The Advantage of PET and CT Integration in Examination of Lung Tumors

Purpose. To evaluate the diagnosis value of integrated positron emission tomography and computed tomography (PET/CT) with lung masses, this study emphasized the correlation between tumor size and maximum standardized uptake value (SUVmax) in selected regions of interest (ROI) of lung masses. Material and Methods. A retrospective analysis was performed on 85 patients with solid pulmonary lesions, all verified by pathology. The morphology, edge (speculated margins and lobule), size, density of pulmonary masses, and on-chest CT images were reviewed. The SUVmax in ROI of pulmonary masses was calculated. Results. Among the 85 patients with lung masses, 59 patients presented with pulmonary malignant neoplasm and 26 patients with benign lesions. The sensitivity, specificity, and accuracy were 89.8%, 61.5%, 81.2%, respectively, for PET measurement only, 88.1%, 65.4%, 81.2% for CT only, and 96.6%, 80.8%, 91.8% for PET/CT. The size of pulmonary malignant neoplasm in the 59 patients was apparently correlated with the ROI's SUVmax (r=0.617, P<.001). However, the size of pulmonary benign mass in the 26 patients was not correlated with the SUVmax. Conclusion. PET/CT is of greater value in characterization of lung masses than PET and CT performed separately. The examination of lung tumor can be further specified by the correlation between the size of pulmonary malignant neoplasm and the ROI's SUVmax

Focal Spot, Spring 1993

https://digitalcommons.wustl.edu/focal_spot_archives/1063/thumbnail.jp

PET-MR imaging using a tri-modality PET/CT-MR system with a dedicated shuttle in clinical routine

Tri-modality PET/CT-MRI includes the transfer of the patient on a dedicated shuttle from one system into the other. Advantages of this system include a true CT-based attenuation correction, reliable PET-quantification and higher flexibility in patient throughput on both systems. Comparative studies of PET/MRI versus PET/CT are readily accomplished without repeated PET with a different PET scanner at a different time point. Additionally, there is a higher imaging flexibility based on the availability of three imaging modalities, which can be combined for the characterization of the disease. The downside is a somewhat higher radiation dose of up to 3mSv with a low dose CT based on the CT-component, longer acquisition times and potential misalignment between the imaging components. Overall, the tri-modality PET/CT-MR system offers comparative studies using the three different imaging modalities in the same patient virtually at the same time, and may help to develop reliable attenuation algorithms at the same tim

IMAGE PROCESSING, SEGMENTATION AND MACHINE LEARNING MODELS TO CLASSIFY AND DELINEATE TUMOR VOLUMES TO SUPPORT MEDICAL DECISION

