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Detection of increased vasa vasorum in artery walls: Improving CT number accuracy using image deconvolution.

Proceedings of SPIE--the International Society for Optical Engineering

Rajendran K, Leng S, Jorgensen SM, Abdurakhimova D, Ritman EL, McCollough CH.
PMID: 28413240
Proc SPIE Int Soc Opt Eng. 2017 Feb 11;10132. doi: 10.1117/12.2255676. Epub 2017 Mar 09.

Changes in arterial wall perfusion are an indicator of early atherosclerosis. This is characterized by an increased spatial density of vasa vasorum (VV), the micro-vessels that supply oxygen and nutrients to the arterial wall. Detection of increased VV during...

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Rajendran K, Leng S, Jorgensen SM, et al. Detection of increased vasa vasorum in artery walls: Improving CT number accuracy using image deconvolution. Proc SPIE Int Soc Opt Eng. 2017;10132doi: 10.1117/12.2255676.
Rajendran, K., Leng, S., Jorgensen, S. M., Abdurakhimova, D., Ritman, E. L., & McCollough, C. H. (2017). Detection of increased vasa vasorum in artery walls: Improving CT number accuracy using image deconvolution. Proceedings of SPIE--the International Society for Optical Engineering, 10132. https://doi.org/10.1117/12.2255676
Rajendran, Kishore, et al. "Detection of increased vasa vasorum in artery walls: Improving CT number accuracy using image deconvolution." Proceedings of SPIE--the International Society for Optical Engineering vol. 10132 (2017). doi: https://doi.org/10.1117/12.2255676
Rajendran K, Leng S, Jorgensen SM, Abdurakhimova D, Ritman EL, McCollough CH. Detection of increased vasa vasorum in artery walls: Improving CT number accuracy using image deconvolution. Proc SPIE Int Soc Opt Eng. 2017 Feb 11;10132. doi: 10.1117/12.2255676. Epub 2017 Mar 09. PMID: 28413240; PMCID: PMC5391689.
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Dual-source multienergy CT with triple or quadruple x-ray beams.

Journal of medical imaging (Bellingham, Wash.)

Yu L, Ren L, Li Z, Leng S, McCollough CH.
PMID: 30065949
J Med Imaging (Bellingham). 2018 Jul;5(3):033502. doi: 10.1117/1.JMI.5.3.033502. Epub 2018 Jul 24.

Energy-resolved photon-counting-detector CT (PCD-CT) is promising for material decomposition with multiple contrast agents using two or more energy bins. However, corrections for nonidealities of PCDs are required, which are still active research topics. In addition, PCD-CT is also likely...

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Yu L, Ren L, Li Z, et al. Dual-source multienergy CT with triple or quadruple x-ray beams. J Med Imaging (Bellingham). 2018;5(3):033502doi: 10.1117/1.JMI.5.3.033502.
Yu, L., Ren, L., Li, Z., Leng, S., & McCollough, C. H. (2018). Dual-source multienergy CT with triple or quadruple x-ray beams. Journal of medical imaging (Bellingham, Wash.), 5(3), 033502. https://doi.org/10.1117/1.JMI.5.3.033502
Yu, Lifeng, et al. "Dual-source multienergy CT with triple or quadruple x-ray beams." Journal of medical imaging (Bellingham, Wash.) vol. 5,3 (2018): 033502. doi: https://doi.org/10.1117/1.JMI.5.3.033502
Yu L, Ren L, Li Z, Leng S, McCollough CH. Dual-source multienergy CT with triple or quadruple x-ray beams. J Med Imaging (Bellingham). 2018 Jul;5(3):033502. doi: 10.1117/1.JMI.5.3.033502. Epub 2018 Jul 24. PMID: 30065949; PMCID: PMC6056773.
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Impact of prior information on material decomposition in dual- and multienergy computed tomography.

Journal of medical imaging (Bellingham, Wash.)

Ren L, Tao S, Rajendran K, McCollough CH, Yu L.
PMID: 30891466
J Med Imaging (Bellingham). 2019 Jan;6(1):013503. doi: 10.1117/1.JMI.6.1.013503. Epub 2019 Mar 14.

Prior information is often included in the basis material decomposition to solve the quantification problem of three-material mixtures in dual-energy computed tomography (DECT). Multienergy computed tomography (MECT) with more than two energy bins can provide a sufficient solution to...

