Kira Grogg, PhD
Research Scientist in Radiology and Biomedical ImagingDownloadHi-Res Photo
Cards
Appointments
Contact Info
About
Copy Link
Titles
Research Scientist in Radiology and Biomedical Imaging
Biography
Kira Grogg earned her Ph.D. in high-energy physics from the University of Wisconsin in 2011, where she conducted research at the Large Hadron Collider at CERN. She then began a postdoctoral fellowship at Massachusetts General Hospital/Harvard Medical School (MGH/HMS), where she investigated imaging patients using positron emission tomography (PET) immediately after proton therapy treatments. Her research aimed to verify the location of the proton radiation dose and was supported by an NCI K07 award. In 2015, Grogg became an Instructor at MGH/HMS and in 2019 completed a certificate program in Medical Physics and Instrumentation at HMS. She worked as a clinical medical physicist and researcher, obtaining ABSNM certification in Nuclear Medicine Physics in 2021. In 2024, Grogg joined the Yale PET Center as a Research Scientist.
Last Updated on April 17, 2025.
Appointments
Radiology & Biomedical Imaging
Research ScientistPrimary
Other Departments & Organizations
Education & Training
- Postdoctoral Fellow
- Massachusetts General Hospital (2015)
- PhD
- University of Wisconsin, Physics (2011)
- BA
- Carleton College, Physics and Astronomy (2005)
Advanced Training & Certifications
- ABSNM Diplomate
- American Board of Science in Nuclear Medicine
Research
Copy Link
Overview
Medical Research Interests
Positron-Emission Tomography; Radiotherapy
ORCID
0000-0002-4649-6377
Research at a Glance
Yale Co-Authors
Frequent collaborators of Kira Grogg's published research.
Publications Timeline
A big-picture view of Kira Grogg's research output by year.
Research Interests
Research topics Kira Grogg is interested in exploring.
Georges El Fakhri, PhD, DABR
Thibault Marin, PhD
Marc David Normandin, PhD
Chao Ma, PhD
Ruth Lim, MD
Xiaofeng Liu
29Publications
482Citations
Positron-Emission Tomography
Publications
2025
Predicting tumor recurrence site after reirradiation in head and neck cancer: a retrospective external validation of a published [18F]-FDG PET radiomic signature
Beddok A, Grogg K, Nioche C, Rozenblum L, Orlhac F, Calugaru V, Crehange G, Shih H, Marin T, Buvat I, El Fakhri G. Predicting tumor recurrence site after reirradiation in head and neck cancer: a retrospective external validation of a published [18F]-FDG PET radiomic signature. La Radiologia Medica 2025, 130: 1854-1863. PMID: 40833475, DOI: 10.1007/s11547-025-02072-1.Peer-Reviewed Original ResearchAltmetricConceptsHead and neck cancerPET radiomics signaturePositive predictive valueNeck cancerRadiomics signatureRecurrent head and neck cancerExternal cohortTumor recurrence siteDose escalationLocoregional failurePET radiomicsRecurrence siteMassachusetts General HospitalLIFEx softwareIndependent cohortRadiomic featuresOriginal cutoffPatientsPredictive valuePublished cutoffsPurposeThis studyCohortGeneral HospitalRecurrenceConclusionThe studyModeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model
Dong Y, Marin T, Zhuo Y, Najem E, Beddok A, Rozenblum L, Moteabbed M, Grogg K, Xing F, Woo J, Chen Y, Lim R, Liu X, Ma C, Fakhri G. Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model. Medical Physics 2025, 52: e17865. PMID: 40317577, PMCID: PMC12424543, DOI: 10.1002/mp.17865.Peer-Reviewed Original ResearchConceptsClinical target volumeGross tumor volumeClinical target volume delineationSoft tissue sarcomasInter-reader variabilityTissue sarcomasClinical target volume contoursMagnetic resonance imagingCTV delineationTarget volume delineationComputed tomographyTreatment of soft tissue sarcomasFluorodeoxyglucose positron emission tomographyCTV contoursTarget volumeVolume delineationT1-weighted magnetic resonance imagingRadiotherapy treatmentEnergy distanceHigh Dice indexPositron emission tomographyTumor volumeMicroscopic spreadFDG-PETTreatment planningEffects of Lung Expansion on Global and Regional Pulmonary Blood Volume in a Sheep Model of Acute Lung Injury
