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677 results on '"Yankelevitz, David"'

1. AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CACTM) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis

Author

Naghavi, Morteza, Reeves, Anthony, Budoff, Matthew, Li, Dong, Atlas, Kyle, Zhang, Chenyu, Atlas, Thomas, Roy, Sion K, Henschke, Claudia I, Wong, Nathan D, Defilippi, Christopher, Levy, Daniel, and Yankelevitz, David F

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Heart Disease, Aging, Cardiovascular, Networking and Information Technology R&D (NITRD), Prevention, Heart Disease - Coronary Heart Disease, Machine Learning and Artificial Intelligence, Atherosclerosis, Humans, Female, Male, Peptide Fragments, Natriuretic Peptide, Brain, Aged, Heart Failure, Predictive Value of Tests, Coronary Artery Disease, Middle Aged, Risk Factors, Biomarkers, Vascular Calcification, Risk Assessment, Prognosis, United States, Time Factors, Incidence, Aged, 80 and over, Computed Tomography Angiography, Artificial Intelligence, Coronary Angiography, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Multidetector Computed Tomography, Asymptomatic Diseases, Artificial intelligence, Coronary artery calcium, Heart failure, Left ventricular volume, NT-proBNP, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Applied computing
Abstract

IntroductionCoronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF).MethodsWe applied AI-CAC to 5750 CAC scans of asymptomatic individuals (52% female, White 40%, Black 26%, Hispanic 22% Chinese 12%) free of known cardiovascular disease at the MESA baseline examination (2000-2002). We used the 15-year outcomes data and compared the time-dependent area under the curve (AUC) of AI-CAC volumetry versus NT-proBNP, Agatston score, and 9 known clinical risk factors (age, gender, diabetes, current smoking, hypertension medication, systolic and diastolic blood pressure, LDL, HDL for predicting incident HF over 15 years.ResultsOver 15 years of follow-up, 256 HF events accrued. The time-dependent AUC [95% CI] at 15 years for predicting HF with AI-CAC all chambers volumetry (0.86 [0.82,0.91]) was significantly higher than NT-proBNP (0.74 [0.69, 0.77]) and Agatston score (0.71 [0.68, 0.78]) (p ​

Published
2024

2. Prospective Cohort Study to Compare Long-Term Lung Cancer-Specific and All-Cause Survival of Clinical Early Stage (T1a–b; ≤20 mm) NSCLC Treated by Stereotactic Body Radiation Therapy and Surgery

Author

Flores, Raja, Kaufman, Andrew, Lee, Dong-Seok, Nicastri, Daniel, Wolf, Andrea, Song, Kimberly, Rosenzweig, Kenneth, Gomez, Jorge, Samstein, Robert, Dutta, Pinaki, Beasley, Mary Beth, Zakowski, Maureen, Chung, Michael, Yankelevitz, David F., Henschke, Claudia I., Taioli, Emanuela, Schwartz, Rebecca, Chan, Huiwen, Zhu, Jeffrey, Kantor, Sydney, Woode, Sydney, Hakami, Ardeshir, Buyuk, Arzu, Friedman, Adie, Dreifuss, Ronald, Verzosa, Stacey, Yakubox, Mariya, Aloferdova, Karina, Stacey, Patricia, De Nobrega, Simone, Lentini, Lauren, Pass, Harvey, Cooper, Benjamin, Moreirea, Andre, Sorensen, Audrey, Kohman, Leslie, Dunton, Robert, Wallen, Jason, Curtiss, Christopher, Scalzetti, Ernest, Ellinwood, Linda, Tannous, Henry, Connery, Cliff P., Torres, Emilo, Cruzer, Dan, Gendron, Bruce, Alyea, Sonya, Krumholtz, Pramila, Watkins, Ammara, Servais, Elliot, Stock, Cameron, McKee, Andrea, Lopez, Edilin, Hsu, Howard, Hunter, Kaudia, Lemons, Jeffrey, Nixon, Asa, Osa, Etin-Osa, Lee, Paul, Hyman, Kevin, Jurado, Julisa, Zeltman, David, Glassman, Lawrence, Sharma, Rajiv, Singh, Vijay, Milhelis, Efstathia, Karan, Nandanee, Rzyman, Witold, Dziedzic, Robert, Henschke, Claudia, Yankelevitz, David, Jirapatnakul, Artit, Yip, Rowena, Zulueta, Javier J., Reeves, A.P., Altorki, Nasser K., Smith, James P., Libby, Daniel M., Pasmantier, Mark, Markowitz, Steven, Miller, Albert, Deval, Jose Cervera, Shaham, Dorith, Seijo, Luis, Bastarika, Gorka, Montuenga, Luis M., Spring, Silver, Aylesworth, Cheryl, Klingler, Karl, Schöb, Othmar, Andaz, Shahriyour, Straznicka, Michaela, Chin, Cynthia, Weiser, Todd, Sone, Shusuke, Hanaoka, Takaomi, Roberts, Heidi, Patsios, Demetris, Scopetuolo, M., Brown, Andrew, Wu, Ning, Cole, Enser, Yeh, Diana, Luedke, Dan, Liu, Xueguo, Herzog, Gary, Aye, Ralph, Rifkin, Matthew, Veronesi, Giula, Infante, Maurizio, Vafai, Davood, Kopel, Samuel, Taylor, Jana, Thurer, Richard, Villamizar, Nestor, Austin, John H.M., Pearson, Gregory D.N., Klippenstein, Donald, Litwin, Alan, Loud, Peter A., Kohman, Leslie J., Scalzetti, Ernest M., Khan, Arfa, Shah, Rakesh, Mayfield, William, Frumiento, Carmine, Smith, Michael V., Thorsen, M. Kristin, Hansen, Richard, Naidich, David, McGuinness, Georgeann, Widmann, Mark, Korst, Robert, Lowry, Joseph, Salvatore, Mary, Walsh, James, Bertsch, David, Scheinberg, Paul, Sheppard, Barry, Cecchi, Gary, Ginsberg, Michelle S., Welch, Laura, Raz, Dan J., Rotter, Arnold, Connery, Cliff, Matalon, Terence A.S., Cheung, Edson H., Glassberg, Robert, Olsen, David, Mullen, David, Odzer, Shari-Lynn, Wiernik, Peter H., Ray, Daniel, DeCunzo, Louis, Endress, Carmen, Vacca, Anthony, Kondapaneni, M., Lim, Melissa, Kalafer, Michael, Green, Jeremy, Yoder, Mark, Shah, Palmi, Camacho, Elmer, O’Brien, James, Willey, James C., Gordon, David, Kocha, Albert, Sun, Qi, Li, Pengfei, and Flores, Raja M.

