Relative Lung Perfusion Distribution in Normal Lung Scans: Observations and Clinical Implications

Cheng, Christopher P.; Taur, Alan; Lee, Grant S.; Goris, Michael L.; Feinstein, Jeffrey A.

doi:10.1111/j.1747-0803.2006.00037.x

Cited by 30 publications

(25 citation statements)

References 19 publications

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“…Our methodology accounted for the deposition in all lung regions truncated in the SPECT/CT FOV by calculating the lung count density (counts/g) from the available left lung SPECT/CT VOI at least 2 cm from the CT liver contour and then multiplying by the total lung mass (g) from the diagnostic chest CT lung VOIs. The implicit assumption that the biodistribution of 99m Tc‐MAA was symmetrical in the left and right lungs was verified in our patient population (Section 3.C.2 ) ; furthermore, this assumption was also found to be valid in healthy lungs . We found that using only the left lung VOI (excluding the 2‐cm liver expansion) successfully minimized liver shine‐through in the left lung in the few cases with high superior left lobe liver 99m Tc‐MAA deposition.…”

Section: Discussionsupporting

confidence: 67%

“…The implicit assumption that the biodistribution of 99m Tc-MAA was symmetrical in the left and right lungs was verified in our patient population (Section 3.C.2); furthermore, this assumption was also found to be valid in healthy lungs. 19 We found that using only the left lung VOI (excluding the 2-cm liver expansion) successfully minimized liver shine-through in the left lung in the few cases with high superior left lobe liver 99m Tc-MAA deposition. Although we observed some apico-basal variation of intensity in the lungs, the mean lung count density was calculated using most of the left lung in the FOV, and therefore minimally affected by local variation in intensity.…”

Section: C Lung 99m Tc-maa Distribution Estimationmentioning

confidence: 73%

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Calculation of lung mean dose and quantification of error for ⁹⁰Y‐microsphere radioembolization using ^99mTc‐MAA SPECT/CT and diagnostic chest CT

et al. 2019

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Purpose Current treatment planning for 90Y radioembolization estimates lung mean dose (LMD) by measuring the lung shunt fraction (LSF) from 99mTc‐macroaggregated albumin (MAA) planar imaging and assuming a 1‐kg lung mass. This methodology, however, overestimates LSF and LMD and could therefore unnecessarily limit the dose to target volume(s). We propose an improved LMD calculation that derives LSF from 99mTc‐MAA SPECT/CT and the patient‐specific lung mass from diagnostic chest CT. Furthermore, we investigated the errors in lung mass, LSF, and LMD arising from contour variability in patient data in order to estimate the precision of our proposed methodology. Methods Our proposed LMD (LMDnew) calculation consisted of the following steps: (a) estimate liver counts from the MAA SPECT/CT liver contour; (b) estimate total lung counts by multiplying density (counts/g) from the MAA SPECT/CT left‐lung contour by the total lung mass (g) from the diagnostic CT lung contours; (c) compute LSFnew from liver and lung counts; (d) calculate LMDnew using LSFnew and the total lung mass from the diagnostic CT (Mnew). LMDnew, LSFnew, and Mnew estimates were compared to standard model values (LMDclin, LSFclin, and 1 kg, respectively) in 52 consecutive patients with hepatocellular carcinoma who underwent radioembolization using 90Y glass microspheres. The precision of our methodology was quantified by varying lung and liver contours in the same patient population and calculating the resulting relative errors in the liver count, lung count, and lung mass measurements. Results The median Mnew was 839 g (range, 550–1178 g) for men and 731 g (range, 548–869 g) for women. The median LSFnew was 0.02 (range, 0.01–0.11), while the median LMDnew was 4.9 Gy (range, 0.3–25.5 Gy). Mnew, LSFnew, and LMDnew were significantly lower than Mclin, LSFclin, and LMDclin, with respective relative mean (±SD) differences of −20% (±16%) for Mnew, −63% (±15%) for LSFnew, and −53% (±23%) for LMDnew. The estimated 1‐sigma uncertainties in Mnew, LSFnew, and LMDnew were 9%, 10%, and 13%, respectively. Conclusions We derived a method to calculate lung mass and LSF using routinely available diagnostic chest CT and 99mTc‐MAA SPECT/CT. More importantly, we systematically quantified the errors in our measurements to establish the precision of the estimated lung dose (13%). The proposed methodology provides a more accurate LMD and an estimate of its precision, which will improve treatment and retreatment planning for 90Y radioembolizations.

