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Ramirez, Giselle

https://orcid.org/0009-0004-3730-5075

Mayo Clinic

Mount Sinai Hospital

Citations 2

Automated AI-Based Aortic Measurements From Attenuation Correction CT as an Adjunctive Cardiovascular Risk Biomarker: An International Multicenter Study
Marcinkiewicz, Anna M , Shanbhag, Aakash , Chareonthaitawee, Panithaya , Zhang, Wenhao, Jilaihawi, Hasan , Zaid, Ryan , Cadet, Sebastien , Ramirez, Giselle , Lemley, Mark , Yi, Jirong , Hijazi, Waseem , Liang, Joanna X. , Fehér, Attila , Mason, Steve, Alexanderson, Erick, Carvajal-Juarez, Isabel , Travin, Mark I. , Rosamond, Thomas, Wopperer, Samuel , Berman, Daniel S. , Carli, Marcelo F. Di , Al-Jilaihawi, Hasanian , Builoff, Valerie , Calsavara, Vinicius F , Einstein, Andrew Jeffrey , Miller, Edward J , Feher, Attila , Ruddy, Terrence D , Le, Viet T , Knight, Stacey , Carvajal-Juarez, Isabel , Slipczuk, Leandro , Rosamond, Thomas L , Wopperer, Samuel , Berman, Daniel , Dey, Damini , Di Carli, Marcelo F , Miller, Robert J H , Slomka, Piotr J , Chareonthaitawee, Panithaya , Lemley, Mark , Ramirez, Giselle , Shanbhag, Aakash , Zaid, Ryan , Miller, Edward J. , Le, Viet T. , Mason, Steve, Knight, Stacey , Alexanderson, Erick , Slipczuk, Leandro , Dey, Damini , Miller, Robert J.H.

Circulation: Cardiovascular Imaging | July 2, 2026 | Volume: 19 | Issue: 7 | Pages: No page available

10.1161/circimaging.125.019726 Get It

BACKGROUND: Aortic enlargement is a powerful predictor of dissection and rupture, yet it is rarely evaluated during routine myocardial perfusion imaging, despite the widespread availability of computed tomography (CT) attenuation correction scans. The aim of this study was to determine whether fully automated, opportunistically derived, artificial intelligence-based aortic measurements from myocardial perfusion imaging CT attenuation correction scans are associated with adverse outcomes in a large multicenter cohort. METHODS: CT attenuation correction scans from patients undergoing positron emission tomography/CT and single-photon emission CT/CT myocardial perfusion imaging across 10 centers were included. A deep learning model automatically segmented the thoracic aorta, and a postprocessing algorithm extracted maximum ascending and descending diameters. The aortic size index was calculated by indexing the diameter to body surface area. RESULTS: A total of 29 339 patients (56% men; median age, 66 years [interquartile range, 58–75 years]) were included. Over a median follow-up of 3.5 years (interquartile range, 1.9–5.0 years), 5083 (17.3%) patients died. Median ascending and descending aortic size index values were 1.8 cm/m 2 (interquartile range, 1.6–2.0) and 1.5 cm/m 2 (interquartile range, 1.4–1.6), respectively, with an increase with age and higher values in females. Elevated aortic size index thresholds (ascending >2.2 cm/m 2 ; descending >1.6 cm/m 2 ) were significantly associated with increased all-cause mortality (ascending: adjusted hazard ratio, 1.16 [95% CI, 1.07–1.26], P <0.001; descending: adjusted hazard ratio, 1.23 [95% CI, 1.14–1.31]; P <0.001). Notably, the prognostic value of an abnormal aortic size index persisted independent of age, sex, and perfusion abnormalities. CONCLUSIONS: Artificial intelligence can unlock previously unused information within routine myocardial perfusion imaging CT attenuation correction scans by rapidly and automatically quantifying aortic size at scale. Opportunistic aortic measurements derived from CT attenuation correction may serve as an adjunctive risk biomarker and could add prognostic value to standard myocardial perfusion imaging without additional imaging or radiation.
Incremental Prognostic Value of Subendocardial Myocardial Flow Reserve in Patients With Normal Perfusion
Lopez, Diana M. , Brown, Jenifer M. , Divakaran, Sanjay , Weber, Brittany , Hainer, Jon , Carre, Sylvain, Lemley, Mark , Ramirez, Giselle , Shanbhag, Aakash , Kavanagh, Paul, Liang, Joanna X. , Blankstein, Ron , Dorbala, S, Mason, Steve, Wopperer, Samuel , Rosamond, Thomas, Kwieciński, Jacek , Travin, Mark I. , Alexanderson, Erick, Packard, René R S, Feher, A, Sanghani, Rupa, deKemp, Robert A. , Berman, Daniel S. , Slomka, P J, Carli, Marcelo F. Di , Packard, René R. Sevag , Lopez, Diana M , Huck, Daniel , Weber, Brittany , Hainer, Jon , Lemley, Mark , Ramirez, Giselle , Shanbhag, Aakash , Kavanagh, Paul , Blankstein, Ron , Dorbala, Sharmila , Dey, Damini , Knight, Stacey , Le, Viet T , Wopperer, Samuel , Chareonthaitawee, Panithaya , Rosamond, Thomas L , Kwiecinski, Jacek , Miller, Robert J H , Slipczuk, Leandro , Carvajal-Juarez, Isabel , Packard, Rene R S , Al-Mallah, Mouaz H , Einstein, Andrew Jeffrey , Feher, Attila , Acampa, Wanda , Buechel, Ronny R , deKemp, Robert A , Berman, Daniel , Slomka, Piotr J , Di Carli, Marcelo F , Divakaran, Sanjay , Brown, Jenifer Michelle , Kavanagh, Paul , Dey, Damini , Knight, Stacey , Le, Viet T. , Mason, Steve, Chareonthaitawee, Panithaya , Miller, Robert J.H. , Slipczuk, Leandro , Alexanderson, Erick , Carvajal-Juarez, Isabel , Al‐Mallah, Mouaz H. , Sanghani, Rupa Mehta