Published
2024
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3. Rural barriers and facilitators of lung cancer screening program implementation in the veterans health administration: a qualitative study.

Author

Lewis, Jennifer, Bonnet, Kemberlee, Schlundt, David, Byerly, Susan, Lindsell, Christopher, Henschke, Claudia, Yankelevitz, David, York, Sally, Hendler, Fred, Dittus, Robert, Vogus, Timothy, Kripalani, Sunil, Moghanaki, Drew, Audet, Carolyn, Roumie, Christianne, and Spalluto, Lucy

Subjects
RE-AIM, barriers, facilitators, implementation science, low-dose CT, lung cancer screening, rural
Abstract

INTRODUCTION: To assess healthcare professionals perceptions of rural barriers and facilitators of lung cancer screening program implementation in a Veterans Health Administration (VHA) setting through a series of one-on-one interviews with healthcare team members. METHODS: Based on measures developed using Reach Effectiveness Adoption Implementation Maintenance (RE-AIM), we conducted a cross-sectional qualitative study consisting of one-on-one semi-structured telephone interviews with VHA healthcare team members at 10 Veterans Affairs medical centers (VAMCs) between December 2020 and September 2021. An iterative inductive and deductive approach was used for qualitative analysis of interview data, resulting in the development of a conceptual model to depict rural barriers and facilitators of lung cancer screening program implementation. RESULTS: A total of 30 interviews were completed among staff, providers, and lung cancer screening program directors and a conceptual model of rural barriers and facilitators of lung cancer screening program implementation was developed. Major themes were categorized within institutional and patient environments. Within the institutional environment, participants identified systems-level (patient communication, resource availability, workload), provider-level (attitudes and beliefs, knowledge, skills and capabilities), and external (regional and national networks, incentives) barriers to and facilitators of lung cancer screening program implementation. Within the patient environment, participants revealed patient-level (modifiable vulnerabilities) barriers and facilitators as well as ecological modifiers (community) that influence screening behavior. DISCUSSION: Understanding rural barriers to and facilitators of lung cancer screening program implementation as perceived by healthcare team members points to opportunities and approaches for improving lung cancer screening reach, implementation and effectiveness in VHA rural settings.

Published
2023

4. Opportunistic AI-enabled automated bone mineral density measurements in lung cancer screening and coronary calcium scoring CT scans are equivalent

Author

Naghavi, Morteza, De Oliveira, Isabel, Mao, Song Shou, Jaberzadeh, Amirhossein, Montoya, Juan, Zhang, Chenyu, Atlas, Kyle, Manubolu, Venkat, Montes, Marlon, Li, Dong, Atlas, Thomas, Reeves, Anthony, Henschke, Claudia, Yankelevitz, David, and Budoff, Matthew

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Lung Cancer, Cancer, Lung, Cardiovascular, Osteoporosis, Bone mineral density, Artificial intelligence, Deep learning, Opportunistic, Coronary artery calcium score, Quantitative computed tomography, Osteopenia, Cardiovascular Screening, Lung cancer screening
Abstract