Techniques for processing and analysing images and medical data have become the main’s translational applications and researches in clinical and pre-clinical environments. The advantages of these techniques are the improvement of diagnosis accuracy and the assessment of treatment response by means of quantitative biomarkers in an efficient way. In the era of the personalized medicine, an early and efficacy prediction of therapy response in patients is still a critical issue. In radiation therapy planning, Magnetic Resonance Imaging (MRI) provides high quality detailed images and excellent soft-tissue contrast, while Computerized Tomography (CT) images provides attenuation maps and very good hard-tissue contrast. In this context, Positron Emission Tomography (PET) is a non-invasive imaging technique which has the advantage, over morphological imaging techniques, of providing functional information about the patient’s disease. In the last few years, several criteria to assess therapy response in oncological patients have been proposed, ranging from anatomical to functional assessments. Changes in tumour size are not necessarily correlated with changes in tumour viability and outcome. In addition, morphological changes resulting from therapy occur slower than functional changes. Inclusion of PET images in radiotherapy protocols is desirable because it is predictive of treatment response and provides crucial information to accurately target the oncological lesion and to escalate the radiation dose without increasing normal tissue injury. For this reason, PET may be used for improving the Planning Treatment Volume (PTV). Nevertheless, due to the nature of PET images (low spatial resolution, high noise and weak boundary), metabolic image processing is a critical task. The aim of this Ph.D thesis is to develope smart methodologies applied to the medical imaging field to analyse different kind of problematic related to medical images and data analysis, working closely to radiologist physicians. Various issues in clinical environment have been addressed and a certain amount of improvements has been produced in various fields, such as organs and tissues segmentation and classification to delineate tumors volume using meshing learning techniques to support medical decision. In particular, the following topics have been object of this study: • Technique for Crohn’s Disease Classification using Kernel Support Vector Machine Based; • Automatic Multi-Seed Detection For MR Breast Image Segmentation; • Tissue Classification in PET Oncological Studies; • KSVM-Based System for the Definition, Validation and Identification of the Incisinal Hernia Reccurence Risk Factors; • A smart and operator independent system to delineate tumours in Positron Emission Tomography scans; 3 • Active Contour Algorithm with Discriminant Analysis for Delineating Tumors in Positron Emission Tomography; • K-Nearest Neighbor driving Active Contours to Delineate Biological Tumor Volumes; • Tissue Classification to Support Local Active Delineation of Brain Tumors; • A fully automatic system of Positron Emission Tomography Study segmentation. This work has been developed in collaboration with the medical staff and colleagues at the: • Dipartimento di Biopatologia e Biotecnologie Mediche e Forensi (DIBIMED), University of Palermo • Cannizzaro Hospital of Catania • Istituto di Bioimmagini e Fisiologia Molecolare (IBFM) Centro Nazionale delle Ricerche (CNR) of Cefalù • School of Electrical and Computer Engineering at Georgia Institute of Technology The proposed contributions have produced scientific publications in indexed computer science and medical journals and conferences. They are very useful in terms of PET and MRI image segmentation and may be used daily as a Medical Decision Support Systems to enhance the current methodology performed by healthcare operators in radiotherapy treatments. The future developments of this research concern the integration of data acquired by image analysis with the managing and processing of big data coming from a wide kind of heterogeneous sources

The clinical application of PET/CT: a contemporary review

The combination of positron emission tomography (PET) scanners and x-ray computed tomography (CT) scanners into a single PET/CT scanner has resulted in vast improvements in the diagnosis of disease, particularly in the field of oncology. A decade on from the publication of the details of the first PET/CT scanner, we review the technology and applications of the modality. We examine the design aspects of combining two different imaging types into a single scanner, and the artefacts produced such as attenuation correction, motion and CT truncation artefacts. The article also provides a discussion and literature review of the applications of PET/CT to date, covering detection of tumours, radiotherapy treatment planning, patient management, and applications external to the field of oncology

The Integration of Positron Emission Tomography With Magnetic Resonance Imaging

A number of laboratories and companies are currently exploring the development of integrated imaging systems for magnetic resonance imaging (MRI) and positron emission tomography (PET). Scanners for both preclinical and human research applications are being pursued. In contrast to the widely distributed and now quite mature PET/computed tomography technology, most PET/MRI designs allow for simultaneous rather than sequential acquisition of PET and MRI data. While this offers the possibility of novel imaging strategies, it also creates considerable challenges for acquiring artifact-free images from both modalities. This paper discusses the motivation for developing combined PET/MRI technology, outlines the obstacles in realizing such an integrated instrument, and presents recent progress in the development of both the instrumentation and of novel imaging agents for combined PET/MRI studies. The performance of the first-generation PET/MRI systems is described. Finally, a range of possible biomedical applications for PET/MRI are outlined

SPECT and PET serve as molecular imaging techniques and in vivo biomarkers for brain metastases

Nuclear medicine techniques (single photon emission computerized tomography, SPECT, and positron emission tomography, PET) represent molecular imaging tools, able to provide in vivo biomarkers of different diseases. To investigate brain tumours and metastases many different radiopharmaceuticals imaged by SPECT and PET can be used. In this review the main and most promising radiopharmaceuticals available to detect brain metastases are reported. Furthermore the diagnostic contribution of the combination of SPECT and PET data with radiological findings (magnetic resonance imaging, MRI) is discussed

EPMA position paper in cancer:current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision

INVITED TALKS

On behalf of the Polish scientific community we have the privilege and pleasure to welcome youto Warsaw for the PETRAD2012 Conference. The Conference follows the opening of the Universityof Warsaw Radiopharmaceuticals Production and Research Centre. The main goal of this centreis the production of radioisotopes and radiopharmaceuticals for Positron Emission Tomography(PET) laboratories in Poland as well as research into new, innovative radiopharmaceuticals