Automatic detection of misleading blood flow values in CT perfusion studies of lung cancer. (April 2016)
- Record Type:
- Journal Article
- Title:
- Automatic detection of misleading blood flow values in CT perfusion studies of lung cancer. (April 2016)
- Main Title:
- Automatic detection of misleading blood flow values in CT perfusion studies of lung cancer
- Authors:
- Bevilacqua, Alessandro
Barone, Domenico
Malavasi, Silvia
Gavelli, Giampaolo - Abstract:
- Abstract : Highlights: CT perfusion (CTp) is a promising technique to assess anti-angiogenic therapies. Patient motion and CTp artefacts prevent reliable quantitative measurements. An adaptive thresholding of goodness-of-fit errors histogram is proposed. Voxels with high fitting errors correspond to vessel, bronchi and artefacts. These misleading voxels are removed and the CTp maps increase their reliability. Abstract: In the oncology field, the anti-angiogenetic therapies aim at inhibiting tumour vascularization, that is the development of new capillary blood vessels in tumours, that allows them to grow and spread and, potentially, to metastasi. Computed tomography perfusion (CTp) is a dynamic contrast-enhanced technique that has emerged in the last few years as a promising approach for earlier assessment of such therapies, and of tumour response, in general, since functional changes precede morphological changes, that take more time to become evident. However several issues, such as patient motion and several types of artefacts, jeopardize quantitative measurements, this preventing CTp to be used in standard clinics. This paper presents an original automatic approach, based on the voxel-based analysis of the time–concentration curves (TCCs), that allows emphasizing those physiological structures, such as vessels, bronchi or artefacts, that could affect the final computation of blood flow perfusion values in CTp studies of lung cancer. The automatic exclusion of theseAbstract : Highlights: CT perfusion (CTp) is a promising technique to assess anti-angiogenic therapies. Patient motion and CTp artefacts prevent reliable quantitative measurements. An adaptive thresholding of goodness-of-fit errors histogram is proposed. Voxels with high fitting errors correspond to vessel, bronchi and artefacts. These misleading voxels are removed and the CTp maps increase their reliability. Abstract: In the oncology field, the anti-angiogenetic therapies aim at inhibiting tumour vascularization, that is the development of new capillary blood vessels in tumours, that allows them to grow and spread and, potentially, to metastasi. Computed tomography perfusion (CTp) is a dynamic contrast-enhanced technique that has emerged in the last few years as a promising approach for earlier assessment of such therapies, and of tumour response, in general, since functional changes precede morphological changes, that take more time to become evident. However several issues, such as patient motion and several types of artefacts, jeopardize quantitative measurements, this preventing CTp to be used in standard clinics. This paper presents an original automatic approach, based on the voxel-based analysis of the time–concentration curves (TCCs), that allows emphasizing those physiological structures, such as vessels, bronchi or artefacts, that could affect the final computation of blood flow perfusion values in CTp studies of lung cancer. The automatic exclusion of these misleading values represents a step towards a quantitative CTp, hence its routine use in clinics. … (more)
- Is Part Of:
- Biomedical signal processing and control. Volume 26(2016)
- Journal:
- Biomedical signal processing and control
- Issue:
- Volume 26(2016)
- Issue Display:
- Volume 26, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 26
- Issue:
- 2016
- Issue Sort Value:
- 2016-0026-2016-0000
- Page Start:
- 109
- Page End:
- 116
- Publication Date:
- 2016-04
- Subjects:
- Quantitative imaging -- Error analysis -- Image processing -- Imaging artefacts -- Cancer
Signal processing -- Periodicals
Biomedical engineering -- Periodicals
Signal Processing, Computer-Assisted -- Periodicals
Image Processing, Computer-Assisted -- Periodicals
Biomedical Engineering -- Periodicals
610.28 - Journal URLs:
- http://www.sciencedirect.com/science/journal/17468094 ↗
http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%2329675%232006%23999989998%23626449%23FLA%23&_cdi=29675&_pubType=J&_auth=y&_acct=C000045259&_version=1&_urlVersion=0&_userid=836873&md5=664b5cf9a57fc91971a17faf20c32ec1 ↗ - DOI:
- 10.1016/j.bspc.2016.01.004 ↗
- Languages:
- English
- ISSNs:
- 1746-8094
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2087.880400
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
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