Rationale and objectivesWe previously reported a novel manual method for measuring bone mineral density (BMD) in coronary artery calcium (CAC) scans and validated our method against Dual X-Ray Absorptiometry (DEXA). Furthermore, we have developed and validated an artificial intelligence (AI) based automated BMD (AutoBMD) measurement as an opportunistic add-on to CAC scans that recently received FDA approval. In this report, we present evidence of equivalency between AutoBMD measurements in cardiac vs lung CT scans.Materials and methodsAI models were trained using 132 cases with 7649 (3 mm) slices for CAC, and 37 cases with 21918 (0.5 mm) slices for lung scans. To validate AutoBMD against manual measurements, we used 6776 cases of BMD measured manually on CAC scans in the Multi-Ethnic Study of Atherosclerosis (MESA). We then used 165 additional cases from Harbor UCLA Lundquist Institute to compare AutoBMD in patients who underwent both cardiac and lung scans on the same day.ResultsMean±SD for age was 69 ± 9.4 years with 52.4% male. AutoBMD in lung and cardiac scans, and manual BMD in cardiac scans were 153.7 ± 43.9, 155.1 ± 44.4, and 163.6 ± 45.3 g/cm3, respectively (p = 0.09). Bland-Altman agreement analysis between AutoBMD lung and cardiac scans resulted in 1.37 g/cm3 mean differences. Pearson correlation coefficient between lung and cardiac AutoBMD was R2 = 0.95 (p

Published
2023

5. AI-enabled left atrial volumetry in coronary artery calcium scans (AI-CACTM) predicts atrial fibrillation as early as one year, improves CHARGE-AF, and outperforms NT-proBNP: The multi-ethnic study of atherosclerosis

Author

Naghavi, Morteza, Yankelevitz, David, Reeves, Anthony P., Budoff, Matthew J., Li, Dong, Atlas, Kyle, Zhang, Chenyu, Atlas, Thomas L., Lirette, Seth, Wasserthal, Jakob, Roy, Sion K., Henschke, Claudia, Wong, Nathan D., Defilippi, Christopher, Heckbert, Susan R., and Greenland, Philip

Published
2024
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9. Using the Framework for Reporting Adaptations and Modifications-Expanded (FRAME) to study adaptations in lung cancer screening delivery in the Veterans Health Administration: a cohort study

Author

Strayer, Thomas E., Spalluto, Lucy B., Burns, Abby, Lindsell, Christopher J., Henschke, Claudia I., Yankelevitz, David F., Moghanaki, Drew, Dittus, Robert S., Vogus, Timothy J., Audet, Carolyn, Kripalani, Sunil, Roumie, Christianne L., and Lewis, Jennifer A.

Published
2023
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12. Association of Rurality With Annual Repeat Lung Cancer Screening in the Veterans Health Administration.

Author

Spalluto, Lucy, Lewis, Jennifer, Samuels, Lauren, Callaway-Lane, Carol, Matheny, Michael, Denton, Jason, Robles, Jennifer, Dittus, Robert, Yankelevitz, David, Henschke, Claudia, Massion, Pierre, Moghanaki, Drew, and Roumie, Christianne

Subjects
Lung cancer screening, Veterans, Veterans Health Administration, lung cancer, rural, Early Detection of Cancer, Humans, Lung Neoplasms, Retrospective Studies, Rural Population, United States, Veterans, Veterans Health
Abstract

PURPOSE: Lung cancer causes the largest number of cancer-related deaths in the United States. Lung cancer incidence rates, mortality rates, and rates of advanced stage disease are higher among those who live in rural areas. Known disparities in lung cancer outcomes between rural and nonrural populations may be in part because of barriers faced by rural populations. The authors tested the hypothesis that among Veterans who receive initial lung cancer screening, rural Veterans would be less likely to complete annual repeat screening than nonrural Veterans. METHODS: A retrospective cohort study was conducted of 10 Veterans Affairs medical centers from 2015 to 2019. Rural and nonrural Veterans undergoing lung cancer screening were identified. Rural status was defined using the rural-urban commuting area codes. The primary outcome was annual repeat lung cancer screening in the 9- to 15-month window (primary analysis) and 31-day to 18-month window (sensitivity analysis) after the first documented lung cancer screening. To examine rurality as a predictor of annual repeat lung cancer screening, multivariable logistic regression models were used. RESULTS: In the final analytic sample of 11,402 Veterans, annual repeat lung cancer screening occurred in 27.7% of rural Veterans (641 of 2,316) and 31.8% of nonrural Veterans (2,891 of 9,086) (adjusted odds ratio: 0.86; 95% confidence interval: 0.73-1.03). Similar results were seen in the sensitivity analysis, with 41.6% of rural Veterans (963 of 2,316) versus 45.2% of nonrural Veterans (4,110 of 9,086) (adjusted odds ratio: 0.88; 95% confidence interval: 0.73-1.04) having annual repeat screening in the expanded 31-day to 18-month window. CONCLUSIONS: Among a national cohort of Veterans, rural residence was associated with numerically lower odds of annual repeat lung cancer screening than nonrural residence. Continued, intentional outreach efforts to increase annual repeat lung cancer screening among rural Veterans may offer an opportunity to decrease deaths from lung cancer.

