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Large variation in blood flow between left ventricular segments, as detected by adenosine stress dynamic CT perfusion.
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Cardiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Department of Clinical Physiology in Kalmar, Linköping University, County Council of Kalmar, Kalmar, Sweden.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
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2015 (English)In: Clinical Physiology and Functional Imaging, ISSN 1475-0961, E-ISSN 1475-097X, Vol. 35, no 4, 291-300 p.Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Dynamic cardiac CT perfusion (CTP) is based on repeated imaging during the first-pass contrast agent inflow. It is a relatively new method that still needs validation.

PURPOSE: To evaluate the variation in adenosine stress dynamic CTP blood flow as compared to (99m) Tc SPECT. Secondarily, to compare manual and automatic segmentation.

METHODS: Seventeen patients with manifest coronary artery disease were included. Nine were excluded from evaluation for various reasons. All patients were examined with dynamic stress CTP and stress/rest SPECT. CTP blood flow was compared with SPECT on a per segment basis. Results for manual and automated AHA segmentation were compared.

RESULTS: CTP showed a positive correlation with SPECT, with correlation coefficients of 0·38 and 0·41 for manual and automatic segmentation, respectively (P<0·0001). There was no significant difference between the correlation coefficients of the manual and automated segmentation procedures (P = 0·75). The average per individual global CTP blood flow value for normal segments varied by a factor of 1·9 (manual and automatic segmentation). For the whole patient group, the CTP blood flow value in normal segments varied by a factor of 2·9/2·7 (manual/automatic segmentation). Within each patient, the average per segment blood flow in normal segments varied by a factor of 1·3-2·0/1·2-2·1 (manual/automatic segmentation).

CONCLUSION: A positive but rather weak correlation was found between CTP and (99m) Tc SPECT. Large variations in CTP blood flow suggest that a cut-off value for stress myocardial blood flow is inadequate to detect ischaemic segments. Dynamic CTP is hampered by a limited coverage.

Place, publisher, year, edition, pages
2015. Vol. 35, no 4, 291-300 p.
National Category
Clinical Medicine
Identifiers
URN: urn:nbn:se:liu:diva-113400DOI: 10.1111/cpf.12163ISI: 000356312800007PubMedID: 24842265OAI: oai:DiVA.org:liu-113400DiVA: diva2:781623
Available from: 2015-01-17 Created: 2015-01-17 Last updated: 2017-12-05
In thesis
1. On the use of computed tomography in cardiac imaging
Open this publication in new window or tab >>On the use of computed tomography in cardiac imaging
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background

Cardiac Computed Tomography Angiography (CCTA) is becoming increasingly useful in the work‐up of coronary artery disease (CAD). Several potential methods for increasing the diagnostic yield of cardiac CT are available.

Purpose

Study I: To investigate whether the use of a 2‐D, non‐linear adaptive noise reduction filter can improve CCTA image quality.

Study II: To evaluate the variation in adenosine stress dynamic CT perfusion (CTP) blood flow as compared to stress 99mTc SPECT. Secondly, to compare the perfusion results from manual and automatic myocardial CTP segmentation.

Study III: To evaluate the accuracy of non‐invasive, CCTA‐derived Fractional Flow Reserve (cFFR).

Study IV: To evaluate the prognostic value of CCTA in terms of major adverse cardiac events (MACE).

Materials and methods

Study I: Single images from 36 consecutive CCTA exams performed with two different dose levels were used. Image quality in full dose, low‐dose and noise‐reduced low‐dose images was graded using visual grading analysis. Image noise was measured.

Study II: CTP and SPECT were performed in 17 patients, and the variation in per AHA‐segment blood flow was evaluated and compared. CTP results from manual and automated image segmentation were compared.

Study III: CCTA datasets from 21 patients were processed using cFFR software and the results compared to the corresponding invasively measured FFR (invFFR).

Study IV: 1205 consecutive patients with chest pain of unknown origin underwent CCTA. Baseline data and data on subsequent MACE were retrieved from relevant registries. Survival, hazard ratios and the three‐year incidence of cardiac events and readmissions were calculated.

Results

Study I: There was significant improvement in perceived image quality for all criteria when the filter was applied, and a significant decrease in image noise.

Study II: The correlation coefficients for CTP vs. SPECT were 0.38 and 0.41 (p<0.001, for manual and automated segmentation respectively. Mean per patient CTP blood flow in normal segments varied between 94‐183 ml/100 ml tissue/min for manual segmentation, and 104‐196 ml/100 ml tissue/min for automated segmentation. The Spearman rank correlation coefficient for manual vs. automated segmentation CTP was ρ = 0.88 (p<0.001) and the Intraclass Correlation Coefficient (ICC) was 0.93 (p<0.001).

Study III: The Spearman rank correlation coefficient for cFFR vs. invFFR was ρ = 0.77 (p<0.001) and the ICC was 0.73 (p<0.001). Sensitivity, specificity, positive predictive value and negative predictive value for significant stenosis (FFR<0.80, per vessel) were 0.83, 0.76, 0.56 and 0.93 respectively.

Study IV: The hazard ratio for non‐obstructive CAD vs. normal coronary arteries was 5.13 (95% C.I 1.03‐25.43, p<0.05), and 151.40 (95% C.I 37.03‐619.08, p<0.001) for obstructive CAD vs. normal coronary arteries. The three‐year incidence of MACE was 1.1% for patients with normal vessels on CCTA, 2.5% for patients with non‐obstructive CAD and 42.7% for patients with obstructive CAD (p<0.001).

Conclusions:

Study I: Image quality and noise levels of low dose images were significantly improved with the filter, even though the improvement was small compared to the image quality of the corresponding diastolic full‐dose images.

Study II: Correlation between dynamic CTP and SPECT was positive but weak. There were large variations in CTP blood flow in normal segments on SPECT, rendering the definition of an absolute cut‐off value for normal vs. ischemic myocardium difficult. Manual and automatic segmentation were equally useful.

Study III: The correlation between cFFR and invFFR was good, indicating that noninvasively estimated cFFR performs on a similar level as invasively measure FFR.

Study IV: The long‐term risk for MACE was very low in patients without obstructive CAD on CCTA, though there seemed to be a substantial increase in the risk for MACE even in patients with non‐obstructive CAD as compared to normal coronary arteries. In addition, even patients with normal coronary arteries or non‐obstructive CAD continued to have a substantial number of readmissions for chest pain or angina pectoris.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2016. 73 p.
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1518
National Category
Radiology, Nuclear Medicine and Medical Imaging Medical Image Processing Cardiac and Cardiovascular Systems
Identifiers
urn:nbn:se:liu:diva-128276 (URN)10.3384/diss.diva-128276 (DOI)978-91-7685-795-3 (ISBN)
Public defence
2016-06-09, Berzeliussalen, ingång 65, plan, 9, Campus US, Linköping, 09:00 (Swedish)
Opponent
Supervisors
Funder
Region ÖstergötlandSwedish Heart Lung Foundation, 20120449
Available from: 2016-05-24 Created: 2016-05-24 Last updated: 2016-05-25Bibliographically approved

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De Geer, JakobGjerde, MarcusBrudin, LarsOlsson, EvaPersson, AndersEngvall, Jan

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