Mathematical Modeling of Blood Flow to Evaluate the Hemodynamic Significance of Peripheral Vascular Lesions

Background: Evaluating the severity of peripheral artery lesions is challenging. Image-based blood flow modeling from peripheral Computed Tomographic Angiography (pCTA) may provide a non-invasive method to determine the hemodynamic significance of lesions. This pilot study evaluates the performance of pCTA-based blood flow modeling in diagnosing functionally significant peripheral lesions in comparison with Digital Subtraction Angiography (DSA). Methods: Ten patients undergoing DSA and pCTA were included. The peripheral arteries were divided into 8 segments per extremity and stenosis severity was graded by visual estimation from DSA. Each segment was graded 0 to IV (normal, mildly-stenotic, moderately-stenotic, severely-stenotic, occluded) or non-evaluable. Independent from DSA review, a Resting Pressure Drop (RPD) and an Exercise Pressure Drop (ExPD) for each segment was calculated from pCTA-based blood flow modeling. A functionally significant (FS) lesion was defined as grade III or IV by DSA and RPD > 5 mmHg from pCTA-based modeling. Analysis was repeated with an ExPD > 20 mmHg. Sensitivity, specificity and accuracy were calculated for RPD > 5 mmHg and ExPD > 20 mmHg using DSA as the standard. Results: Mean age was 52±16 years, 4 patients were male, 8 patients presented with critical limb ischemia, mean ankle brachial index was 0.60±0.29, and 66 arterial segments were available for both assessment methods. Twenty-two segments had FS lesions by DSA. Using an RPD > 5 mmHg, sensitivity was 80%, specificity was 85% and accuracy was 79%. Using an ExPD > 20 mmHg, sensitivity was 84%, specificity was 89% and accuracy was 88%. Conclusion: Use of a resting pressure drop > 5 mmHg and an exercise pressure drop > 20 mmHg, measured by blood flow modeling from CT angiography, can accurately identify functionally significant stenosis in patients with peripheral vascular disease. This information motivates the need for a larger-scale prospective imaging trial to further validate this novel non-invasive approach.

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Abstract 16856: Mathematical Modeling of Blood Flow to Evaluate the Hemodynamic Significance of Peripheral Vascular Lesions

Circulation ◽

10.1161/circ.142.suppl_3.16856 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Seyed Mehran Mirramezani ◽

Paul Cimadomo ◽

Ernie Ahsan ◽

David Shavelle ◽

Leonardo Clavijo ◽

...

Keyword(s):

Blood Flow ◽

Pressure Gradient ◽

Ankle Brachial Index ◽

Peripheral Arteries ◽

Flow Modeling ◽

Peripheral Vascular ◽

Blood Flow Modeling ◽

Resting Pressure ◽

Grade Iii ◽

Significant Lesion

Introduction: Evaluating the severity of lesions in peripheral arteries is challenging. Image-based blood flow modeling from peripheral computed tomographic angiography (pCTA) may provide a non-invasive method to determine the hemodynamic significance of lesions. The objective of this study was to evaluate the diagnostic performance of a trans-lesion pressure drop computed from pCTA-based blood flow modeling in the peripheral arteries. Methods: Ten patients undergoing digital subtraction angiography (DSA) and pCTA were included. The peripheral arteries were divided into 8 segments per extremity and stenosis severity was visually graded by DSA as non-stenosed (grade 0), mild (grade I), moderate (grade II), severe (grade III), occluded (grade IV) or non-evaluable. A functionally significant lesion was defined as grade III or IV by DSA. Independent from the DSA review, a resting pressure gradient (rPG) and exercise PG (ExPG) for each segment was calculated from pCTA-based blood flow modeling (Figure), and a functionally significant lesion was defined as having an rPG > 5 mm Hg or an ExPG > 20 mm Hg. Results: Mean age was 52±16 years, 4 patients (40%) were male, 8 patients (80%) presented with critical limb ischemia, mean ankle brachial index was 0.60±0.29 and 66 arterial segments were available for both assessment methods. Twenty-two segments had functionally significant lesions by DSA. For rPG, sensitivity was 80%, specificity was 85% and accuracy was 79% with DSA as the standard; for ExPG, sensitivity was 84%, specificity was 89% and accuracy was 88%. Conclusions: Use of a resting pressure gradient > 5 mm Hg and an exercise pressure gradient > 20 mm Hg measured by peripheral computed tomography-based blood flow modeling accurately identifies functionally significant stenosis in patients with advanced peripheral vascular disease. These results support a prospective imaging trial to further validate this novel approach.

