Molecular PET/CT Imaging-Guided Radiation Therapy Treatment Planning

Zaidi, Habib; Vees, Hansjörg; Wissmeyer, Michael

doi:10.1016/j.acra.2009.02.014

Cited by 73 publications

(55 citation statements)

References 298 publications

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“…20,21 Integration of functional PET data with anatomic CT data should be a standard in radiation therapy. 14,22 However, it remains a challenge to quantify the improvement of simulation with PET/CT over CT in radiation treatment planning, as conclusive clinical data are not yet available. Early studies have found PET/CT has advantages over CT in standardization of volume delineation, 23,24 in reduction of the risk for geometric misses, 25 and in minimization of radiation dose to the nontarget organs.…”

Section: Introductionmentioning

confidence: 99%

Attenuation Correction Strategies for Positron Emission Tomography/Computed Tomography and 4-Dimensional Positron Emission Tomography/Computed Tomography

Pan

Zaidi

2013

PET Clinics

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Section: Introductionmentioning

confidence: 99%

Attenuation Correction Strategies for Positron Emission Tomography/Computed Tomography and 4-Dimensional Positron Emission Tomography/Computed Tomography

Pan

Zaidi

2013

PET Clinics

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“…Medical images are used daily for diagnosis [1], treatment planning [2], and assessing a patient's response to treatment [3]. The usefulness of medical imaging has spurred revolutions in the acquisition technologies utilised as part of clinical workflows.…”

Section: Motivationmentioning

confidence: 99%

A graph-based approach for the retrieval of multi-modality medical images

Kumar

Kim

Wen

et al. 2014

Medical Image Analysis

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Advances in sensors and imaging technologies are contributing to rapidly expanding data repositories that contain interrelated information from different modalities. The extraction and visualisation of knowledge from these repositories is a major challenge in the modern, digital world. In the medical domain, images are routinely acquired for a variety of tasks, including diagnosis and patient monitoring. Advances in imaging technologies have resulted in devices capable of acquiring images in multiple dimensions (volumetric and dynamic) as well as from multiple modalities. One example of a widely used volumetric and multimodality image is combined positron emission tomography and computed tomography (PET-CT), which presents physicians with complementary functional and anatomical features and spatial relationships. In clinical practice, PET-CT imaging has already proven its ability to improve cancer diagnosis, localisation, and staging compared to its single-modality counterparts.The clinical benefits provided by medical imaging have spurred increases in the data volume acquired in clinical environments. As such, massive medical imaging collections offer the opportunity for search-based applications in evidence-based diagnosis, physician training, and biomedical research. However, conventional search techniques that operate upon manually assigned textual annotations are not feasible for the volume of data acquired in modern hospitals. Qualitative text descriptions are also limited in their capacity to quantitatively describe the rich information inherent in medical images. Content-based image retrieval (CBIR) is an image search technique that utilises visual features as search criteria. CBIR has already demonstrated benefits forevidence-based diagnosis, physician training, and biomedical research by allowing clinical staff to consider relevant knowledge from retrieved cases. The majority of medical CBIR research has focused on single modality medical images leaving a clear deficiency in the retrieval of multi-modality images. In particular, images iii like PET-CT offer the ability for retrieval based upon the relationships between regions in different modalities, such as the location of tumour features (from PET) in relation to organ features (from CT). The challenge of multi-modality image retrieval for cancer patients lies in representing these complementary geometric and topologic attributes between tumours and organs. A secondary challenge lies in the human aspect of retrieval -effectively communicating the retrieved results to users and facilitating a better understanding of the similarity between the query and retrieved multi-modality images.As such, in this thesis we propose a new graph representation for multimodality images. Our representation preserves the spatial relationships between modalities by emphasising the inherent characteristics of these images that are used for disease staging and classification. This is done by structurally constraining the graph based on image features, e.g., spatia...

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“…This includes estimation of organ volumes or tumor volumes as well as definition of target treatment volumes in radiation therapy [66,67] or for assessment of treatment response [68,69], extraction of parameters of clinical relevance such as the left ventricular region in nuclear cardiology [70,71], automated ROI delineation of structures of interest in dynamic functional imaging [72], generation of functional images to highlight regions of similar temporal behavior (components) [73,74], determination of the attenuation map in emission tomography [75], anatomicallytomically-guided image reconstruction and partial volume segmentation [48], and construction of voxel-based anthropomorphic phantoms based on high resolution anatomical images. For the latter, the interested reader is refered to a recent review describing the development of such computational models in connection with Monte Carlo modeling tools in radiological sciences [76].…”

Section: Image Segmentation In Quantitative Pet Imagingmentioning

confidence: 99%

Quantitative Techniques in PET-CT Imaging

Basu¹,

Zaidi²,

Holm³

et al. 2011

CMIR

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Abstract:The appearance of hybrid PET/CT scanners has made quantitative whole body scanning of radioactive tracers feasible. This paper deals with the novel concepts for assessing global organ function and disease activity based on combined functional (PET) and structural (CT or MR) imaging techniques, their advantages over current quantitative techniques and their potential clinical applications in the management of various diseases. First the complicated kinetic modeling and methods for calculation of the standardized uptake value (SUV) that have been utilized in the practice of clinical PET are briefly described. Subsequently we discuss the quantitative concepts in PET-CT imaging that have been developed in recent years: (a) SUV analysis in the dual-time point and delayed PET imaging, (b) partial volume correction of SUV for small lesions (c) assessment of global metabolic activity in the whole organ or of diseased sites and (d) the novel image segmentation techniques with FDG-PET and newer tracers to precisely define the diseased or intended normal tissue which is of great value for image guided radiation therapy.

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Molecular PET/CT Imaging-Guided Radiation Therapy Treatment Planning

Cited by 73 publications

References 298 publications

Attenuation Correction Strategies for Positron Emission Tomography/Computed Tomography and 4-Dimensional Positron Emission Tomography/Computed Tomography

Attenuation Correction Strategies for Positron Emission Tomography/Computed Tomography and 4-Dimensional Positron Emission Tomography/Computed Tomography

A graph-based approach for the retrieval of multi-modality medical images

Quantitative Techniques in PET-CT Imaging

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