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2. Quality of life outcomes after robotic-assisted and video-assisted thoracoscopic surgery for early-stage non–small cell lung cancer

Author

Flores, Raja, Kaufman, Andrew, Lee, Dong-Seok, Nicastri, Daniel, Wolf, Andrea, Song, Kimberly, Rosenzweig, Kenneth, Samstein, Robert, Dutta, Pinaki, Gomez, Jorge, Beasley, Mary Beth, Zakowski, Maureen, Chung, Michael, Yankelevitz, David F., Henschke, Claudia I., Taioli, Emanuela, Zhu, Yeqing, Paksashvili, Natela, Zhang, Lijing, Lyu, Lyu, Chan, Huiwen, Zhu, Jeffrey, Kantor, Sydney, Lentini, Lauren, Hakami, Ardeshir, Buyuk, Arzu, Friedman, Adie, Dreifuss, Ronald, Verzosa, Stacey, Aloferdova, Karina, Stacey, Patricia, De Nobrega, Simone, 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, Schwartz, Rebecca, Milhelis, Efstathia, Karan, Nandanee, Rzyman, Witold, Dziedzic, Robert, Henschke, Claudia, Yankelevitz, David, Jirapatnakul, Artit, Yip, Rowena, Zhang, Jiafang, Flores, Raja M., and Schwartz, Rebecca M.

Published
2025
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4. 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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6. 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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7. 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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8. 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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13. Initiative for Early Lung Cancer Research on Treatment: Development of Study Design and Pilot Implementation

Author

Flores, Raja, Kaufman, Andrew, Lee, Dong-Seok, Nicastri, Daniel, Wolf, Andrea, Rosenzweig, Kenneth, Gomez, Jorge, Beasley, Mary Beth, Zakowski, Maureen, Chung, Michael, Yankelevitz, David, Henschke, Claudia, Futamura, Rita, Kantor, Sydney, Wallace, Carly, Bhora, Faiz, Raad, Wissam, Evans, Andrew, Choi, Walter, Buyuk, Zrzu, Friedman, Adie, Dreifuss, Ronald, Verzosa, Stacey, Yakubox, Mariya, Aloferdova, Karina, Stacey, Patricia, De Nobrega, Simone, Hakami, Ardeshir, Tam, Kathleen, Pass, Harvey, Crawford, Berne, Donnington, Jessica, Cooper, Benjamin, Moreirea, Andre, Sorensen, Audrey, Kohman, Leslie, Dunton, Robert, Wallen, Jason, Curtiss, Christopher, Scalzetti, Ernest, Ellinwood, Linda, Aye, Ralph, Vallieres, Eric, Louie, Brian, Frivar, Alex, Mehta, Vivek, Manning, Kristin, Chona, Maria, Smith, Andrew, Connery, Clifford P., Torres, Emilo, Cruzer, Dan, Gendron, Bruce, Alyea, Sonya, Lackaye, Daniel, Studer, Lauren, Taioli, Emanuela, Becker, Betsy, Jirapatnakul, Artit, Reeves, Anthony, Schwartz, Rebecca, Yip, Rowena, Fevrier, Esther, Steiger, Benjamin, Yankelevitz, David F., Becker, Betsy J., and Henschke, Claudia I.

Published
2018
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16. CT- and computer-based features of small hamartomas

Author

Huang, Yao, Xu, Dong ming, Jirapatnakul, Artit, Reeves, Anthony P., Farooqi, Ali, Zhang, Li juan, Giunta, Salvatore, Zulueta, Javier, Aye, Ralph, Miller, Albert, Mendelson, David S., Aylesworth, Cheryl, Sheppard, Barry, Klingler, Karl, Yankelevitz, David F., and Henschke, Claudia I.

Published
2011
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19. Dose‐response relationship between World Trade Center dust exposure and hepatic steatosis.

Author

Jirapatnakul, Artit, Yip, Rowena, Branch, Andrea D., Lewis, Sara, Crane, Michael, Yankelevitz, David F., and Henschke, Claudia I.

Subjects
FATTY liver, COMPUTED tomography, DUST, POISONS, LIVER diseases
Abstract

Background: The World Trade Center (WTC) attack exposed thousands of workers to toxic chemicals that have been linked to liver diseases and cancers. This study examined the relationship between the intensity of WTC dust exposure and the risk of hepatic steatosis in the WTC General Responders Cohort (GRC). Methods: All low‐dose computed tomography (CT) scans of the chest performed on the WTC GRC between September 11, 2001 and December 31, 2018, collected as part of the World Trade Center Health Program, were reviewed. WTC dust exposure was categorized into five groups based on WTC arrival time. CT liver density was estimated using an automated algorithm, statistics‐based liver density estimation from imaging. The relationship between the intensity of WTC dust exposure and the risk of hepatic steatosis was examined using univariate and multivariable regression analyses. Results: Of the 1788 WTC responders, 258 (14.4%) had liver attenuation less than 40 Hounsfield units (HU < 40) on their earliest CT. Median time after September 11, 2001 and the earliest available CT was 11.3 years (interquartile range: 8.0–14.9 years). Prevalence of liver attenuation less than 40 HU was 17.0% for arrivals on September 11, 2001, 16.0% for arrivals on (September 12, 2001 or September 13, 2001), 10.9% for arrivals on September 14–30, 2001, and 9.0% for arrivals on January 10, 2001 or later (p = 0.0015). A statistically significant trend of increasing liver steatosis was observed with earlier arrival times (p < 0.0001). WTC arrival time remained a significant independent factor for decreased liver attenuation after controlling for other covariates. Conclusions: Early arrival at the WTC site was significantly associated with increasing hepatic steatosis. [ABSTRACT FROM AUTHOR]

