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      Patient-specific arterial input function for accurate perfusion assessment in intraoperative fluorescence imaging

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          Abstract.

          Significance

          The arterial input function (AIF) plays a crucial role in correcting the time-dependent concentration of the contrast agent within the arterial system, accounting for variations in agent injection parameters (speed, timing, etc.) across patients. Understanding the significance of the AIF can enhance the accuracy of tissue vascular perfusion assessment through indocyanine green–based dynamic contrast-enhanced fluorescence imaging (DCE-FI).

          Aim

          We evaluate the impact of the AIF on perfusion assessment through DCE-FI.

          Approach

          A total of 144 AIFs were acquired from 110 patients using a pulse dye densitometer. Simulation and patient intraoperative imaging were conducted to validate the significance of AIF for perfusion assessment based on kinetic parameters extracted from fluorescence images before and after AIF correction. The kinetic model accuracy was evaluated by assessing the variability of kinetic parameters using individual AIF versus population-based AIF.

          Results

          Individual AIF can reduce the variability in kinetic parameters, and population-based AIF can potentially replace individual AIF for estimating wash-out rate ( kep ), maximum intensity ( Imax ), ingress slope with lower differences compared with those in estimating blood flow, volume transfer constant ( Ktrans ), and time to peak.

          Conclusions

          Individual AIF can provide the most accurate perfusion assessment compared with assessment without AIF or based on population-based AIF correction.

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          Most cited references44

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          Models and methods for analyzing DCE-MRI: a review.

          To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.
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            Confidence in Altman-Bland plots: a critical review of the method of differences.

            1. Altman and Bland argue that the virtue of plotting differences against averages in method-comparison studies is that 95% confidence limits for the differences can be constructed. These allow authors and readers to judge whether one method of measurement could be substituted for another. 2. The technique is often misused. So I have set out, by statistical argument and worked examples, to advise pharmacologists and physiologists how best to construct these limits. 3. First, construct a scattergram of differences on averages, then calculate the line of best fit for the linear regression of differences on averages. If the slope of the regression is shown to differ from zero, there is proportional bias. 4. If there is no proportional bias and if the scatter of differences is uniform (homoscedasticity), construct 'classical' 95% confidence limits. 5. If there is proportional bias yet homoscedasticity, construct hyperbolic 95% confidence limits (prediction interval) around the line of best fit. 6. If there is proportional bias and the scatter of values for differences increases progressively as the average values increase (heteroscedasticity), log-transform the raw values from the two methods and replot differences against averages. If this eliminates proportional bias and heteroscedasticity, construct 'classical' 95% confidence limits. Otherwise, construct horizontal V-shaped 95% confidence limits around the line of best fit of differences on averages or around the weighted least products line of best fit to the original data. 7. In designing a method-comparison study, consult a qualified biostatistician, obey the rules of randomization and make replicate observations.
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              The Key Role of the Blood Supply to Bone

              The importance of the vascular supply for bone is well-known to orthopaedists but is still rather overlooked within the wider field of skeletal research. Blood supplies oxygen, nutrients and regulatory factors to tissues, as well as removing metabolic waste products such as carbon dioxide and acid. Bone receives up to about 10% of cardiac output, and this blood supply permits a much higher degree of cellularity, remodelling and repair than is possible in cartilage, which is avascular. The blood supply to bone is delivered to the endosteal cavity by nutrient arteries, then flows through marrow sinusoids before exiting via numerous small vessels that ramify through the cortex. The marrow cavity affords a range of vascular niches that are thought to regulate the growth and differentiation of hematopoietic and stromal cells, in part via gradients of oxygen tension. The quality of vascular supply to bone tends to decline with age and may be compromised in common pathological settings, including diabetes, anaemias, chronic airway diseases and immobility, as well as by tumours. Reductions in vascular supply are associated with bone loss. This may be due in part to the direct effects of hypoxia, which blocks osteoblast function and bone formation but causes reciprocal increases in osteoclastogenesis and bone resorption. Common regulatory factors such as parathyroid hormone or nitrates, both of which are potent vasodilators, might exert their osteogenic effects on bone via the vasculature. These observations suggest that the bone vasculature will be a fruitful area for future research.
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                Author and article information

                Contributors
                Journal
                J Biomed Opt
                J Biomed Opt
                JBOPFO
                JBO
                Journal of Biomedical Optics
                Society of Photo-Optical Instrumentation Engineers
                1083-3668
                1560-2281
                6 September 2024
                June 2024
                6 September 2024
                : 29
                : Suppl 3
                : S33306
                Affiliations
                [a ]Thayer School of Engineering at Dartmouth , Hanover, New Hampshire, United States
                [b ]Dartmouth Health , Department of Orthopaedics, Lebanon, New Hampshire, United States
                Author notes
                [* ]Address all correspondence to Jonathan Thomas Elliott, Jonathan.T.Elliott@ 123456dartmouth.edu
                [†]

                Yue Tang and Shudong Jiang contributed equally to this work.

                Author information
                https://orcid.org/0009-0000-3589-6917
                https://orcid.org/0000-0001-7396-7886
                https://orcid.org/0000-0003-0585-2969
                https://orcid.org/0000-0001-6084-1440
                https://orcid.org/0000-0002-0371-010X
                https://orcid.org/0000-0002-8485-0234
                Article
                JBO-240089SSR 240089SSR
                10.1117/1.JBO.29.S3.S33306
                11379448
                39247899
                2e1a6c81-b6c6-4780-939c-203805dfa7df
                © 2024 The Authors

                Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

                History
                : 29 March 2024
                : 17 July 2024
                : 18 July 2024
                Page count
                Figures: 9, Tables: 3, References: 44, Pages: 17
                Funding
                Funded by: National Institutes of Health
                Award ID: R01 AR077157
                Award ID: R00 CA190890
                Funded by: Department of Defense Clinical Translational Research Award
                Award ID: W81XWH2010319
                Funded by: Gillian Reny Stepping Strong Center for Trauma Innovation
                Categories
                Special Issue on Pulse Oximetry: 50 Years of Inventions and Discoveries in Biomedical Optics
                Paper
                Custom metadata
                Tang et al.: Patient-specific arterial input function for accurate perfusion assessment…

                Biomedical engineering
                arterial input function,pulse dye densitometry,dynamic contrast-enhanced fluorescence imaging,indocyanine green,vascular perfusion,kinetic parameters of perfusion

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