The effect of lung deformation on the spatial distribution of pulmonary blood flow

Arai, Tatsuya; Theilmann, Rebecca J.; Sá, Rui Carlos; Villongco, Michael T.; Hopkins, Susan R.

doi:10.1113/jp272030

Cited by 6 publications

(7 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For healthy volunteers, the respiratory index α global (which is a measure of the change in lung perfusion during the breathing cycle; see “Theory” section) was, on average, 1.02 ± 0.07, in accordance with literature results (data elaborated from , α global = 1.04). Interestingly, α global appears to be different for male and female (on average 1.07 and 0.95, respectively), but a larger collective of volunteers would be required for conclusive results.…”

Section: Discussionsupporting

confidence: 87%

“…The premise of Equation [] has already been assumed by other ventilation‐weighted imaging techniques and is corroborated by recent findings that show a non‐statistically significant pulmonary perfusion change over the whole lung and no significant lobar perfusion redistribution for breath‐holds in the tidal volume region. As a result, the respiratory index

α_{local} (\overset{x}{true})

reflects virtually lung ventilation and is independent of the lung density (see Eq.…”

Section: Theorysupporting

confidence: 67%

“…[]), we therefore find for the global respiratory index

α_{global} (V_{0}) \approx - {\frac{\partial \log (\bar{ρ} (V))}{\partial \log (V)} |}_{V = V_{0}} = 1 - \frac{V_{0}}{M_{0}} \cdot {\frac{\partial M_{blood}}{\partial V} |}_{V = V_{0}}

where the second term reflects the change in whole pulmonary blood mass as a function of the whole lung volume change (note,

\frac{V_{0}}{M_{0}}

is simply a scaling factor and

M_{0} ≔ M (V_{0})

). Simulations indicate that

α_{global}

is almost independent of the breathing position,

V_{0}

, that is,

| 1 - \frac{α_{global} (V + δ V)}{α_{global} (V - δ V)} | < 0.03

for variations up to

δ V = \frac{V_{0}}{6}

(tidal breathing, e.g., 2.4 ± 0.4 L), and

| \frac{\partial M_{blood}}{\partial V} | < 0.25 \cdot \frac{M_{0}}{V_{0}}

(value elaborated from assuming healthy tissues and

M_{tissue} = M_{blood} (V_{0})

).…”

Section: Theorymentioning

confidence: 99%

“…In a simple dry sponge model in which the sponge mass is constant, the signal intensity (SI) is inversely proportional to the lung volume V:

SI (V) = Λ \cdot V^{- 1} + η

where

Λ

is a signal intensity scaling factor (related to parenchymal “mass”), and

η

is the SI in the limit of infinite volume (i.e., noise). The assumption of mass preservation in the dry sponge model, however, is not precise enough to model the lung mechanics as a result of physiological changes, such as the variability of blood volume during breathing , or because of ventilation inhomogeneities or regional abnormalities. As a result, Equation [] needs to be modified to take the form

SI (V) = Λ \cdot V^{- α} + η

where α is the respiratory index, which maps lung expansion and changes in pulmonary blood volume during breathing.…”

Section: Theorymentioning

confidence: 99%

See 3 more Smart Citations

Rapid 3D in vivo 1H human lung respiratory imaging at 1.5 T using ultra‐fast balanced steady‐state free precession

Pusterla

Bauman

Wielpütz

et al. 2016

Magnetic Resonance in Med

View full text Add to dashboard Cite

show abstract

Section: Discussionsupporting

confidence: 87%

α_{local} (\overset{x}{true})

reflects virtually lung ventilation and is independent of the lung density (see Eq.…”

Section: Theorysupporting

confidence: 67%

“…[]), we therefore find for the global respiratory index

α_{global} (V_{0}) \approx - {\frac{\partial \log (\bar{ρ} (V))}{\partial \log (V)} |}_{V = V_{0}} = 1 - \frac{V_{0}}{M_{0}} \cdot {\frac{\partial M_{blood}}{\partial V} |}_{V = V_{0}}

where the second term reflects the change in whole pulmonary blood mass as a function of the whole lung volume change (note,

\frac{V_{0}}{M_{0}}

is simply a scaling factor and

M_{0} ≔ M (V_{0})

). Simulations indicate that

α_{global}

is almost independent of the breathing position,

V_{0}

, that is,

| 1 - \frac{α_{global} (V + δ V)}{α_{global} (V - δ V)} | < 0.03

for variations up to

δ V = \frac{V_{0}}{6}

(tidal breathing, e.g., 2.4 ± 0.4 L), and

| \frac{\partial M_{blood}}{\partial V} | < 0.25 \cdot \frac{M_{0}}{V_{0}}

(value elaborated from assuming healthy tissues and

M_{tissue} = M_{blood} (V_{0})