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Ren L, Tao S, Rajendran K, et al. Impact of prior information on material decomposition in dual- and multienergy computed tomography. J Med Imaging (Bellingham). 2019;6(1):013503doi: 10.1117/1.JMI.6.1.013503.
Ren, L., Tao, S., Rajendran, K., McCollough, C. H., & Yu, L. (2019). Impact of prior information on material decomposition in dual- and multienergy computed tomography. Journal of medical imaging (Bellingham, Wash.), 6(1), 013503. https://doi.org/10.1117/1.JMI.6.1.013503
Ren, Liqiang, et al. "Impact of prior information on material decomposition in dual- and multienergy computed tomography." Journal of medical imaging (Bellingham, Wash.) vol. 6,1 (2019): 013503. doi: https://doi.org/10.1117/1.JMI.6.1.013503
Ren L, Tao S, Rajendran K, McCollough CH, Yu L. Impact of prior information on material decomposition in dual- and multienergy computed tomography. J Med Imaging (Bellingham). 2019 Jan;6(1):013503. doi: 10.1117/1.JMI.6.1.013503. Epub 2019 Mar 14. PMID: 30891466; PMCID: PMC6416528.
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Variants in .

Brain communications

Ramanan VK, Wang X, Przybelski SA, Raghavan S, Heckman MG, Batzler A, Kosel ML, Hohman TJ, Knopman DS, Graff-Radford J, Lowe VJ, Mielke MM, Jack CR, Petersen RC, Ross OA, Vemuri P.
PMID: 33426524
Brain Commun. 2020 Sep 26;2(2):fcaa159. doi: 10.1093/braincomms/fcaa159. eCollection 2020.

Tau deposition is a key biological feature of Alzheimer's disease that is closely related to cognitive impairment. However, it remains poorly understood why certain individuals may be more susceptible to tau deposition while others are more resistant. The recent...

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Ramanan VK, Wang X, Przybelski SA, et al. Variants in . Brain Commun. 2020;2(2):fcaa159doi: 10.1093/braincomms/fcaa159.
Ramanan, V. K., Wang, X., Przybelski, S. A., Raghavan, S., Heckman, M. G., Batzler, A., Kosel, M. L., Hohman, T. J., Knopman, D. S., Graff-Radford, J., Lowe, V. J., Mielke, M. M., Jack, C. R., Petersen, R. C., Ross, O. A., & Vemuri, P. (2020). Variants in . Brain communications, 2(2), fcaa159. https://doi.org/10.1093/braincomms/fcaa159
Ramanan, Vijay K, et al. "Variants in ." Brain communications vol. 2,2 (2020): fcaa159. doi: https://doi.org/10.1093/braincomms/fcaa159
Ramanan VK, Wang X, Przybelski SA, Raghavan S, Heckman MG, Batzler A, Kosel ML, Hohman TJ, Knopman DS, Graff-Radford J, Lowe VJ, Mielke MM, Jack CR, Petersen RC, Ross OA, Vemuri P. Variants in . Brain Commun. 2020 Sep 26;2(2):fcaa159. doi: 10.1093/braincomms/fcaa159. eCollection 2020. PMID: 33426524; PMCID: PMC7780444.
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Study of Symptomatic vs. Silent Brain Infarctions on MRI in Elderly Subjects.

Frontiers in neurology

Raghavan S, Graff-Radford J, Scharf E, Przybelski SA, Lesnick TG, Gregg B, Schwarz CG, Gunter JL, Zuk SM, Rabinstein A, Mielke MM, Petersen RC, Knopman DS, Kantarci K, Jack CR, Vemuri P.
PMID: 33679582
Front Neurol. 2021 Feb 17;12:615024. doi: 10.3389/fneur.2021.615024. eCollection 2021.

Brain infarctions are closely associated with future risk of stroke and dementia. Our goal was to report (i) frequency and characteristics that differentiate symptomatic vs. silent brain infarctions (SBI) on MRI and (ii) frequency and location by vascular distribution...

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Raghavan S, Graff-Radford J, Scharf E, et al. Study of Symptomatic vs. Silent Brain Infarctions on MRI in Elderly Subjects. Front Neurol. 2021;12:615024doi: 10.3389/fneur.2021.615024.
Raghavan, S., Graff-Radford, J., Scharf, E., Przybelski, S. A., Lesnick, T. G., Gregg, B., Schwarz, C. G., Gunter, J. L., Zuk, S. M., Rabinstein, A., Mielke, M. M., Petersen, R. C., Knopman, D. S., Kantarci, K., Jack, C. R., & Vemuri, P. (2021). Study of Symptomatic vs. Silent Brain Infarctions on MRI in Elderly Subjects. Frontiers in neurology, 12615024. https://doi.org/10.3389/fneur.2021.615024
Raghavan, Sheelakumari, et al. "Study of Symptomatic vs. Silent Brain Infarctions on MRI in Elderly Subjects." Frontiers in neurology vol. 12 (2021): 615024. doi: https://doi.org/10.3389/fneur.2021.615024
Raghavan S, Graff-Radford J, Scharf E, Przybelski SA, Lesnick TG, Gregg B, Schwarz CG, Gunter JL, Zuk SM, Rabinstein A, Mielke MM, Petersen RC, Knopman DS, Kantarci K, Jack CR, Vemuri P. Study of Symptomatic vs. Silent Brain Infarctions on MRI in Elderly Subjects. Front Neurol. 2021 Feb 17;12:615024. doi: 10.3389/fneur.2021.615024. eCollection 2021. PMID: 33679582; PMCID: PMC7925615.
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Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner.

