CT dose optimization with model based iterative reconstruction

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dc.contributor.advisor Maher, Michael M. en
dc.contributor.advisor O'Connor, Owen en
dc.contributor.author Moloney, Fiachra
dc.date.accessioned 2019-04-09T11:43:02Z
dc.date.available 2019-04-09T11:43:02Z
dc.date.issued 2019
dc.date.submitted 2019
dc.identifier.citation Moloney, F. G. 2019. CT dose optimization with model based iterative reconstruction. MD Thesis, University College Cork. en
dc.identifier.endpage 192 en
dc.identifier.uri http://hdl.handle.net/10468/7728
dc.description.abstract The aim of this thesis is to assess the feasibility of using model-based iterative reconstruction (MBIR) to develop new low-dose CT (computed tomography) protocols in the areas of neck, chest, and abdominal imaging without compromising diagnostic performance. Medical imaging has become the largest source of radiation exposure for humans other than natural background radiation. The availability of and improvements in diagnostic imaging have led to a sevenfold increase in the use of imaging over the past 30 years. This is especially true for CT, with a 7.8% annual increase in the use of CT from 1996 to 2010. The major concern associated with the widespread uptake of CT is the parallel increase in radiation exposure incurred by patients, and while the relationship of diagnostic radiation exposure to a quantifiable risk of cancer induction remains a controversial topic, physicians are beholden to keep radiation doses from diagnostic imaging as low as reasonably possible to limit the risk of radiation-induced cancer. We conducted preliminary phantom and cadaveric studies to examine the performance of MBIR at different radiation dose levels in the thorax and abdomen. Cadavers and phantoms provide a means of safely assessing new technologies and optimizing scan protocols prior to clinical validation. An anthropomorphic torso phantom and 5 human cadavers were scanned at varying radiation dose levels and images reconstructed using three different reconstruction techniques: filtered back projection, hybrid IR and MBIR. MBIR reduced image noise and improved image quality even in CT images acquired with a mean radiation dose reduction of 62%, compared with conventional dose studies reconstructed with hybrid IR, with lower levels of objective image noise, superior diagnostic acceptability and contrast resolution, and comparable subjective image noise and streak artifact scores. We subsequently performed clinical studies with the objectives of assessing MBIR as a tool for image quality improvement and radiation dose reduction in CT, and for the development of new low-dose carotid angiography, chest, and abdominopelvic CT protocols. We developed a low-dose carotid CTA protocol reconstructed with MBIR comparable to a conventional dose CTA protocol in terms of image quality and diagnostic accuracy while enabling a dose reduction of 49.6%. 20 patients were scanned using a split-dose technique with radiation dose divided into a low-dose acquisition reconstructed with MBIR and a conventional dose acquisition reconstructed with hybrid IR. Mean effective dose was significantly lower for the low-dose studies (1.84mSv versus 3.71mSv) and subjective image noise, contrast resolution, and spatial resolution were significantly higher for the low-dose studies. There was excellent agreement for stenosis grading accuracy between low- and conventional dose studies (Cohen κ = 0.806). A modified low-dose CT thorax protocol reconstructed with MBIR was also developed to monitor pulmonary disease progression in patients with cystic fibrosis with our low-dose protocol enabling the acquisition of a full-volume diagnostic quality chest CT at a dose equivalent to that of a chest radiograph (0.09±0.01mSv). Finally, we assessed the feasibility of low-dose abdominopelvic CT performed with MBIR as a radiation dose reduction strategy for imaging patients presenting with acute abdominal pain. A 74.7% mean radiation dose reduction was achieved with scans performed in the peri- and submillisievert range in patients of normal and low BMI, respectively, without compromising diagnostic performance. Dose reduction to the submillisievert range for patients with an elevated BMI was a challenge. The current era is extremely exciting in terms of radiation dose optimization in CT. This thesis is a demonstration of the potential for substantial reductions in radiation exposure, when the benefits of iterative reconstruction are combined with automated tube current modulation and other CT scanner technologies. The combination of all these hardware and software developments is now seeing major benefits for the patient and moving beyond the narrow aim of radiation exposure reduction to a complete change in practice, towards replacement of conventional radiography with low-dose CT, without any penalty for the patient in terms of radiation exposure. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher University College Cork en
dc.rights © 2019, Fiachra Moloney. en
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/ en
dc.subject Computed tomography en
dc.subject Iterative reconstruction en
dc.subject Acute abdomen en
dc.subject Ionizing radiation en
dc.subject Radiation dose en
dc.title CT dose optimization with model based iterative reconstruction en
dc.type Masters thesis (Research) en
dc.type.qualificationlevel Doctoral en
dc.type.qualificationname MD en
dc.internal.availability Full text available en
dc.check.info Not applicable en
dc.description.version Accepted Version
dc.description.status Not peer reviewed en
dc.internal.school Medicine en
dc.check.type No Embargo Required
dc.check.reason Not applicable en
dc.check.opt-out No en
dc.thesis.opt-out false
dc.check.embargoformat Embargo not applicable (If you have not submitted an e-thesis or do not want to request an embargo) en
ucc.workflow.supervisor m.maher@ucc.ie
dc.internal.conferring Spring 2019 en
dc.internal.ricu HRB Clinical Research Facility at UCC en

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© 2019, Fiachra Moloney. Except where otherwise noted, this item's license is described as © 2019, Fiachra Moloney.
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