Quantitative Imaging and Analysis Lab

Predictive Alzheimer’s Risk

Posted on December 19, 2025 by Cristian Badea

Congratulations to QIAL’s Dr. Alexandra Badea and Dr. Trong-Kha Truong on receiving the 2025 Medical Physics Fall Seed Grant Award for their project, “Predictive Modeling of Alzheimer’s Disease Risk Using Explainable AI and High-Resolution MRI.”

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Exercise Protects the Aging Heart in High-Fat Diet APOE Mice

Posted on December 16, 2025 by Cristian Badea

Using photon-counting CT and deep learning, we show that voluntary exercise significantly mitigates high-fat diet–induced cardiac dysfunction in adult APOE-targeted mice, with the strongest benefits observed in APOE4 and humanized innate immune (HN) backgrounds.

Exercise mitigates high-fat diet–induced cardiac dysfunction via APOE genotype- and immune-dependent mechanisms: a photon-counting CT study in adult mice. Nadkarni R., Allphin A. J., Clark D. P., Qi Y., Han Z. Y., Ghaghada K. B., Badea A., Badea C. T. PLOS ONE, 2025. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0339293

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Imaging Bone Aging with Photon-Counting CT

Posted on November 13, 2025 by Cristian Badea

How do genetics, sex, and immune signaling shape bone health as mice age?
Our study shows that photon-counting CT in APOE mouse models reveals strong sex- and immune-dependent bone loss, with female HN mice showing the most pronounced decline.

Nadkarni, R.; Han, Z.Y.; Allphin, A.J.; Clark, D.P.; Badea, A.; Badea, C.T.
Photon-Counting Micro-CT for Bone Morphometry in Murine Models.
Tomography 2025, 11, 127. https://doi.org/10.3390/tomography11110127

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Visiting Fulbright Scholar: Dr Kristina Bliznakova

Posted on October 6, 2025 by Cristian Badea

Delighted to host Dr. Kristina Bliznakova, Fulbright Scholar, at Duke’s Quantitative Imaging & Analysis Lab. Looking forward to teaming up on photon-counting CT and virtual imaging.

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Identifying Alzheimer’s network biomarkers

Posted on August 15, 2025 by Cristian Badea

New article and three institutions collaborating!
We identify network biomarkers of Alzheimer’s risk by combining high-res MRI with multifactorial analysis in ApoE mouse models. Joint volume + texture patterns reveal how genotype, sex, diet, & immunity interact to shape brain networks.

Bridgeford EW, Chung J, Anderson RJ, Mahzarnia A, Stout JA, Moon HS, Han ZY, Vogelstein JT, Badea A : Network biomarkers of Alzheimer’s disease risk derived from joint volume and texture covariance patterns in mouse models. PLoS One 20(8): e0327118. https://doi.org/10.1371/journal.pone.0327118

Virtual Wistar Rats Enable Realistic PCCT Simulations

Posted on August 14, 2025 by Cristian Badea

Our team developed anatomically variable digital Wistar rat phantoms for realistic preclinical imaging simulations, enabling PCCT studies & reducing animal use.

Segars, H. E., Nadkarni, R., Badea, C. T., Badea, A., Chin, B., Johnson, G. A., Payne, J., Samei, E., & Segars, W. P. (2025). Development of anatomically variable digital Wistar rat phantoms for small animal imaging research. Medical Physics, 52(8), e18057. https://doi.org/10.1002/mp.18057

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Olfactory-Guided Behavior Uncovers Signatures of AD risk

Posted on August 13, 2025 by Cristian Badea

Could your sense of smell reveal Alzheimer’s risk years before memory loss?
Our new study connects olfactory behavior, brain networks, & blood gene signatures to early AD vulnerability.

Moon, H.S.; Han, Z.Y.; Anderson, R.J.; Mahzarnia, A.; Stout, J.A.; Niculescu, A.R.; Tremblay, J.T.; Badea, A. Olfactory-Guided Behavior Uncovers Imaging and Molecular Signatures of Alzheimer’s Disease Risk. Brain Sci.2025, 15, 863. https://doi.org/10.3390/brainsci15080863

Adaptive AI Denoising for Pediatric Cardiac PCCT

Posted on July 15, 2025 by Cristian Badea

We developed a data-adaptive, self-supervised deep learning method combining sparse coding (SC) + visual transformer (ViT) for denoising pediatric cardiac photon-counting CT. Preserves anatomy, adapts to noise, generalizes well—even to preclinical data.

Clark, D. P., Cao, J. Y., & Badea, C. T. (2025). Denoising pediatric cardiac photon-counting CT data with sparse coding and data-adaptive, self-supervised deep learning. Medical Physics. https://doi.org/10.1002/mp.17918

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PCCT-Visible Bioprinted Patch

Posted on July 15, 2025 by Cristian Badea

Our team developed a CT-visible bioprinted vascular patch using dual-contrast bioinks. Photon-counting CT enabled precise tracking of structure and perfusion, highlighting the role of imaging in cardiac repair.

Gil, C. J., Allphin, A. J., Jin, L., Salar Amoli, M., Rezapourdamanab, S., Tomov, M. L., Hwang, B., Sridhar, V., El Shammas, L. R., Wu, Y., Evans, C. J., Li, L., Singh, Y., Nandwani, R. K., Nish, J., Shen, M., Mahmoudi, M., Bauser, H. D., Pourmorteza, A., Roeder, R. K., Badea, C. T., & Serpooshan, V. (2025). Image-guided cardiac regeneration via a 3D bioprinted vascular patch with built-in CT visibility. Chemical Engineering Journal, 475, 165926. https://doi.org/10.1016/j.cej.2025.165926