Published
2022

13. From the International Association for the Study of Lung Cancer Early Detection and Screening Committee: Terminology Issues in Screening and Early Detection of Lung Cancer—International Association for the Study of Lung Cancer Early Detection and Screening Committee Expert Group Recommendations

Author

Yang, Dawei, Zulueta, Javier, Viola, Lucia, Mohan, Anant, Cavic, Milena, Balata, Haval, Kazerooni, Ella, Sales dos Santos, Ricardo, Kerpel-Fronius, Anna, Henschke, Claudia, Ventura, Luigi, Jiang, Long, Fraser, Anne, Koegelenberg, Coenraad FN., Tammemägi, Martin, Lam, Stephen, Huber, Rudolf, Huber, Rudolf M., Borondy Kitts, Andrea, Field, John K., Kazerooni, Ella A., Smith, Robert A., Taioli, Emanuela, and Yankelevitz, David

Published
2024
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14. The International Association for the Study of Lung Cancer Early Lung Imaging Confederation Open-Source Deep Learning and Quantitative Measurement Initiative

Author

Lam, Stephen, Wynes, Murry W., Connolly, Casey, Ashizawa, Kazuto, Atkar-Khattra, Sukhinder, Belani, Chandra P., DiNatale, Domenic, Henschke, Claudia I., Hochhegger, Bruno, Jacomelli, Claudio, Jelitto, Małgorzata, Jirapatnakul, Artit, Kelly, Karen L., Krishnan, Karthik, Kobayashi, Takeshi, Logan, Jacqueline, Mattos, Juliane, Mayo, John, McWilliams, Annette, Mitsudomi, Tetsuya, Pastorino, Ugo, Polańska, Joanna, Rzyman, Witold, Sales dos Santos, Ricardo, Scagliotti, Giorgio V., Wakelee, Heather, Yankelevitz, David F., Field, John K., Mulshine, James L., and Avila, Ricardo

Published
2024
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15. New or enlarging hiatal hernias after thoracic surgery for early lung cancer

Author

Flores, Raja, Kaufman, Andrew, Lee, Dong-Seok, Nicastri, Daniel, Wolf, Andrea, Song, Kimberly, Rosenzweig, Kenneth, Gomez, Jorge, Beasley, Mary Beth, Zakowski, Maureen, Chung, Michael, Yankelevitz, David F., Henschke, Claudia I., Taioli, Emanuela, Schwartz, Rebecca, Chan, Huiwen, Zhu, Jeffrey, Kantor, Sydney, Adler, Shana, Raad, Wissam, Buyuk, Zrzu, Friedman, Adie, Dreifuss, Ronald, Verzosa, Stacey, Yakubox, Mariya, Aloferdova, Karina, Stacey, Patricia, De Nobrega, Simone, Hakami, Ardeshir, Pass, Harvey, Crawford, Berne, Donnington, Jessica, Cooper, Benjamin, Moreirea, Andre, Sorensen, Audrey, Kohman, Leslie, Dunton, Robert, Wallen, Jason, Curtiss, Christopher, Scalzetti, Ernest, Ellinwood, Linda, Connery, Clifford P., Torres, Emilo, Cruzer, Dan, Gendron, Bruce, Alyea, Sonya, Lackaye, Daniel, Studer, Lauren, Henschke, Claudia, Yankelevitz, David, Becker, Betsy, Jirapatnakul, Artit, Yip, Rowena, You, Nan, Libby, Daniel M., Smith, James P., Pasmantier, Mark, Reeves, A.P., Markowitz, Steven, Miller, Albert, Deval, Jose Cervera, Roberts, Heidi, Patsios, Demetris, Sone, Shusuke, Hanaoka, Takaomi, Zulueta, Javier, de-Torres, Juan P., Lozano, Maria D., Aye, Ralph, Manning, Kristin, Care, Christiana, Bauer, Thomas, Canitano, Stefano, Giunta, Salvatore, Cole, Enser, Klingler, Karl, Austin, John H.M., Pearson, Gregory D.N., Shaham, Dorith, Aylesworth, Cheryl, Meyers, Patrick, Andaz, Shahriyour, Vafai, Davood, Naidich, David, McGuinness, Georgeann, Sheppard, Barry, Rifkin, Matthew, Thorsen, M. Kristin, Hansen, Richard, Kopel, Samuel, Mayfield, William, Luedke, Dan, Klippenstein, Donald, Litwin, Alan, Loud, Peter A., Kohman, Leslie J., Scalzetti, Ernest M., Thurer, Richard, Villamizar, Nestor, Khan, Arfa, Shah, Rakesh, Liu, Xueguo, Herzog, Gary, Yeh, Diana, Wu, Ning, Lowry, Joseph, Salvatore, Mary, Frumiento, Carmine, Mendelson, David S., Smith, Michael V., Korst, Robert, Taylor, Jana, Ginsberg, Michelle S., Straznicka, Michaela, Widmann, Mark, Cecchi, Gary, Matalon, Terence A.S., Scheinberg, Paul, Odzer, Shari-Lynn, Olsen, David, Grannis, Fred, Rotter, Arnold, Ray, Daniel, Mullen, David, Wiernik, Peter H., Cheung, Edson H., Lim, Melissa, DeCunzo, Louis, Glassberg, Robert, Endress, Carmen, Yoder, Mark, Shah, Palmi, Welch, Laura, Kalafer, Michael, Green, Jeremy, Walsh, James, Bertsch, David, Camacho, Elmer, Chin, Cynthia, O'Brien, James, Willey, James C., Song, Kimberly J., Cai, Qiang, Zhu, Yeqing, Singh, Ayushi, and Lewis, Erik E.