Journal of medical imaging (Bellingham, Wash.)

Yu Z, Leng S, Kappler S, Hahn K, Li Z, Halaweish AF, Henning A, McCollough CH.
PMID: 28018936
J Med Imaging (Bellingham). 2016 Oct;3(4):043503. doi: 10.1117/1.JMI.3.4.043503. Epub 2016 Dec 14.

Photon counting detector (PCD)-based computed tomography (CT) is an emerging imaging technique. Compared to conventional energy integrating detector (EID)-based CT, PCD-CT is able to exclude electronic noise that may severely impair image quality at low photon counts. This work...

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Yu Z, Leng S, Kappler S, et al. Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner. J Med Imaging (Bellingham). 2016;3(4):043503doi: 10.1117/1.JMI.3.4.043503.
Yu, Z., Leng, S., Kappler, S., Hahn, K., Li, Z., Halaweish, A. F., Henning, A., & McCollough, C. H. (2016). Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner. Journal of medical imaging (Bellingham, Wash.), 3(4), 043503. https://doi.org/10.1117/1.JMI.3.4.043503
Yu, Zhicong, et al. "Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner." Journal of medical imaging (Bellingham, Wash.) vol. 3,4 (2016): 043503. doi: https://doi.org/10.1117/1.JMI.3.4.043503
Yu Z, Leng S, Kappler S, Hahn K, Li Z, Halaweish AF, Henning A, McCollough CH. Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner. J Med Imaging (Bellingham). 2016 Oct;3(4):043503. doi: 10.1117/1.JMI.3.4.043503. Epub 2016 Dec 14. PMID: 28018936; PMCID: PMC5155128.
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Pretreatment imaging of peripheral vascular malformations.

Journal of vascular diagnostics

Johnson JB, Cogswell PM, McKusick MA, Binkovitz LA, Riederer SJ, Young PM.
PMID: 25625123
J Vasc Diagn. 2014;2014(2):121-126. doi: 10.2147/JVD.S66467.

Peripheral vascular malformations (VMs) are complex and diverse vascular lesions which require individualized pretreatment planning. Pretreatment imaging using various modalities, especially magnetic resonance imaging and time-resolved magnetic resonance angiography, is a valuable tool for classifying peripheral VMs to allow...

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Johnson JB, Cogswell PM, McKusick MA, et al. Pretreatment imaging of peripheral vascular malformations. J Vasc Diagn. 2014;2014(2):121-126doi: 10.2147/JVD.S66467.
Johnson, J. B., Cogswell, P. M., McKusick, M. A., Binkovitz, L. A., Riederer, S. J., & Young, P. M. (2014). Pretreatment imaging of peripheral vascular malformations. Journal of vascular diagnostics, 2014(2), 121-126. https://doi.org/10.2147/JVD.S66467
Johnson, Joshua B, et al. "Pretreatment imaging of peripheral vascular malformations." Journal of vascular diagnostics vol. 2014,2 (2014): 121-126. doi: https://doi.org/10.2147/JVD.S66467
Johnson JB, Cogswell PM, McKusick MA, Binkovitz LA, Riederer SJ, Young PM. Pretreatment imaging of peripheral vascular malformations. J Vasc Diagn. 2014;2014(2):121-126. doi: 10.2147/JVD.S66467. PMID: 25625123; PMCID: PMC4304669.
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Tau-PET uptake: Regional variation in average SUVR and impact of amyloid deposition.

Alzheimer's & dementia (Amsterdam, Netherlands)

Vemuri P, Lowe VJ, Knopman DS, Senjem ML, Kemp BJ, Schwarz CG, Przybelski SA, Machulda MM, Petersen RC, Jack CR.
PMID: 28138510
Alzheimers Dement (Amst). 2016 Dec 21;6:21-30. doi: 10.1016/j.dadm.2016.12.010. eCollection 2017.

