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Introduction
Published in A Stewart Whitley, Jan Dodgeon, Angela Meadows, Jane Cullingworth, Ken Holmes, Marcus Jackson, Graham Hoadley, Randeep Kumar Kulshrestha, Clark’s Procedures in Diagnostic Imaging: A System-Based Approach, 2020
A Stewart Whitley, Jan Dodgeon, Angela Meadows, Jane Cullingworth, Ken Holmes, Marcus Jackson, Graham Hoadley, Randeep Kumar Kulshrestha
Technology continues to evolve rapidly in the arena of hybrid imaging, with PET scanning systems capable of TOF imaging and the supporting CT technology capable of more complex imaging techniques such as cardiac PET–CT. It is important to note that rarely is the term PET used singularly as PET–CT is now common place. At the time of writing, PET–MRI is also an evolving technology; this has a particular focus in neurology imaging of the brain, and many research centres are working with new tracers in the development of imaging in this field.
Recent Advances in Technology
Published in John C Watkinson, Raymond W Clarke, Louise Jayne Clark, Adam J Donne, R James A England, Hisham M Mehanna, Gerald William McGarry, Sean Carrie, Basic Sciences Endocrine Surgery Rhinology, 2018
Integrated PET-MRI is an emerging technology, a development of registering PET with MRI obtained from different scanners.95 Combining PET with MRI for assessment of H&N cancer is an area of considerable interest because MRI is often performed as a complement to PET-CT in the assessment of H&N cancer. The added value of PET-MRI compared with separate PET-CT and MRI scanning has yet to be fully evaluated. Beyond a significantly lower dose of ionizing radiation, the advantage of PET-MRI as an alternative to PET-CT is unclear. A pilot study of 25 patients designed to evaluate the accuracy of FDG PET-MR for loco-regional tumour evaluation compared to FDG PET-CT and MRI in initial tumour and recurrence diagnosis in histo-pathologically confirmed H&N SqCC found no significant differences were observed in T and N staging among the three modalities. In 13 patients undergoing hybrid imaging for cancer recurrence diagnosis, diagnostic accuracy was 57% with MRI and 72% with FDG PET-CT and FDG PET-MRI, respectively.96 In a study designed to evaluate and compare the diagnostic potential of FDG PET-MRI to FDG PET-CT for people with cancer of unknown primary a total of 20 patients underwent a dedicated head and neck and whole-body FDG PET-CT and subsequent simultaneous FDG PET-MRI. Both hybrid imaging techniques provide a comparable diagnostic ability for detection of primary cancer and metastases, with comparably high-lesion conspicuity and diagnostic confidence, offering superior assessment of cervical lesions in PET-MRI and potentially of pulmonary lesions in PET-CT.97
Integrated PET and MRI of the heart
Published in Yi-Hwa Liu, Albert J. Sinusas, Hybrid Imaging in Cardiovascular Medicine, 2017
Ciprian Catana, David E. Sosnovik
First attempts to characterize the respiratory motion in the context of PET-MRI have focused on the abdomen (Guerin et al. 2011). This is not surprising because this is a region of the body where the effects of respiratory motion can be largely disentangled from those of cardiac motion. Simple techniques (e.g., respiratory bellows, 1-D MR navigators for monitoring the position of the diaphragm, etc.) are currently used for respiratory gating in PET and MRI studies performed on stand-alone instruments. However, although these methods are useful for deriving a respiratory signal, they are clearly not sufficient for completely characterizing nonrigid organ deformations that accompany respiratory motion and more advanced MR techniques have been proposed for this purpose, such as phase contrast MRI, tagged-MRI, displacement encoding with stimulated echoes, and harmonic phase imaging (HARP) (Ozturk, Derbyshire, and McVeigh 2003).