Published
2022
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16. The Association of Organizational Readiness With Lung Cancer Screening Utilization

Author

Lewis, Jennifer A., Samuels, Lauren R., Weems, Jacy, Park, Daniel, Winter, Robert, Lindsell, Christopher J., Callaway-Lane, Carol, Audet, Carolyn, Slatore, Christopher G., Wiener, Renda Soylemez, Dittus, Robert S., Kripalani, Sunil, Yankelevitz, David F., Henschke, Claudia I., Moghanaki, Drew, Matheny, Michael E., Vogus, Timothy J., Roumie, Christianne L., and Spalluto, Lucy B.

Published
2023
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20. Neoadjuvant clinical trials provide a window of opportunity for cancer drug discovery

Author

Marron, Thomas U., Galsky, Matthew D., Taouli, Bachir, Fiel, Maria Isabel, Ward, Stephen, Kim, Edward, Yankelevitz, David, Doroshow, Deborah, Guttman-Yassky, Emma, Ungar, Benjamin, Mehandru, Saurabh, Golas, Benjamin J., Labow, Daniel, Sfakianos, John, Nair, Sujit S., Chakravarty, Dimple, Buckstein, Michael, Song, Xiaoyu, Kenigsberg, Effi, Gnjatic, Sacha, Brown, Brian D., Sparano, Joseph, Tewari, Ashutosh, Schwartz, Myron, Bhardwaj, Nina, and Merad, Miriam

Published
2022
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21. Lung Cancer and Severe Acute Respiratory Syndrome Coronavirus 2 Infection: Identifying Important Knowledge Gaps for Investigation

Author

Rolfo, Christian, Meshulami, Noy, Russo, Alessandro, Krammer, Florian, García-Sastre, Adolfo, Mack, Philip C., Gomez, Jorge E., Bhardwaj, Nina, Benyounes, Amin, Sirera, Rafael, Moore, Amy, Rohs, Nicholas, Henschke, Claudia I., Yankelevitz, David, King, Jennifer, Shyr, Yu, Bunn, Paul A., Jr., Minna, John D., and Hirsch, Fred R.

Published
2022
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23. Survival with Parenchymal and Pleural Invasion of Non–Small Cell Lung Cancers Less than 30 mm

Author

Henschke, Claudia I., Yankelevitz, David F., Yip, Rowena, Salvatore, Mary, Flores, Raja, Wolf, Andrea, Chen, Mildred, Libby, Daniel M., Smith, James P., Pasmantier, Mark, Reeves, A.P., Markowitz, Steven, Miller, Albert, Deval, Jose Cervera, Roberts, Heidi, Patsios, Demetris, Sone, Shusuke, Hanaoka, Takaomi, Zulueta, Javier, de-Torres, Juan P., Lozano, Maria D., Aye, Ralph, Manning, Kristin, Bauer, Thomas, Canitano, Stefano, Giunta, Salvatore, Cole, Enser, Klingler, Karl, Austin, John H.M., Pearson, Gregory D.N., Shaham, Dorith, Aylesworth, Cheryl, Meyers, Patrick, Andaz, Shahriyour, Vafai, Davood, Naidich, David, McGuinness, Georgeann, Sheppard, Barry, Rifkin, Matthew, Thorsen, M. Kristin, Hansen, Richard, Kopel, Samuel, Mayfield, William, Luedke, Dan, Klippenstein, Donald, Litwin, Alan, Loud, Peter A., Kohman, Leslie J., Scalzetti, Ernest M., Thurer, Richard, Villamizar, Nestor, Khan, Arfa, Shah, Rakesh, Liu, Xueguo, Herzog, Gary, Yeh, Diana, Wu, Ning, Lowry, Joseph, Frumiento, Carmine, Mendelson, David S., Smith, Michael V., Korst, Robert, Taylor, Jana, Ginsberg, Michelle S., Straznicka, Michaela, Widmann, Mark, Cecchi, Gary, Matalon, Terence A.S., Scheinberg, Paul, Odzer, Shari-Lynn, Olsen, David, Grannis, Fred, Rotter, Arnold, Ray, Daniel, Mullen, David, Wiernik, Peter H., Cheung, Edson H., Lim, Melissa, DeCunzo, Louis, Glassberg, Robert, Pass, Harvey, Endress, Carmen, Yoder, Mark, Shah, Palmi, Welch, Laura, Kalafer, Michael, Green, Jeremy, Walsh, James, Bertsch, David, Camacho, Elmer, Chin, Cynthia, O’Brien, James, Willey, James C., Ma, Teng, Flores, Raja M., and Yankelevitz, David