INTRODUCTION: Tau-positron emission tomography (PET) imaging with AV1451 is sensitive to Alzheimer disease (AD)-related tau deposition in the brain. We (1) examined regional variation of average tau-PET standardized uptake value ratios (SUVRs) in a young normal population (30-49 years)...

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Vemuri P, Lowe VJ, Knopman DS, et al. Tau-PET uptake: Regional variation in average SUVR and impact of amyloid deposition. Alzheimers Dement (Amst). 2016;6:21-30doi: 10.1016/j.dadm.2016.12.010.
Vemuri, P., Lowe, V. J., Knopman, D. S., Senjem, M. L., Kemp, B. J., Schwarz, C. G., Przybelski, S. A., Machulda, M. M., Petersen, R. C., & Jack, C. R. (2017). Tau-PET uptake: Regional variation in average SUVR and impact of amyloid deposition. Alzheimer's & dementia (Amsterdam, Netherlands), 621-30. https://doi.org/10.1016/j.dadm.2016.12.010
Vemuri, Prashanthi, et al. "Tau-PET uptake: Regional variation in average SUVR and impact of amyloid deposition." Alzheimer's & dementia (Amsterdam, Netherlands) vol. 6 (2017): 21-30. doi: https://doi.org/10.1016/j.dadm.2016.12.010
Vemuri P, Lowe VJ, Knopman DS, Senjem ML, Kemp BJ, Schwarz CG, Przybelski SA, Machulda MM, Petersen RC, Jack CR. Tau-PET uptake: Regional variation in average SUVR and impact of amyloid deposition. Alzheimers Dement (Amst). 2016 Dec 21;6:21-30. doi: 10.1016/j.dadm.2016.12.010. eCollection 2017. PMID: 28138510; PMCID: PMC5257031.
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Impact of Photon Counting Detector Technology on kV Selection and Diagnostic Workflow in CT.

Proceedings of SPIE--the International Society for Optical Engineering

Zhou W, Abdurakhimova D, Bruesewitz M, Halaweish A, McCollough CH, Leng S.
PMID: 30034081
Proc SPIE Int Soc Opt Eng. 2018 Mar;10573. doi: 10.1117/12.2294952.

The purpose of this study is to determine the optimal iodine contrast-to-noise ratio (CNR) achievable for different patient sizes using virtual-monoenergetic-images (VMIs) and a universal acquisition protocol on photon-counting-detector CT (PCD-CT), and to compare results to those from single-energy...

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Zhou W, Abdurakhimova D, Bruesewitz M, et al. Impact of Photon Counting Detector Technology on kV Selection and Diagnostic Workflow in CT. Proc SPIE Int Soc Opt Eng. 2018;10573doi: 10.1117/12.2294952.
Zhou, W., Abdurakhimova, D., Bruesewitz, M., Halaweish, A., McCollough, C. H., & Leng, S. (2018). Impact of Photon Counting Detector Technology on kV Selection and Diagnostic Workflow in CT. Proceedings of SPIE--the International Society for Optical Engineering, 10573. https://doi.org/10.1117/12.2294952
Zhou, Wei, et al. "Impact of Photon Counting Detector Technology on kV Selection and Diagnostic Workflow in CT." Proceedings of SPIE--the International Society for Optical Engineering vol. 10573 (2018). doi: https://doi.org/10.1117/12.2294952
Zhou W, Abdurakhimova D, Bruesewitz M, Halaweish A, McCollough CH, Leng S. Impact of Photon Counting Detector Technology on kV Selection and Diagnostic Workflow in CT. Proc SPIE Int Soc Opt Eng. 2018 Mar;10573. doi: 10.1117/12.2294952. PMID: 30034081; PMCID: PMC6052873.
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Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution.

Journal of medical imaging (Bellingham, Wash.)

Rajendran K, Leng S, Jorgensen SM, Anderson JL, Halaweish AF, Abdurakhimova D, Ritman EL, McCollough CH.
PMID: 29250564
J Med Imaging (Bellingham). 2017 Oct;4(4):044006. doi: 10.1117/1.JMI.4.4.044006. Epub 2017 Dec 08.

Changes in arterial wall perfusion mark the onset of atherosclerosis. A characteristic change is the increased spatial density of vasa vasorum (VV), the microvessels in the arterial walls. Measuring this increased VV (IVV) density using contrast-enhanced computed tomography (CT)...