Comparing different CT, PET and MRI multi-modality image combinations for deep learning-based head and neck tumor segmentation
Published in Acta Oncologica, 2021
Jintao Ren, Jesper Grau Eriksen, Jasper Nijkamp, Stine Sofia Korreman
By including MRI, CT-PET-MRI gave higher median values (0.77) than CT-PET (0.74) in terms of Dice, but the average scores were not improved. CT-PET-MRI’s median recall score (0.69) had a significant drop compared to CT-PET (0.77), indicating that in some cases, CT-PET-MRI predicts more FN compared to CT-PET (Figure 3(E)). The superior soft-tissue contrast provided by MRI improves the HD95 in some cases (Figure 3(C)). PET-MRI combination gave comparable results to CT-PET, demonstrating that MRI provides an equally good contribution to CT when in combination with PET. The MSD results suggest that all three PET including combinations have similar general surface distance toward the ground truth. Overall, the CT-PET-MRI combination input did not perform as well as we had expected. The underachievement could caused by the employed deep learning pipeline not being capable of learning the underlying information from all multi-modalities at once. It’s also plausible that MRI doesn’t carry extra credibility than CT-PET in clinically delineated GTV ground truth.
Non-invasive imaging techniques to assess myocardial perfusion
Published in Expert Review of Medical Devices, 2020
Olivier Villemain, Jérôme Baranger, Zakaria Jalal, Christopher Lam, Jérémie Calais, Mathieu Pernot, Barbara Cifra, Mark K. Friedberg, Luc Mertens
Ultimately, it seems intuitive to say that the next generation of imaging for myocardial perfusion analysis will be hybrid (or fusion) techniques combining several techniques and combining their strengths. The CT-SPECT combination (Figure 5) is one possible example, as is the Ultrasound-PET combination. Since 2010, hybrid PET/MRI using sequential and integrated scanner platforms has been available, with hybrid cardiac PET/MR imaging protocols increasingly incorporated into clinical workflows. Given the range of complementary information provided by each method, the use of hybrid PET/MRI may be justified and beneficial in particular clinical settings for the evaluation of different disease entities. Indeed, as summarized in this Review paper, each technique has its inherent limitations in the underlying physics. But being able to combine the advantages of each would allow research and medical teams to go further in the analysis of myocardial perfusion. Through the development of other technologies, such as machine learning, automatic image analysis, or potential robotization (for the automatic performance of echocardiography), the association and combination of imaging techniques will become more accessible and reliable.
Quantitative analysis of 18-FDG-PET/MRI to assess pathological complete response following neoadjuvant radiochemotherapy in locally advanced rectal cancer. A prospective preliminary study
Published in Acta Oncologica, 2019
Valentina Ferri, Emilio Vicente Lopez, Yolanda Quijano Collazo, Riccardo Caruso, Hipolito Duran Gimenez Rico, Benedetto Ielpo, Eduardo Diaz Reques, Isabel Fabra Cabrera, Luis Malavè Cardozo, Roberta Isernia, Eva Pinna, Carlos Plaza Hernandezv, Marjorie Garcerant, Lina Garcia Cañamaques, Virgina Perez Dueñas
Pathologic complete response (pCR) is observed in 8–24% of the cases of patients with locally advanced rectal cancer (LARC) treated with neoadjuvant radiochemotherapy (RCT) before curative surgery [1,2]. Accurate restaging modalities after RCT are of paramount importance to be able to individualize the most appropriate treatment, as preserving surgical techniques can be offered to selected patients [3]. In the literature, MRI with diffusion (DWI) protocol is proven to be the most accurate imaging technique to assess local therapy response [4] and to restage patients with colorectal cancer [5]. FDG-PET/CT has been shown to improve the accuracy of malignant lymph node detection compared with CT and MRI [6]. However, no definite consensus on optimal imaging modality has yet been established, and more specific and sensitive methods are needed [7,8]. In recent years 18-FDG-PET/MRI has emerged as a new imaging technique that combines simultaneous positron emission tomography. MRI can add anatomic and quantitative strengths of MR imaging to physiologic information obtained from PET [9–11].