).…”

Section: Theorymentioning

confidence: 99%

“…In a simple dry sponge model in which the sponge mass is constant, the signal intensity (SI) is inversely proportional to the lung volume V:

SI (V) = Λ \cdot V^{- 1} + η

where

Λ

is a signal intensity scaling factor (related to parenchymal “mass”), and

η

SI (V) = Λ \cdot V^{- α} + η

where α is the respiratory index, which maps lung expansion and changes in pulmonary blood volume during breathing.…”

Section: Theorymentioning

confidence: 99%

See 2 more Smart Citations

Rapid 3D in vivo 1H human lung respiratory imaging at 1.5 T using ultra‐fast balanced steady‐state free precession

Pusterla

Bauman

Wielpütz

et al. 2016

Magnetic Resonance in Med

View full text Add to dashboard Cite

show abstract

“…Assuming that the distortion presented in the field would manifest itself as a continuous function without any local rapid changes in such small volume [ 30 – 32 ], a global transformation could properly describe the field distortion and generate the correction factors for scanning protocols. Affine transformation with 3D cubic b-spline interpolation was implemented in the study [ 33 ].…”

Section: Methodsmentioning

confidence: 99%

MR-CBCT image-guided system for radiotherapy of orthotopic rat prostate tumors

et al. 2018

Self Cite

View full text Add to dashboard Cite

Multi-modality image-guided radiotherapy is the standard of care in contemporary cancer management; however, it is not common in preclinical settings due to both hardware and software limitations. Soft tissue lesions, such as orthotopic prostate tumors, are difficult to identify using cone beam computed tomography (CBCT) imaging alone. In this study, we characterized a research magnetic resonance (MR) scanner for preclinical studies and created a protocol for combined MR-CBCT image-guided small animal radiotherapy. Two in-house dual-modality, MR and CBCT compatible, phantoms were designed and manufactured using 3D printing technology. The phantoms were used for quality assurance tests and to facilitate end-to-end testing for combined preclinical MR and CBCT based treatment planning. MR and CBCT images of the phantoms were acquired utilizing a Varian 4.7 T scanner and XRad-225Cx irradiator, respectively. The geometry distortion was assessed by comparing MR images to phantom blueprints and CBCT. The corrected MR scans were co-registered with CBCT and subsequently used for treatment planning. The fidelity of 3D printed phantoms compared to the blueprint design yielded favorable agreement as verified with the CBCT measurements. The geometric distortion, which varied between -5% and 11% throughout the scanning volume, was substantially reduced to within 0.4% after correction. The distortion free MR images were co-registered with the corresponding CBCT images and imported into a commercial treatment planning software SmART Plan. The planning target volume (PTV) was on average 19% smaller when contoured on the corrected MR-CBCT images relative to raw images without distortion correction. An MR-CBCT based preclinical workflow was successfully designed and implemented for small animal radiotherapy. Combined MR-CBCT image-guided radiotherapy for preclinical research potentially delivers enhanced relevance to human radiotherapy for various disease sites. This novel protocol is wide-ranging and not limited to the orthotopic prostate tumor study presented in the study.

show abstract

Pulmonary blood mass dynamics on 4DCT during tidal breathing

et al. 2019

View full text Add to dashboard Cite

Introduction Direct measurements of pulmonary perfusionReverend Stephen Hales (circa 1733) was the first to have quantitatively measured blood pressure and, variation in blood pressure during tidal breathing (Lewis 1994). Connecting a glass tube to a horse's crural artery and measuring the blood column height, Hales observed a decrease in the column's height during inspiration and an increase with expiration. This observation led to the theory that negative intrathoracic pressure affects left ventricular function by increasing the pressure at which the heart must work against the afterload (Buda et al 1979). It is now established that during spontaneous tidal breathing, venous return to the right atrium increases with the decrease in intrathoracic pressure (Pinsky 1984) and thus, pulmonary arterial blood flow to the lungs increases (Seely 1948).Previous efforts to measure respiratory induced variations in pulmonary perfusion and blood volume were limited to model systems. Brecher et al (Brecher and Hubay 1955) measured pulmonary blood flow (PBF) directly, using flow meters connected to the pulmonary artery and apical vena cava in normal spontaneous breathing

show abstract

The effect of lung deformation on the spatial distribution of pulmonary blood flow

Cited by 6 publications

References 46 publications

Rapid 3D in vivo 1H human lung respiratory imaging at 1.5 T using ultra‐fast balanced steady‐state free precession

Rapid 3D in vivo 1H human lung respiratory imaging at 1.5 T using ultra‐fast balanced steady‐state free precession

MR-CBCT image-guided system for radiotherapy of orthotopic rat prostate tumors

Pulmonary blood mass dynamics on 4DCT during tidal breathing

Contact Info

Product

Resources

About