Published
2019
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25. The importance of low-dose CT screening to identify emphysema in asymptomatic participants with and without a prior diagnosis of COPD

Author

Henschke, Claudia I., Yankelevitz, David F., Yip, Rowena, Jirapatnakul, Artit, Flores, Raja, Wolf, Andrea, Libby, Daniel M., Smith, James P., Pasmantier, Mark, Reeves, A.P., Markowitz, Steven, Miller, Albert, Deval, Jose Cervera, Roberts, Heidi, Patsios, Demetris, Sone, Shusuke, Hanaoka, Takaomi, Zulueta, Javier, de-Torres, Juan P., Lozano, Maria D., Aye, Ralph, Manning, Kristin, Bauer, Thomas, Canitano, Stefano, Giunta, Salvatore, Cole, Enser, Klingler, Karl, Austin, John H.M., Pearson, Gregory D.N., Shaham, Dorith, Aylesworth, Cheryl, Meyers, Patrick, Andaz, Shahriyour, Vafai, Davood, Naidich, David, McGuinness, Georgeann, Sheppard, Barry, Rifkin, Matthew, Thorsen, M. Kristin, Hansen, Richard, Kopel, Samuel, Mayfield, William, Luedke, Dan, Klippenstein, Donald, Litwin, Alan, Loud, Peter A., Kohman, Leslie J., Scalzetti, Ernest M., Thurer, Richard, Villamizar, Nestor, Khan, Arfa, Shah, Rakesh, Liu, Xueguo, Herzog, Gary, Yeh, Diana, Wu, Ning, Lowry, Joseph, Salvatore, Mary, Frumiento, Carmine, Mendelson, David S., Smith, Michael V., Korst, Robert, Taylor, Jana, Ginsberg, Michelle S., Straznicka, Michaela, Widmann, Mark, Cecchi, Gary, Matalon, Terence A.S., Scheinberg, Paul, Odzer, Shari-Lynn, Olsen, David, Grannis, Fred, Rotter, Arnold, Ray, Daniel, Mullen, David, Wiernik, Peter H., Cheung, Edson H., Lim, Melissa, DeCunzo, Louis, Glassberg, Robert, Pass, Harvey, Endress, Carmen, Yoder, Mark, Shah, Palmi, Welch, Laura, Kalafer, Michael, Green, Jeremy, Walsh, James, Bertsch, David, Camacho, Elmer, Chin, Cynthia, O'Brien, James, Willey, James C., Steiger, David, and Siddiqi, M. Faisal

Published
2021
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29. Protocol to evaluate an enterprise-wide initiative to increase access to lung cancer screening in the Veterans Health Administration

Author

Lewis, Jennifer A., Spalluto, Lucy B., Henschke, Claudia I., Yankelevitz, David F., Aguayo, Samuel M., Morales, Providencia, Avila, Rick, Audet, Carolyn M., Prusaczyk, Beth, Lindsell, Christopher J., Callaway-Lane, Carol, Dittus, Robert S., Vogus, Timothy J., Massion, Pierre P., Limper, Heather M., Kripalani, Sunil, Moghanaki, Drew, and Roumie, Christianne L.

Published
2021
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31. 2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans

Author

Hecht, Harvey S, Cronin, Paul, Blaha, Michael J, Budoff, Matthew J, Kazerooni, Ella A, Narula, Jagat, Yankelevitz, David, and Abbara, Suhny

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Health Services, Biomedical Imaging, Clinical Research, 7.3 Management and decision making, Management of diseases and conditions, Generic health relevance, Cardiovascular, Good Health and Well Being, Coronary Artery Disease, Coronary Vessels, Humans, Societies, Medical, Tomography, X-Ray Computed, Vascular Calcification, Coronary artery disease, Coronary artery calcium, Computed tomography, Nuclear Medicine & Medical Imaging, Cardiovascular medicine and haematology, Clinical sciences
Abstract

The Society of Cardiovascular Computed Tomography (SCCT) and the Society of Thoracic Radiology (STR) have jointly produced this document. Experts in this subject have been selected from both organizations to examine subject-specific data and write this guideline in partnership. A formal literature review, weighing the strength of evidence has been performed. When available, information from studies on cost was considered. Computed tomography (CT) acquisition, CAC scoring methodologies and clinical outcomes are the primary basis for the recommendations in this guideline. This guideline is intended to assist healthcare providers in clinical decision making. The recommendations reflect a consensus after a thorough review of the best available current scientific evidence and practice patterns of experts in the field and are intended to improve patient care while acknowledging that situations arise where additional information may be needed to better inform patient care.