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Rajendran K, Leng S, Jorgensen SM, et al. Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution. J Med Imaging (Bellingham). 2017;4(4):044006doi: 10.1117/1.JMI.4.4.044006.
Rajendran, K., Leng, S., Jorgensen, S. M., Anderson, J. L., Halaweish, A. F., Abdurakhimova, D., Ritman, E. L., & McCollough, C. H. (2017). Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution. Journal of medical imaging (Bellingham, Wash.), 4(4), 044006. https://doi.org/10.1117/1.JMI.4.4.044006
Rajendran, Kishore, et al. "Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution." Journal of medical imaging (Bellingham, Wash.) vol. 4,4 (2017): 044006. doi: https://doi.org/10.1117/1.JMI.4.4.044006
Rajendran K, Leng S, Jorgensen SM, Anderson JL, Halaweish AF, Abdurakhimova D, Ritman EL, McCollough CH. Measuring arterial wall perfusion using photon-counting computed tomography (CT): improving CT number accuracy of artery wall using image deconvolution. J Med Imaging (Bellingham). 2017 Oct;4(4):044006. doi: 10.1117/1.JMI.4.4.044006. Epub 2017 Dec 08. PMID: 29250564; PMCID: PMC5722232.
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White matter abnormalities are key components of cerebrovascular disease impacting cognitive decline.

Brain communications

Vemuri P, Graff-Radford J, Lesnick TG, Przybelski SA, Reid RI, Reddy AL, Lowe VJ, Mielke MM, Machulda MM, Petersen RC, Knopman DS, Jack CR.
PMID: 33937772
Brain Commun. 2021 Apr 12;3(2):fcab076. doi: 10.1093/braincomms/fcab076. eCollection 2021.

While cerebrovascular disease can be observed

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Vemuri P, Graff-Radford J, Lesnick TG, et al. White matter abnormalities are key components of cerebrovascular disease impacting cognitive decline. Brain Commun. 2021;3(2):fcab076doi: 10.1093/braincomms/fcab076.
Vemuri, P., Graff-Radford, J., Lesnick, T. G., Przybelski, S. A., Reid, R. I., Reddy, A. L., Lowe, V. J., Mielke, M. M., Machulda, M. M., Petersen, R. C., Knopman, D. S., & Jack, C. R. (2021). White matter abnormalities are key components of cerebrovascular disease impacting cognitive decline. Brain communications, 3(2), fcab076. https://doi.org/10.1093/braincomms/fcab076
Vemuri, Prashanthi, et al. "White matter abnormalities are key components of cerebrovascular disease impacting cognitive decline." Brain communications vol. 3,2 (2021): fcab076. doi: https://doi.org/10.1093/braincomms/fcab076
Vemuri P, Graff-Radford J, Lesnick TG, Przybelski SA, Reid RI, Reddy AL, Lowe VJ, Mielke MM, Machulda MM, Petersen RC, Knopman DS, Jack CR. White matter abnormalities are key components of cerebrovascular disease impacting cognitive decline. Brain Commun. 2021 Apr 12;3(2):fcab076. doi: 10.1093/braincomms/fcab076. eCollection 2021. PMID: 33937772; PMCID: PMC8072521.
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Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition.

Brain communications

Raghavan S, Reid RI, Przybelski SA, Lesnick TG, Graff-Radford J, Schwarz CG, Knopman DS, Mielke MM, Machulda MM, Petersen RC, Jack CR, Vemuri P.
PMID: 34136811
Brain Commun. 2021 May 19;3(2):fcab106. doi: 10.1093/braincomms/fcab106. eCollection 2021.

White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to...

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Raghavan S, Reid RI, Przybelski SA, et al. Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition. Brain Commun. 2021;3(2):fcab106doi: 10.1093/braincomms/fcab106.
Raghavan, S., Reid, R. I., Przybelski, S. A., Lesnick, T. G., Graff-Radford, J., Schwarz, C. G., Knopman, D. S., Mielke, M. M., Machulda, M. M., Petersen, R. C., Jack, C. R., & Vemuri, P. (2021). Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition. Brain communications, 3(2), fcab106. https://doi.org/10.1093/braincomms/fcab106
Raghavan, Sheelakumari, et al. "Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition." Brain communications vol. 3,2 (2021): fcab106. doi: https://doi.org/10.1093/braincomms/fcab106
Raghavan S, Reid RI, Przybelski SA, Lesnick TG, Graff-Radford J, Schwarz CG, Knopman DS, Mielke MM, Machulda MM, Petersen RC, Jack CR, Vemuri P. Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition. Brain Commun. 2021 May 19;3(2):fcab106. doi: 10.1093/braincomms/fcab106. eCollection 2021. PMID: 34136811; PMCID: PMC8202149.
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