Published
2021
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22. Growth Pattern Analysis of Murine Lung Neoplasms by Advanced Semi-Automated Quantification of Micro-CT Images.

Author

Li, Minxing, Jirapatnakul, Artit, Biancardi, Alberto, Riccio, Mark L., Weiss, Robert S., and Reeves, Anthony P.

Subjects
*TREATMENT of lung tumors, *COMPUTED tomography, *LUNG cancer diagnosis, *NUCLEOTIDES, *GENE expression, *LABORATORY mice
Abstract

Computed tomography (CT) is a non-invasive imaging modality used to monitor human lung cancers. Typically, tumor volumes are calculated using manual or semi-automated methods that require substantial user input, and an exponential growth model is used to predict tumor growth. However, these measurement methodologies are time-consuming and can lack consistency. In addition, the availability of datasets with sequential images of the same tumor that are needed to characterize in vivo growth patterns for human lung cancers is limited due to treatment interventions and radiation exposure associated with multiple scans. In this paper, we performed micro-CT imaging of mouse lung cancers induced by overexpression of ribonucleotide reductase, a key enzyme in nucleotide biosynthesis, and developed an advanced semi-automated algorithm for efficient and accurate tumor volume measurement. Tumor volumes determined by the algorithm were first validated by comparison with results from manual methods for volume determination as well as direct physical measurements. A longitudinal study was then performed to investigate in vivo murine lung tumor growth patterns. Individual mice were imaged at least three times, with at least three weeks between scans. The tumors analyzed exhibited an exponential growth pattern, with an average doubling time of 57.08 days. The accuracy of the algorithm in the longitudinal study was also confirmed by comparing its output with manual measurements. These results suggest an exponential growth model for lung neoplasms and establish a new advanced semi-automated algorithm to measure lung tumor volume in mice that can aid efforts to improve lung cancer diagnosis and the evaluation of therapeutic responses. [ABSTRACT FROM AUTHOR]

Published
2013
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23. Automated measurement of liver attenuation to identify moderate-to-severe hepatic steatosis from chest CT scans.

Author

Jirapatnakul, Artit, Reeves, Anthony P., Lewis, Sara, Chen, Xiangmeng, Ma, Teng, Yip, Rowena, Chin, Xing, Liu, Shuang, Perumalswami, Ponni V., Yankelevitz, David F., Crane, Michael, Branch, Andrea D., and Henschke, Claudia I.

Subjects
*FATTY degeneration, *INTRACLASS correlation, *LIVER, *STATISTICAL sampling, *LIVER biopsy
Abstract

Purpose: Develop and validate an automated method for measuring liver attenuation in non-contrast low-dose chest CT (LDCT) scans and compare it to the standard manual method for identifying moderate-to-severe hepatic steatosis (HS).Method: The automated method identifies a region below the right lung within the liver and uses statistical sampling techniques to exclude non-liver parenchyma. The method was used to assess moderate-to-severe HS on two IRB-approved cohorts: 1) 24 patients with liver disease examined between 1/2013-1/2017 with non-contrast chest CT and abdominal MRI scans obtained within three months of liver biopsy, and 2) 319 lung screening participants with baseline LDCT performed between 8/2011-1/2017. Agreement between the manual and automated CT methods, the manual MRI method, and pathology for determining moderate-to-severe HS was assessed using Cohen's Kappa by applying a 40 HU threshold to the CT method and 17.4% fat fraction to MRI. Agreement between the manual and automated CT methods was assessed using the intraclass correlation coefficient (ICC). Variability was assessed using Bland-Altman limits of agreement (LoA).Results: In the first cohort, the manual and automated CT methods had almost perfect agreement (ICC = 0.97, κ = 1.00) with LoA of -7.6 to 4.7 HU. Both manual and automated CT methods had almost perfect agreement with MRI (κ = 0.90) and substantial agreement with pathology (κ = 0.77). In the second cohort, the manual and automated CT methods had almost perfect agreement (ICC = 0.94, κ = 0.87). LoA were -10.6 to 5.2 HU.Conclusion: Automated measurements of liver attenuation from LDCT scans can be used to identify moderate-to-severe HS on LDCT. [ABSTRACT FROM AUTHOR]

Published
2020
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