Published
2017

32. Erratum to “2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans a report of the society of Cardiovascular Computed Tomography and Society of Thoracic Radiology” [J. Cardiovasc. Comput. Tomogr. 11 (2017) 74–84]

Author

Hecht, Harvey S, Cronin, Paul, Blaha, Michael J, Budoff, Matthew J, Kazerooni, Ella A, Narula, Jagat, Yankelevitz, David, and Abbara, Suhny

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Cardiovascular, Good Health and Well Being, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Applied computing
Abstract

In the January/February 2017 issue of Journal of Cardiovascular Computed Tomography, in the Guidelines article titled ‘‘2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans a report of the society of Cardiovascular Computed Tomography and Society of Thoracic Radiology’’ (2017; 11:74–84; http://dx.doi.org/10.1016/j.jcct.2016.11.003), Appendix 1 containing the disclosures was not included. The appendix has been added to the online version of the article.

Published
2017

33. 2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans: A report of the Society of Cardiovascular Computed Tomography and Society of Thoracic Radiology

Author

Hecht, Harvey S, Cronin, Paul, Blaha, Michael J, Budoff, Matthew J, Kazerooni, Ella A, Narula, Jagat, Yankelevitz, David, and Abbara, Suhny

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Biomedical Imaging, Heart Disease, Cardiovascular, Clinical Research, Heart Disease - Coronary Heart Disease, Generic health relevance, Good Health and Well Being, Adult, Aged, Consensus, Coronary Artery Disease, Humans, Incidental Findings, Middle Aged, Predictive Value of Tests, Prognosis, Radiography, Thoracic, Reproducibility of Results, Risk Assessment, Risk Factors, Severity of Illness Index, Tomography, X-Ray Computed, Vascular Calcification, Coronary artery disease, Coronary artery calcium, Computed tomography, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Applied computing
Abstract

The Society of Cardiovascular Computed Tomography (SCCT) and the Society of Thoracic Radiology (STR) have jointly produced this document. Experts in this subject have been selected from both organizations to examine subject-specific data and write this guideline in partnership. A formal literature review, weighing the strength of evidence has been performed. When available, information from studies on cost was considered. Computed tomography (CT) acquisition, CAC scoring methodologies and clinical outcomes are the primary basis for the recommendations in this guideline. This guideline is intended to assist healthcare providers in clinical decision making. The recommendations reflect a consensus after a thorough review of the best available current scientific evidence and practice patterns of experts in the field and are intended to improve patient care while acknowledging that situations arise where additional information may be needed to better inform patient care.

Published
2017

39. The International Association for the Study of Lung Cancer Consensus Statement on Optimizing Management of EGFR Mutation-Positive Non-Small Cell Lung Cancer: Status in 2016.

Author

Tan, Daniel SW, Yom, Sue S, Tsao, Ming S, Pass, Harvey I, Kelly, Karen, Peled, Nir, Yung, Rex C, Wistuba, Ignacio I, Yatabe, Yasushi, Unger, Michael, Mack, Philip C, Wynes, Murry W, Mitsudomi, Tetsuya, Weder, Walter, Yankelevitz, David, Herbst, Roy S, Gandara, David R, Carbone, David P, Bunn, Paul A, Mok, Tony SK, and Hirsch, Fred R

Subjects
Humans, Carcinoma, Non-Small-Cell Lung, Brain Neoplasms, Lung Neoplasms, Protein Kinase Inhibitors, Consensus, Drug Resistance, Neoplasm, Mutation, ErbB Receptors, Brain metastases, EGFR mutation, Non–small cell lung cancer, Resistance, Therapy, Tyrosine kinase inhibitor, Non-small cell lung cancer, Carcinoma, Non-Small-Cell Lung, Drug Resistance, Neoplasm, Receptor, Epidermal Growth Factor, Lung Cancer, Lung, Cancer, Clinical Research, Oncology & Carcinogenesis, Clinical Sciences, Cardiorespiratory Medicine and Haematology, Oncology and Carcinogenesis
Abstract

Mutations in the epidermal growth factor receptor gene (EGFR) represent one of the most frequent "actionable" alterations in non-small cell lung cancer (NSCLC). Typified by high response rates to targeted therapies, EGFR tyrosine kinase inhibitors (TKIs) are now established first-line treatment options and have transformed the treatment paradigm for NSCLC. With the recent breakthrough designation and approval of the third-generation EGFR TKI osimertinib, available systemic and local treatment options have expanded, requiring new clinical algorithms that take into account individual patient molecular and clinical profiles. In this International Association for the Study of Lung Cancer commissioned consensus statement, key pathologic, diagnostic, and therapeutic considerations, such as optimal choice of EGFR TKI and management of brain metastasis, are discussed. In addition, recommendations are made for clinical guidelines and research priorities, such as the role of repeat biopsies and use of circulating free DNA for molecular studies. With the rapid pace of progress in treating EGFR-mutant NSCLC, this statement provides a state-of-the-art review of the contemporary issues in managing this unique subgroup of patients.