Zang M, Zeng C, Lagier D, Leng N, Grogg K, Motta-Ribeiro G, Laine A, Winkler T, Melo M. Effects of Lung Expansion on Global and Regional Pulmonary Blood Volume in a Sheep Model of Acute Lung Injury. Anesthesiology 2025, 142: 1071-1084. PMID: 39946655, PMCID: PMC12074886, DOI: 10.1097/aln.0000000000005412.Peer-Reviewed Original ResearchCitationsAltmetricConceptsPositive end-expiratory pressurePulmonary blood volumeLung expansionBlood volumeLung injurySystemic endotoxemiaMechanical ventilationRespiratory-gated positron emission tomographyVentilator-induced lung injuryModel of acute lung injuryDistribution of blood volumeAcute lung injuryLow-volume mechanical ventilationLung injury modelEnd-expiratory pressureQuantify blood volumePulmonary capillary blood volumeLow blood volumeRegional blood volumePositron emission tomographyVascular blood volumeCapillary blood volumeLung blood volumeCapillary closureEnd-inspirationGross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model
Dong Y, Marin T, Zhuo Y, Najem E, Moteabbed M, Xing F, Beddok A, Lahoud R, Rozenblum L, Ding Z, Liu X, Grogg K, Woo J, Chen Y, Lim R, Ma C, Fakhri G. Gross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model. Physics And Imaging In Radiation Oncology 2025, 33: 100734. PMID: 40123775, PMCID: PMC11926426, DOI: 10.1016/j.phro.2025.100734.Peer-Reviewed Original ResearchConceptsGross tumor volumeSoft tissue sarcomasTissue sarcomasGross tumor volume delineationManual GTV delineationsMagnetic resonance imagingComputed tomographyFluorodeoxyglucose positron emission tomographyGTV delineationT1-weighted magnetic resonance imagingSingle-modePositron emission tomographyMulti-modal medical imagesTumor volumeIntra-reader variabilityFDG-PETTreatment planningSarcomaEmission tomographyImaging modalitiesResonance imagingDiffusion modelDice indexReader variabilityPatients
2024
Integration of a continuously varying image-space PSF for a dual-panel ultra-high TOF-PET scanner
Chemli Y, Marin T, Orehar M, Dolenec R, Normandin M, Gascón D, Gola A, Grogg K, Pavón G, Razdevsek G, Pestotnik R, Fakhri G. Integration of a continuously varying image-space PSF for a dual-panel ultra-high TOF-PET scanner. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10656225.Peer-Reviewed Original ResearchConceptsGaussian mixture modelGaussian process regressionPoint spread functionAccurate image reconstructionMaximum likelihood estimation maximizationShift-variant convolutionsImage reconstructionMixture modelProcess regressionEstimation maximizationTime-of-flight (TOFPanel architectureSpread functionArchitectureParameter interpolationHigh resolution time-of-flight (TOFTOF-PET scannerBrain phantomFitting processPositron emission tomography scannerSimulated point sourcesConvolutionAlgorithmEffective diagnosisSize benefitsMechanical ventilation guided by driving pressure optimizes local pulmonary biomechanics in an ovine model
Lagier D, Zeng C, Kaczka D, Zhu M, Grogg K, Gerard S, Reinhardt J, Ribeiro G, Rashid A, Winkler T, Vidal Melo M. Mechanical ventilation guided by driving pressure optimizes local pulmonary biomechanics in an ovine model. Science Translational Medicine 2024, 16: eado1097. PMID: 39141699, DOI: 10.1126/scitranslmed.ado1097.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsPositive end-expiratory pressureMechanical ventilationFour-dimensional computed tomographyParenchymal strainsVentilator-induced lung injuryAcute respiratory distress syndromeRespiratory system driving pressureManagement of mechanical ventilationPositive end-expiratory pressure valuesRespiratory distress syndromeTidal overdistensionEnd-expiratory pressureAssociated with mortalityPulmonary complicationsLung biomechanicsLung massDistress syndromeClinical outcomesLung injuryComputed tomographyClinical managementGeneral anesthesiaLung collapseDriving pressureLung593: Using [18F]-FDG PET Radiomics to Predict Survival After Reirradiation in Head and Neck Cancer
