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The Effect of Limiting the Scan Range of Computed Tomography Pulmonary Angiography (to Reduce Radiation Exposure) on the Detection of Pulmonary Embolism: A Systematic Review.

ABSTRACT: (1) Background: Computed tomography pulmonary angiography (CTPA) is the standard imaging test for the evaluation of acute pulmonary embolism (PE), but it is associated with patients' exposure to radiation. Studies have suggested that radiation exposure can be reduced without compromising PE detection by limiting the scan range (the z-axis, going from up to down); (2) Methods: A literature search was conducted in MEDLINE and EMBASE on 17 July 2021. Studies were included if they enrolled patients who had undergone a CTPA and described the yield of PE diagnoses, number of missed filling defects and/or other diagnoses using a reduced z-axis in comparison to a full-length scan. To assess risk of bias, we modified an existing risk of bias tools for observational studies, the Newcastle-Ottawa Scale. Results were synthesized in a narrative review. Primary outcomes were the number of missed PE diagnoses (based on at least one filling defect) and filling defects; the secondary outcome was the number of other missed findings; (3) Results: Eleven cohort studies and one case-control study were included reporting on a total of 3955 scans including 1025 scans with a diagnosis of PE. Six different reduced scan ranges were assessed; the most studied was from the top of the aortic arch to below the heart, in which no PEs were missed (seven studies). One sub-segmental PE was missed when the scan coverage was 10 cm starting from the bottom of the aortic arch and 14.7 cm starting from the top of the arch. Five studies that reported on other findings all found that other diagnoses were missed with a reduced z-axis. Most of the included studies had a high risk of bias; (4) Conclusions: CTPA scan coverage reduction from the top of aortic arch to below the heart reduced radiation exposure without affecting PE diagnoses, but studies were generally at high risk of bias.

SUBMITTER: Zaw A

PROVIDER: S-EPMC8700432 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesCardiac computed tomography (CT) is essential in diagnosing coronary heart disease. However, a disadvantage is the associated radiation exposure to the patient which depends in part on the scan range. This study aimed to develop a deep neural network to optimize the delimitation of scan ranges in CT localizers to reduce the radiation dose.MethodsOn a retrospective training cohort of 1507 CT localizers randomly selected from calcium scoring and angiography scans and acquired between 2010 and 2017, optimized scan ranges were delimited by two radiologists in consensus. A neural network was trained to reproduce the scan ranges and was tested on two randomly selected and independent validation cohorts: an internal cohort of 233 CT localizers (January 2018-June 2020) and an external cohort from a nearby hospital of 298 CT localizers (July 2020-December 2020). Localizers where a bypass surgery was visible were excluded. The effective radiation dose to the patient was simulated using a Monte Carlo simulation. Scan ranges of radiographers, radiologists, and the network were compared using an equivalence test; likewise, the reduction in effective dose was tested using a superior test.ResultsThe network replicated the radiologists' scan ranges with a Dice score of 96.5 ± 0.02 (p < 0.001, indicating equivalence). The generated scan ranges resulted in an effective dose reduction of 10.0% (p = 0.002) in the internal cohort and 12.6% (p < 0.001) in the external cohort compared to the scan ranges delimited by radiographers in clinical routine.ConclusionsAutomatic delimitation of the scan range can result in a radiation dose reduction to the patient.Clinical relevance statementFully automated delimitation of the scan range using a deep neural network enables a significant reduction in radiation exposure during CT coronary angiography compared to manual examination planning. It can also reduce the workload of the radiographers.Key points• Scan range delimitation for coronary computed tomography angiography could be performed with high accuracy by a deep neural network. • Automated scan ranges showed a high agreement of 96.5% with the scan ranges of radiologists. • Using a Monte Carlo simulation, automated scan ranges reduced the effective dose to the patient by up to 12.6% (0.9 mSv) compared to the scan ranges of radiographers in clinical routine.

Dataset Information

The Effect of Limiting the Scan Range of Computed Tomography Pulmonary Angiography (to Reduce Radiation Exposure) on the Detection of Pulmonary Embolism: A Systematic Review.

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