming these challenges requires advancements in detector sensitivity, spectral analysis algorithms, and calibration methods to expand AET's applicability in diverse scientific and industrial settings.
AET integrates with spectroscopic techniques by utilizing emitted wavelengths from excited atoms or ions to identify and quantify elemental compositions within a sample. Spectroscopic analysis in AET involves resolving characteristic emission lines associated with specific elements and isotopes, providing qualitative and quantitative information about their spatial distribution. By combining spectral data from AET with techniques like X-ray fluorescence and laser-induced breakdown spectroscopy, researchers achieve comprehensive elemental analysis and mapping in materials science, environmental monitoring, and biomedical research. This integration enhances the versatility and analytical capabilities of AET for studying elemental interactions, trace element distributions, and chemical changes in diverse samples.
Recent advancements in Atomic Emission Tomography (AET) technology include improvements in detector sensitivity and resolution, enabling enhanced detection of trace elements and finer spatial mapping of elemental distributions. Advanced spectral processing algorithms and machine learning techniques have been integrated to automate data analysis and improve spectral resolution, accelerating the interpretation of AET images in research and industrial applications. Additionally, developments in excitation sources such as tunable lasers and electron beams have expanded AET's capability to image a broader range of elements and isotopes with higher accuracy and reduced measurement times. These technological advancements continue to propel AET as a pivotal tool for elemental analysis in materials science, environmental studies, and biomedical research.
Hardware and software required for Atomic Emission Tomography
Hardware Components:
- Gamma Camera or PET Scanner:
- For SPECT, a gamma camera is used to detect gamma rays emitted by the radiotracers.
- In PET, a dedicated PET scanner is employed to detect pairs of gamma rays resulting from positron annihilation.
- Collimators:
- Collimators in gamma cameras are crucial for spatial resolution by allowing only parallel rays to reach the detectors.
- In PET, collimators are not used due to the nature of positron annihilation.
- Radiotracer Delivery System: A system for introducing radiotracers into the patient’s body, typically through injection for both PET and SPECT.
- Patient Bed: A stable and adjustable bed to position the patient accurately within the scanner.
- Detector Arrays: Arrays of detectors surround the patient to capture emitted gamma rays or positron annihilation events.
- Coincidence Detection System (for PET): A system that identifies simultaneous detections of gamma rays in different detectors, indicating a positron annihilation event.
- Computer System: A high-performance computer system is required for real-time data acquisition, processing, and reconstruction.
- Powerful Data Storage: Adequate data storage for the large volumes of imaging data generated during scans.
- Quality Control Tools: Instruments to monitor and maintain the performance of the imaging system.
Software Components:
- Acquisition Software: Controls the acquisition of imaging data from detectors, managing parameters such as scan duration and timing intervals.
- Reconstruction Software: Utilizes mathematical algorithms (e.g., filtered back projection, iterative reconstruction) to convert raw data into three-dimensional images.
- Attenuation Correction Software: Corrects for attenuation of gamma rays as they pass through different tissues in the body, improving the accuracy of the reconstructed images.
- Image Processing and Analysis Tools: Software for enhancing, visualizing, and analyzing the reconstructed images. This may include tools for region-of-interest analysis, 3D rendering, and quantification.
- Data Storage and Archiving: Software for managing and storing imaging data efficiently, including archiving for long-term storage and retrieval.
- Integration with Other Modalities (for Hybrid Systems): Software that enables seamless integration with other imaging modalities, such as CT or MRI, in hybrid systems like PET/CT or SPECT/CT.
- Clinical Reporting and Integration with PACS: Tools for generating clinical reports and integration with Picture Archiving and Communication Systems (PACS) for easy access to patient data.
- Security and Compliance Software: Measures to ensure the security of patient data and compliance with healthcare regulations.
- Updates and Maintenance Software: Tools for applying software updates and performing system maintenance.
- DICOM (Digital Imaging and Communications in Medicine) Compatibility: Standards-compliant software for the communication and exchange of medical images and information.
Key figure in Atomic Emission Tomography
In the early 1950s, Ter-Pogossian, along with colleagues, began researching the medical applications of positron-emitting isotopes. This led to the creation of the first PET scanner, a device capable of detecting and imaging the distribution of positron-emitting radiotracers within the human body.
Ter-Pogossian’s contributions to the field were instrumental in establishing PET as a powerful imaging modality, particularly in the field of oncology. His work laid the foundation for the continued advancements and widespread clinical use of PET in diagnosing and monitoring various medical conditions.
Facts on Atomic Emission Tomography
Development of PET and SPECT: Atomic Emission Tomography (AET) encompasses Positron Emission Tomography (PET) and Single-Photon Emission Computed Tomography (SPECT). PET was developed in the 1970s, primarily by Michel Ter-Pogossian, and SPECT followed shortly thereafter.
Principle of AET: AET involves the detection of emitted radiation from radiotracers introduced into the body. These tracers emit gamma rays or positrons during decay processes, and detectors capture these emissions to create detailed three-dimensional images.
Radiotracers and Isotopes: Radiotracers used in AET are often composed of radioisotopes, such as fluorine-18 (used in PET) or technetium-99m (used in SPECT). The choice of radiotracer depends on the specific physiological process or organ being studied.