Beddok A, Grogg K, Rozenblum L, Nioche C, Orhlac F, Calugaru V, Crehange G, Shih H, Marin T, Fakhri G, Buvat I. 593: Using [18F]-FDG PET Radiomics to Predict Survival After Reirradiation in Head and Neck Cancer. Radiotherapy And Oncology 2024, 194: s1210-s1212. DOI: 10.1016/s0167-8140(24)01168-x.Peer-Reviewed Original Research
2023
Dynamic lung aeration and strain with positive end-expiratory pressure individualized to maximal compliance versus ARDSNet low-stretch strategy: a study in a surfactant depletion model of lung injury
Zeng C, Zhu M, Motta-Ribeiro G, Lagier D, Hinoshita T, Zang M, Grogg K, Winkler T, Vidal Melo M. Dynamic lung aeration and strain with positive end-expiratory pressure individualized to maximal compliance versus ARDSNet low-stretch strategy: a study in a surfactant depletion model of lung injury. Critical Care 2023, 27: 307. PMID: 37537654, PMCID: PMC10401825, DOI: 10.1186/s13054-023-04591-7.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsAcute respiratory distress syndromeFour-dimensional computed tomographyPEEP strategyLung aerationEnd-inspirationLung injuryTidal recruitmentComputed tomographyRegistration-based techniqueEnd-expirationCyclic recruitmentMechanisms of ventilator-induced lung injuryVentilator-induced lung injuryPotential outcome benefitsBackgroundPositive end-expiratory pressureRespiratory distress syndromeHigh-resolution CTRespiratory system complianceEnd-expiratory pressureSaline lung lavageLung massDistress syndromeInspiratory increaseRecruitable lungSurfactant depletion modelImpact of motion correction on [18F]-MK6240 tau PET imaging
Tiss A, Marin T, Chemli Y, Spangler-Bickell M, Gong K, Lois C, Petibon Y, Landes V, Grogg K, Normandin M, Becker A, Thibault E, Johnson K, Fakhri G, Ouyang J. Impact of motion correction on [18F]-MK6240 tau PET imaging. Physics In Medicine And Biology 2023, 68: 105015. PMID: 37116511, PMCID: PMC10278956, DOI: 10.1088/1361-6560/acd161.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMotion correctionPET quantitationImpact of motion correctionList-mode reconstructionMotion correction methodList-mode dataMotion-corrected imagesEffect of motion correctionVoxel displacementsPhantom experimentsOptical tracking dataLong acquisitionBrain PET scansSlow motionImage qualityPET imagingPositron emission tomographyCorrectionMotionCorrection methodRates of tau accumulationHead motionMotion metricsPhantomPositronEffect of PEEP Setting with Minimal Driving Pressure on the Distribution of Voxel-level Lung Strain and Aeration Measured with Dynamic Computed Tomography (CT) in Large Animal Normal and Injured Lungs
Zeng C, Lagier D, Zhu M, Rashid A, Winkler T, Grogg K, Gerard S, Kaczka D, Reinhardt J, Melo M. Effect of PEEP Setting with Minimal Driving Pressure on the Distribution of Voxel-level Lung Strain and Aeration Measured with Dynamic Computed Tomography (CT) in Large Animal Normal and Injured Lungs. American Journal Of Respiratory And Critical Care Medicine 2023, 207: a6061-a6061. DOI: 10.1164/ajrccm-conference.2023.207.1_meetingabstracts.a6061.Peer-Reviewed Original Research
Academic Achievements & Community Involvement
Copy Link
News
Copy Link
Get In Touch
Copy Link
Contacts
Email
Events
Aug 202624-25Multiple Days
Everyone All DaySpeakers to be announced.