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Section: Discussionsupporting

confidence: 67%

Section: C Lung 99m Tc-maa Distribution Estimationmentioning

confidence: 73%

Calculation of lung mean dose and quantification of error for ⁹⁰Y‐microsphere radioembolization using ^99mTc‐MAA SPECT/CT and diagnostic chest CT

et al. 2019

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“…The standard deviations seen in Table are relatively high, but this could be accounted for by the inclusion of semi‐large vessels and the inherent heterogeneity of blood flow in the lung. The perfusion values for both methods exhibit the expected right lung/left lung imbalance .…”

Section: Discussionmentioning

confidence: 87%

Quantitative lung perfusion evaluation using fourier decomposition perfusion MRI

Kjørstad

Corteville

Fischer

et al. 2013

Magnetic Resonance in Med

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“…In fact, assigning a constant pressure condition would lead to a flow split entirely governed by the segmented (simulated) geometry [44], which is likely a non-physiologic result. In this case, the resistance parameters for the left and right branches are tuned to provide a normal flow split, i.e., 55% of the flow to the right side [45], leading to R RPA = 0.011 g mm −4 s −1 and R LPA = 0.017 g mm −4 s −1 . The resistive boundary condition was compared to a three-element Windkessel outflow model, assuming distal resistance coefficients equal to the ones reported above, a proximal resistance equal to 1/10 of the distal resistance, and a compliance coefficient equal to 10 mm 4 s 2 g −1 , as suggested in [36].…”

Section: Boundary Conditionsmentioning

confidence: 99%

Blood Flow Dynamics at the Pulmonary Artery Bifurcation

Capuano

Loke

Balaras

2019

Fluids

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Knowledge of physiologic hemodynamics is a fundamental requirement to establish pathological findings. However, little is known about the normal flow fields in the pulmonary arteries, especially for children. The purpose of this study is to characterize flow patterns in the pulmonary artery bifurcation of healthy pediatric subjects using direct numerical simulations. A realistic geometry is obtained via statistical shape modeling, by averaging five subject-specific digital models extracted from cardiovascular magnetic resonance datasets of healthy volunteers. Boundary conditions are assigned to mimic physiological conditions at rest, corresponding to a peak Reynolds number equal to 3400 and a Womersley number equal to 15. Results show that the normal bifurcation is highly hemodynamically efficient, as measured by an energy dissipation index. The curvature of the pulmonary arteries is sufficiently small to prevent flow separation along the inner walls, and no signs of a turbulent-like state are found. In line with previous imaging studies, a helical structure protruding into the right pulmonary artery is detected, and its formation mechanism is elucidated in the paper. These findings might help to identify abnormal flow features in patients with altered anatomic and physiologic states, particularly those with repaired congenital heart disease.

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Relative Lung Perfusion Distribution in Normal Lung Scans: Observations and Clinical Implications

Cited by 30 publications

References 19 publications

Calculation of lung mean dose and quantification of error for ⁹⁰Y‐microsphere radioembolization using ^99mTc‐MAA SPECT/CT and diagnostic chest CT

Calculation of lung mean dose and quantification of error for ⁹⁰Y‐microsphere radioembolization using ^99mTc‐MAA SPECT/CT and diagnostic chest CT

Quantitative lung perfusion evaluation using fourier decomposition perfusion MRI

Blood Flow Dynamics at the Pulmonary Artery Bifurcation

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Relative Lung Perfusion Distribution in Normal Lung Scans: Observations and Clinical Implications

Cited by 30 publications

References 19 publications

Calculation of lung mean dose and quantification of error for 90Y‐microsphere radioembolization using 99mTc‐MAA SPECT/CT and diagnostic chest CT

Calculation of lung mean dose and quantification of error for 90Y‐microsphere radioembolization using 99mTc‐MAA SPECT/CT and diagnostic chest CT

Quantitative lung perfusion evaluation using fourier decomposition perfusion MRI

Blood Flow Dynamics at the Pulmonary Artery Bifurcation

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Product

Resources

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Calculation of lung mean dose and quantification of error for ⁹⁰Y‐microsphere radioembolization using ^99mTc‐MAA SPECT/CT and diagnostic chest CT

Calculation of lung mean dose and quantification of error for ⁹⁰Y‐microsphere radioembolization using ^99mTc‐MAA SPECT/CT and diagnostic chest CT