Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.
Objectives: The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated construction of patient-specific computational phantoms b...
| Published in: | European Radiology Vol. 29; no. 12; pp. 6805 - 6816 |
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| Main Authors: | , |
| Format: | Journal Article |
| Published: |
Springer Nature
Dec2019
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139479384&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139479384 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Dec2019 vid: 29 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 139479384 139479384 NLM31227881 10.1007/s00330-019-06296-4 NLM31227881 139479384 ppf: 6805 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks. aug: au: Xie, Tianwu Zaidi, Habib affil: Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland sug: subj: Radiography, Abdominal Statistics and Numerical Data Radiation Dosage Tomography, X-Ray Computed Statistics and Numerical Data Tomography, X-Ray Computed Methods Young Adult Female Radiometry Methods Adult Phantoms, Imaging Middle Age Systems Analysis Pregnancy Radiography, Abdominal Methods Computer Simulation Scales Adult: 19-44 years Middle Aged: 45-64 years Female ab: Objectives: The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated construction of patient-specific computational phantoms based on actual patient CT images to enable accurate estimation of conceptus dose.Methods: We developed a 3D deep convolutional network algorithm for automated segmentation of CT images to build realistic computational phantoms. The neural network architecture consists of analysis and synthesis paths with four resolution levels each, trained on manually labeled CT scans of six identified anatomical structures. Thirty-two CT exams were augmented to 128 datasets and randomly split into 80%/20% for training/testing. The absorbed doses for six segmented organs/tissues from abdominal CT scans were estimated using Monte Carlo calculations. The resulting radiation doses were then compared between the computational models generated using automated segmentation and manual segmentation, serving as reference.Results: The Dice similarity coefficient for identified internal organs between manual segmentation and automated segmentation results varies from 0.92 to 0.98 while the mean Hausdorff distance for the uterus is 16.1 mm. The mean absorbed dose for the uterus is 2.9 mGy whereas the mean organ dose differences between manual and automated segmentation techniques are 0.07%, - 0.45%, - 1.55%, - 0.48%, - 0.12%, and 0.28% for the kidney, liver, lung, skeleton, uterus, and total body, respectively.Conclusion: The proposed methodology allows automated construction of realistic computational models that can be exploited to estimate patient-specific organ radiation doses from radiological imaging procedures.Key Points: • The conceptus dose during diagnostic radiology and nuclear medicine imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. • The proposed methodology allows automated construction of realistic computational models that can be exploited to estimate patient-specific organ radiation doses from radiological imaging procedures. • The dosimetric results can be used for the risk-benefit analysis of radiation hazards to conceptus from diagnostic imaging procedures, thus guiding the decision-making process. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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