Circulation | June 4, 2026 | Volume: 154 | Issue: 3 | Pages: 212-222

10.1161/circulationaha.125.078816 Get It

BACKGROUND: Although the prognostic utility of positron emission tomography (PET) myocardial flow reserve (MFR) is well established, emerging data suggest that reduced subendocardial flows also predict adverse outcomes. However, the incremental value of subendocardial MFR (MFR SE ) beyond transmural MFR (MFR TM ) remains unclear. METHODS: We studied patients in a multicenter PET registry with normal perfusion on stress/rest Rb-82 PET, excluding those with a previous history of coronary artery bypass surgery, heart transplantation, or left ventricular ejection fraction <40%. The optimal MFR SE cutoff for predicting major adverse cardiovascular events (MACEs; death, myocardial infarction [MI], revascularization, or heart failure [HF] hospitalization) was determined using Youden’s index. Patients were stratified into 3 groups: concordant-normal (MFR TM ≥2.0; MFR SE ≥2.1), discordant (low-MFR SE , normal MFR TM ), and abnormal MFR TM . Clinical outcomes were compared by MFR groups. RESULTS: Among 6603 patients (normal N=4103; discordant N=885; abnormal N=1615) the mean age was 66.3±12.4 years, and 54% were women. Compared with the concordant-normal group, patients with discordant low-MFR SE were older and more likely to have hypertension, diabetes, peripheral artery disease, and previous percutaneous coronary intervention. The median MFR TM for normal, discordant, and abnormal groups were 2.86, 2.15, and 1.72, respectively. Over a median follow-up of 4.9 years, 1661 MACE events occurred. Discordant low-MFR SE patients had a higher risk of MACE (hazard ratio [HR], 1.41; 95% CI, 1.22–1.64) and all-cause mortality (HR, 1.36; 95% CI, 1.14–1.61) compared with concordant-normal patients. The discordant group had an intermediate absolute risk of MACE, with an adjusted annualized event rate of 5.79% (95% CI, 5.10–6.49) compared with 3.99% (95% CI, 3.67–4.30; P <0.001) in the concordant-normal group and 8.35% (95% CI, 7.71–9.00; P <0.001) in the abnormal MFR TM group. CONCLUSIONS: Subendocardial MFR reveals clinically meaningful risk heterogeneity among patients with preserved transmural flow reserve, helping refine risk stratification beyond traditional PET metrics.