Positron Annihilation (for PET): In PET, positron-emitting radioisotopes decay within the body, producing positrons. When a positron encounters an electron, they annihilate each other, emitting two gamma rays in opposite directions. PET detectors capture these gamma rays for imaging.
Gamma Ray Detection (for SPECT): SPECT relies on gamma-emitting radioisotopes. The gamma camera rotates around the patient, capturing gamma rays emitted from the radiotracer. The data is then used to create three-dimensional images.
Clinical Applications: AET is widely used in oncology for cancer diagnosis, staging, and treatment response monitoring. In cardiology, SPECT is utilized for myocardial perfusion imaging, aiding in the diagnosis of coronary artery disease. Neurology benefits from PET and SPECT for imaging brain function, detecting neurodegenerative diseases, and mapping neurological disorders.
Hybrid Imaging Systems: PET/CT and SPECT/CT are hybrid imaging systems that combine AET with computed tomography (CT). These integrated systems provide both anatomical and functional information in a single imaging session.
Quantitative Imaging: AET allows for quantitative analysis of physiological processes, providing not only qualitative images but also quantitative data on tissue metabolism, blood flow, and other parameters.
Radiation Exposure: Concerns about radiation exposure in AET have led to ongoing research and technological advancements aimed at optimizing radiotracer doses while maintaining diagnostic efficacy.
Theranostics: AET has contributed to the development of theranostics, where the same radiotracer is used for both diagnostic imaging and targeted therapy. This approach is particularly promising in personalized medicine.
Artificial Intelligence Integration: Machine learning and artificial intelligence are increasingly integrated into AET for image reconstruction, processing, and analysis. AI algorithms enhance the speed and accuracy of image interpretation.
Research in Infectious Diseases: AET is being explored for imaging infectious diseases, providing insights into inflammation, pathogen distribution, and treatment responses.
Functional Connectomics (for PET): PET, in combination with other imaging techniques, contributes to the emerging field of functional connectomics, mapping connectivity and interactions within the brain’s neural networks.
Continual Technological Advancements: Ongoing research focuses on improving detector technologies, developing novel radiotracers, and exploring new applications of AET in various medical disciplines.
Academic References on Atomic Emission Tomography
- Cherry, S. R., & Sorenson, J. A. (2003). Physics in Nuclear Medicine. Philadelphia, PA: Saunders.
- Valk, P. E., Bailey, D. L., & Townsend, D. W. (2003). Positron Emission Tomography: Basic Sciences. Secaucus, NJ: Springer.
- Phelps, M. E., Huang, S. C., & Hoffman, E. J. (1979). Tomographic measurement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2-deoxy-D-glucose: Validation of method. Annals of Neurology, 6(5), 371-388.
- Beyer, T., & Townsend, D. W. (2001). A combined PET/CT scanner: the path to true image fusion. The British Journal of Radiology, 74(Spec No 1), S24-S30.
- Goerres, G. W., Burger, C., Kamel, E., Seifert, B., & Hany, T. F. (2003). Clinical evaluation of a dedicated PET scanner for FDG imaging of the heart. The Journal of Nuclear Medicine, 44(4), 603-609.
- Cherry, S. R. (2004). The 2003 Henry N. Wagner Lecture: Of mice and men (and positrons)—advances in PET imaging technology. Journal of Nuclear Medicine, 45(6), 24N-35N.
- El Fakhri, G., Kijewski, M. F., & Johnson, K. A. (2009). Synergy and pitfalls in combining anatomical and functional imaging with PET. In Positron Emission Tomography (pp. 513-532). Humana Press.
- Kinahan, P. E., & Fletcher, J. W. (2010). Positron emission tomography-computed tomography standardized uptake values in clinical practice and assessing response to therapy. Seminars in Ultrasound, CT and MRI, 31(6), 496-505.
- Minoshima, S., Koeppe, R. A., Frey, K. A., Kuhl, D. E., & Anzai, Y. (1994). A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. Journal of Nuclear Medicine, 35(2), 319-329.
- Rahmim, A., & Zaidi, H. (2008). PET versus SPECT: Strengths, limitations and challenges. Nuclear Medicine Communications, 29(3), 193-207.
- Boellaard, R., O’Doherty, M. J., Weber, W. A., Mottaghy, F. M., Lonsdale, M. N., Stroobants, S. G., … & Shankar, L. K. (2010). FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0. European Journal of Nuclear Medicine and Molecular Imaging, 37(1), 181-200.
- Belhocine, T., Thille, A., Nasr, A., Brasseur, P., & Flamen, P. (2012). 18F-FDG PET imaging in assessing exocrine pancreas alterations in diabetes: Contribution to the debate. Diabetes Care, 35(12), e83-e83.
- Hossain, M., Saha, A., & Watanabe, S. (2014). A comprehensive review of positron emission tomography (PET) in oncology. Asian Pacific Journal of Cancer Prevention, 15(5), 2089-2095.
- Townsend, D. W., & Beyer, T. (2008). A combined PET/CT scanner: the path to true image fusion. The British Journal of Radiology, 81(961), 361-370.