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Dynamics of blood flow: modeling of the Fåhræus–Lindqvist effect

Journal of Biological Physics ◽

10.1007/s10867-015-9376-1 ◽

2015 ◽

Vol 41 (3) ◽

pp. 313-326 ◽

Cited By ~ 20

Author(s):

Rachid Chebbi

Keyword(s):

Blood Flow ◽

Flow Modeling ◽

Blood Flow Modeling

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PL - 031 Skeletal muscle blood flow determination using gold standard invasive arterial input function and non-invasive image-based input function by positron emission tomography (PET)

Exercise Biochemistry Review ◽

10.14428/ebr.v1i1.8493 ◽

2018 ◽

Vol 1 (1) ◽

Author(s):

Ilkka Heinonen ◽

Kari Kalliokoski ◽

Vesa Oikonen ◽

Christopher Mawhinney ◽

Warren Gregson ◽

...

Keyword(s):

Skeletal Muscle ◽

Blood Flow ◽

Data Analysis ◽

Arterial Input Function ◽

Muscle Blood Flow ◽

Input Function ◽

Invasive Approach ◽

Skeletal Muscle Blood Flow ◽

Non Invasive ◽

Arterial Blood

Objective Skeletal muscle is unique among organs in that its blood flow, thus oxygen supply that is critical for muscular function, can change over a remarkably large range. Compared to the rest, muscle blood flow can increase over 20-fold during intense exercise. Positron emission tomography (PET) and [15O]-H2O tracer provide a unique tool for the direct measurement of muscle blood flow in specific muscle regions. Quantification of PET blood flow requires knowledge of the arterial input function, which is usually provided by arterial blood sampling. However, arterial sampling is an invasive approach requiring arterial cannulation. In the current study, we aimed to explore the analysis and error estimation based on non-invasive, PET image-based input function for skeletal muscle blood flow in PET [15O]-labeled radiowater study. Methods Thirty healthy untrained men volunteered to participate in this study. [15O]-labeled radio water PET perfusion scans were performed at rest and right after cycling exercise. GE Discovery PET-CT scanner was used for image acquisition. The 15O isotope was produced with a Cyclone 3 cyclotron (IBA Molecular, Belgium). After 455 MBq of 15O-H2O was injected intravenously and after 20 seconds, dynamic scanning images were performed in following frames: 6x5 seconds, 12x10 seconds, 7x30 seconds and 12x10 seconds. Arterial blood was sampled continuously from radial artery during imaging for radioactivity with a detector during PET scanning. All the data analysis was performed using all in-house developed programs. Arterial input function was preprocessed with delay correction. Image-based input function was defined based on sum image of dynamic images. Blood flow was calculated using the 1-tissue compartment model, k1 is considered as blood flow without any further correction. All data analysis was performed by Carimas software (http://www.turkupetcentre.fi/carimas). Data analysis was performed in five parts: 1) Modelling data using input function from artery. 2) By defining femoral artery Volume Of Interest (VOI) on PET images. 3) Modelling data using image-based input function. 4) Calculating the correlation for blood flow between artery (blood) input function and image-based input function. 5) Predicted true blood flow was calculated based on correlation based on the initial linear relationship between blood and image-based input functions. Results Skeletal muscle blood flow had a good linear relationship calculated by femoral artery VOI and by arterial (blood) input function (y = 2,9587x - 0,096, R² = 0,8852, p<0.0001). Further, by using the prediction equation obtained by the linear relationship between VOI-determined (femoral) artery blood flow and direct gold standard (radial) artery input function determined blood flow, image-based input function determined blood flow was well predicted using this non-invasive approach (y = 1,1812x + 0,1219, R² = 0,9259, p<0.0001). Conclusions It is concluded that there is a strong linear correlation between gold standard invasive approach and non-invasive image-based approach to measure skeletal muscle blood flow by PET, but if no further corrections are made, image-based approach overestimates correct blood flow. However, this can be corrected by linear prediction equation, suggesting that invasive arterial input function may not always be needed in the future when measuring skeletal muscle blood flow by PET. This will be of benefit particularly for exercise studies.

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