Ms. Ailis Muldoon Profile

Ailis Muldoon

at Athinoula A Martinos Ctr for Biomedical Imaging

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Author

Publications (4)

SPIE Journal Paper | 11 May 2024 Open Access

Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy

Bin Deng, Ailis Muldoon, Jayne Cormier, Nathaniel Mercaldo, Elizabeth Niehoff, Natalie Moffett, Mansi A. Saksena, Steven Isakoff, Stefan Carp

JBO, Vol. 29, Issue 06, 066001, (May 2024) https://doi.org/10.1117/12.10.1117/1.JBO.29.6.066001

KEYWORDS: Tumors, Breast, Digital breast tomosynthesis, Biomedical optics, Mammography, Tissues, Hemodynamics, Chemotherapy, Breast cancer, Magnetic resonance imaging

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SignificanceAchieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes.AimWe aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT.ApproachTwenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers.ResultsNormalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (p=0.042). In addition, the change in normalized tumor StO2 upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (p=0.038). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI.ConclusionsThese findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.

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Proceedings Article | 17 March 2023 Presentation

Non-invasive monitoring of cerebral hemodynamics using near-infrared spectroscopy and diffuse correlation spectroscopy during transcatheter aortic valve replacement surgery

Ailis Muldoon, Bryce Carr, Behzad Khajavi, Alyssa Martin, Mitchell Robinson, Julia Bertsch, Alexis Novak, Liza Parab, Ariel Mueller, Marissa Albanese, Jason Qu, Maria Angela Franceschini, Stefan Carp

Proceedings Volume 12364, 123640F (2023) https://doi.org/10.1117/12.2668694

KEYWORDS: Near infrared spectroscopy, Surgery, Hemodynamics, Spectroscopy, Oxygen, Injuries, Head, Electroencephalography, Doppler effect, Brain

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Proceedings Article | 7 March 2023 Presentation

Early prediction of neoadjuvant chemotherapy outcome with longitudinal breast diffuse optical tomography

Bin Deng, Ailis Muldoon, Jayne Cormier, Mansi Saksena, Steven Isakoff, Stefan Carp

Proceedings Volume PC12376, PC123760J (2023) https://doi.org/10.1117/12.2650855

KEYWORDS: Tumors, Breast, Diffuse optical tomography, Tissues, Imaging systems, Digital breast tomosynthesis, X-rays, X-ray imaging, Tissue optics, Optical imaging

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Proceedings Article | 5 March 2021 Presentation

Multimodal optical assessment of breast tumor aggressiveness and progression in murine models

Bin Deng, Ailis Muldoon, Rahul Pal, Alana Ross, Pamela Pantazopoulos, Zdravka Medarova, Anand T. Kumar, Stefan Carp

Proceedings Volume 11634, 116340B (2021) https://doi.org/10.1117/12.2577699

KEYWORDS: Tumors, Breast, Near infrared spectroscopy, Breast cancer, Tumor growth modeling, Spectroscopy, Luminescence, Indocyanine green, Imaging spectroscopy, Fluorescence spectroscopy

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