Qing Lyu
Assistant ProfessorCards
About
Research
Publications
2026
MCR-VQGAN: A Scalable and Cost-Effective Tau PET Synthesis Approach for Alzheimer’s Disease Imaging
Kim, Jin Young, et al. "MCR-VQGAN: A Scalable and Cost-Effective Tau PET Synthesis Approach for Alzheimer’s Disease Imaging." IEEE Access 99 (2026): 1-1.Peer-Reviewed Original ResearchRDDM: A Residual-Driven Drifting Model for High-Fidelity Low-Dose CT Denoising
Wang, Jianxu, Qing Lyu, and Ge Wang. "RDDM: A Residual-Driven Drifting Model for High-Fidelity Low-Dose CT Denoising." arXiv preprint arXiv:2605.17188 (2026).Peer-Reviewed Original ResearchPROMISE-AD: Progression-aware Multi-horizon Survival Estimation for Alzheimer's Disease Progression and Dynamic Tracking
Lyu, Qing, et al. "PROMISE-AD: Progression-aware Multi-horizon Survival Estimation for Alzheimer's Disease Progression and Dynamic Tracking." arXiv preprint arXiv:2604.28055 (2026).Peer-Reviewed Original ResearchMRI-to-CT synthesis using drifting models
Lyu, Qing, et al. "MRI-to-CT synthesis using drifting models." arXiv preprint arXiv:2603.28498 (2026).Peer-Reviewed Original Research
2025
A large scale multi-dataset investigation of brain metastases distribution based on primary cancer type
Lyu Q, Yuan H, Lin Z, Barcus R, Hudson J, Jiang Y, Kim J, Whitlow C. A large scale multi-dataset investigation of brain metastases distribution based on primary cancer type. BMC Cancer 2025, 25: 1821. PMID: 41291518, PMCID: PMC12648834, DOI: 10.1186/s12885-025-15222-5.Peer-Reviewed Original ResearchCancer brain metastasesBreast cancer brain metastasesBrain metastasesPattern of brain metastasesLung cancer brain metastasisMelanoma brain metastasesPrimary tumor typePrimary cancer typeTemporal lobeMetastasis distributionTumor volumeTumor typesPoor prognosisKidney cancerClinical challengeHeterogeneous distribution patternCancer typesMelanomaStatistical differenceBreastLungKidneyFrontal lobePredicting Immunotherapy-Induced Pneumonitis Based on Chest CT and Non-Imaging Data
Lyu Q, Yuan H, Lin Z, Ponnatapura J, Whitlow C. Predicting Immunotherapy-Induced Pneumonitis Based on Chest CT and Non-Imaging Data. Cancers 2025, 17: 2980. PMID: 41008824, PMCID: PMC12468472, DOI: 10.3390/cancers17182980.Peer-Reviewed Original ResearchImmune checkpoint inhibitorsICI-pneumonitisCT scanTreatment of non-small cell lung cancer patientsComputed tomographyNon-small cell lung cancer patientsRisk of developing pneumonitisCell lung cancer patientsHigh riskICI-based immunotherapyImmunotherapy-induced pneumonitisEarly identification of patientsSignificant survival benefitScreening computed tomographyEarly identificationIdentification of patientsReceiver operating characteristic curveArea under the receiver operating characteristic curveLung cancer patientsOperating characteristics curveCheckpoint inhibitorsChest CTSurvival benefitClinical featuresClinical dataMultimodal radiopathomics signature for prediction of response to immunotherapy-based combination therapy in gastric cancer using interpretable machine learning
Huang W, Wang X, Zhong R, Li Z, Zhou K, Lyu Q, Han J, Chen T, Islam M, Yuan Q, Ahmad M, Chen S, Chen C, Huang J, Xie J, Shen Y, Xiong W, Shen L, Xu Y, Yang F, Xu Z, Li G, Jiang Y. Multimodal radiopathomics signature for prediction of response to immunotherapy-based combination therapy in gastric cancer using interpretable machine learning. Cancer Letters 2025, 631: 217930. PMID: 40675469, DOI: 10.1016/j.canlet.2025.217930.Peer-Reviewed Original ResearchConceptsGastric cancerCombination therapyTreatment responseTreatment of advanced gastric cancerAdvanced gastric cancerPatient-specific treatment strategiesMemory B cellsKaplan-Meier analysisReceiver-operating-characteristic curveExternal validation cohortNon-surgical patientsImmune-related mechanismsLow-risk groupComputed tomography scan imagesImmune regulation pathwaysAdvanced-stageHER-2Predictive biomarkersMulticenter cohortValidation cohortB cellsPrognostic riskTreatment strategiesGC patientsMSI-HMRI-Based Radiomics Ensemble Model for Predicting Radiation Necrosis in Brain Metastasis Patients Treated with Stereotactic Radiosurgery and Immunotherapy
Chen Y, Helis C, Cramer C, Munley M, Choi A, Tan J, Xing F, Lyu Q, Whitlow C, Willey J, Chan M, Jiang Y. MRI-Based Radiomics Ensemble Model for Predicting Radiation Necrosis in Brain Metastasis Patients Treated with Stereotactic Radiosurgery and Immunotherapy. Cancers 2025, 17: 1974. PMID: 40563624, PMCID: PMC12191015, DOI: 10.3390/cancers17121974.Peer-Reviewed Original ResearchArea under the curveRadiation necrosisNegative predictive valuePositive predictive valueBrain metastasesConclusions:Occurrence of radiation necrosisRadiomic featuresPredictive valueResults:SRS sessionBrain metastasis patientsHighest area under the curveMethod:Radiosurgery sessionStereotactic radiosurgeryRadiation therapyMetastasis patientsTreatment modalitiesValidation cohortClinical factorsNeurological deficitsMetastasisClinical informationNecrosisMedical multimodal multitask foundation model for lung cancer screening
Niu C, Lyu Q, Carothers C, Kaviani P, Tan J, Yan P, Kalra M, Whitlow C, Wang G. Medical multimodal multitask foundation model for lung cancer screening. Nature Communications 2025, 16: 1523. PMID: 39934138, PMCID: PMC11814333, DOI: 10.1038/s41467-025-56822-w.Peer-Reviewed Original ResearchConceptsLung cancer screeningMultimodal dataCancer screeningState-of-the-art modelsCombination of multimodal dataState-of-the-artHigh-dimensional imagesLung cancer riskLow-dose computed tomographyMultitask learningMultitask datasetsModel architectureHealthcare qualityBig dataCancer riskClinical data typesData typesMortality risk predictionData elementsComputed tomographyRisk predictionMinimal dataFoundation modelClinical managementCT series
2024
Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.
Nan Y, Xing X, Wang S, Tang Z, Felder FN, Zhang S, Ledda RE, Ding X, Yu R, Liu W, Shi F, Sun T, Cao Z, Zhang M, Gu Y, Zhang H, Gao J, Wang P, Tang W, Yu P, Kang H, Chen J, Lu X, Zhang B, Mamalakis M, Prinzi F, Carlini G, Cuneo L, Banerjee A, Xing Z, Zhu L, Mesbah Z, Jain D, Mayet T, Yuan H, Lyu Q, Qayyum A, Mazher M, Wells A, Walsh SL, Yang G. Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge. Med Image Anal 2024, 97: 103253. PMID: 38968907, DOI: 10.1016/j.media.2024.103253.Peer-Reviewed Original Research
Get In Touch
Contacts
Email
Locations
100 College Street
Academic Office
New Haven, CT 06510