Published
2016

43. Role of the Quantitative Imaging Biomarker Alliance in Optimizing CT for the Evaluation of Lung Cancer Screen–Detected Nodules

Author

Mulshine, James L, Gierada, David S, Armato, Samuel G, Avila, Rick S, Yankelevitz, David F, Kazerooni, Ella A, McNitt-Gray, Michael F, Buckler, Andrew J, and Sullivan, Daniel C

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Biomedical Imaging, Lung Cancer, Clinical Research, Bioengineering, Lung, Cancer, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Algorithms, Biomarkers, Early Detection of Cancer, Humans, Lung Neoplasms, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Sensitivity and Specificity, Solitary Pulmonary Nodule, Tomography, X-Ray Computed, Lung cancer screening, pulmonary nodules, quantitative imaging biomarker, low-dose CT scans, metrology, Clinical Sciences, Public Health and Health Services, Nuclear Medicine & Medical Imaging, Clinical sciences
Abstract

The Quantitative Imaging Biomarker Alliance (QIBA) is a multidisciplinary consortium sponsored by the RSNA to define processes that enable the implementation and advancement of quantitative imaging methods described in a QIBA profile document that outlines the process to reliably and accurately measure imaging features. A QIBA profile includes factors such as technical (product-specific) standards, user activities, and relationship to a clinically meaningful metric, such as with nodule measurement in the course of CT screening for lung cancer. In this report, the authors describe how the QIBA approach is being applied to the measurement of small pulmonary nodules such as those found during low-dose CT-based lung cancer screening. All sources of variance with imaging measurement were defined for this process. Through a process of experimentation, literature review, and assembly of expert opinion, the strongest evidence was used to define how to best implement each step in the imaging acquisition and evaluation process. This systematic approach to implementing a quantitative imaging biomarker with standardized specifications for image acquisition and postprocessing for a specific quantitative measurement of a pulmonary nodule results in consistent performance characteristics of the measurement (eg, bias and variance). Implementation of the QIBA small nodule profile may allow more efficient and effective clinical management of the diagnostic workup of individuals found to have suspicious pulmonary nodules in the course of lung cancer screening evaluation.

Published
2015

47. Author Correction: Neoadjuvant clinical trials provide a window of opportunity for cancer drug discovery

Author

Marron, Thomas U., Galsky, Matthew D., Taouli, Bachir, Fiel, Maria Isabel, Ward, Stephen, Kim, Edward, Yankelevitz, David, Doroshow, Deborah, Guttman-Yassky, Emma, Ungar, Benjamin, Mehandru, Saurabh, Golas, Benjamin J., Labow, Daniel, Sfakianos, John, Nair, Sujit S., Chakravarty, Dimple, Buckstein, Michael, Song, Xiaoyu, Kenigsberg, Effi, Gnjatic, Sacha, Brown, Brian D., Sparano, Joseph, Tewari, Ashutosh, Schwartz, Myron, Bhardwaj, Nina, and Merad, Miriam

Published
2022
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48. Quantitative imaging workshop XIX: Utilizing quantitative thoracic imaging to optimize population health final summary.

Author

Mulshine, James L., Avila, Riccardo S., Rizzo, Albert A., Estepar, Raul San Jose, McGlothlin, Anita, Pyenson, Bruce, Hoyos, Jody, Aldigé, Carolyn R., and Yankelevitz, David F.

Abstract

Lung cancer screening involves the use of thoracic CT for both detection and measurements of suspicious lung nodules to guide the screening management. Since lung cancer screening eligibility typically requires age over 50 years along with >20 pack‐year tobacco exposure, thoracic CT scans also frequently reveal evidence for pulmonary emphysema as well as coronary artery calcification. These three thoracic diseases are collectively three of the leading causes of premature death across the world. Screening for the major thoracic diseases in this heavily tobacco‐exposed cohort is broadening the focus of lung cancer screening to a more comprehensive health evaluation including discussing the relevance of screen‐detected findings of the heart and lung parenchyma. The status and implications of these emerging issues were reviewed in a multidisciplinary workshop focused on the process of quantitative imaging in the lung cancer screening setting to guide the evolution of this important new area of public health. [ABSTRACT FROM AUTHOR]

Published
2024
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