A complete list of our peer-reviewed publications is available on PubMed and Google Scholar
KEY PUBLICATIONS
2023
Tonnesen, P Erik; Mercaldo, Nathaniel D; Tahir, Ismail; Dietrich, Anna-Sophia W; Amayri, Wael; Graur, Alexander; Allaire, Brett; Bouxsein, Mary L; Samelson, Elizabeth J; Kiel, Douglas P; Fintelmann, Florian J
Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment: The Framingham Heart Study Journal Article
In: Invest Radiol, 2023, ISSN: 1536-0210.
@article{pmid37725490,
title = {Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment: The Framingham Heart Study},
author = {P Erik Tonnesen and Nathaniel D Mercaldo and Ismail Tahir and Anna-Sophia W Dietrich and Wael Amayri and Alexander Graur and Brett Allaire and Mary L Bouxsein and Elizabeth J Samelson and Douglas P Kiel and Florian J Fintelmann},
doi = {10.1097/RLI.0000000000001012},
issn = {1536-0210},
year = {2023},
date = {2023-09-01},
journal = {Invest Radiol},
abstract = {BACKGROUND: Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking.nnOBJECTIVE: The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia.nnMATERIALS AND METHODS: This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm 2 ), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm 2 /m 2 ), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45-54, 55-64, 65-74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level-specific reference values were created and embedded into an open access online Web application.nnRESULTS: The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33-92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex.nnCONCLUSIONS: This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking.nnOBJECTIVE: The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia.nnMATERIALS AND METHODS: This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm 2 ), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm 2 /m 2 ), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45-54, 55-64, 65-74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level-specific reference values were created and embedded into an open access online Web application.nnRESULTS: The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33-92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex.nnCONCLUSIONS: This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.
Fintelmann, Florian J
Body Composition Analysis on Chest CT Scans: A Value Proposition for Lung Cancer Care Miscellaneous
2023, ISSN: 1527-1315.
@misc{pmid37489985,
title = {Body Composition Analysis on Chest CT Scans: A Value Proposition for Lung Cancer Care},
author = {Florian J Fintelmann},
doi = {10.1148/radiol.231205},
issn = {1527-1315},
year = {2023},
date = {2023-07-01},
journal = {Radiology},
volume = {308},
number = {1},
pages = {e231205},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Sänger, Jonathan A; Graur, Alexander; Tahir, Ismail; Price, Melissa C; Keane, Florence K; Lanuti, Michael; Sharma, Amita; Fintelmann, Florian J
In: Lung Cancer, vol. 181, pp. 107231, 2023, ISSN: 1872-8332.
@article{pmid37172368,
title = {Outcomes following cryoablation of stage IA non-small cell lung cancer in patients with and without interstitial lung disease: A retrospective single-center cohort study},
author = {Jonathan A Sänger and Alexander Graur and Ismail Tahir and Melissa C Price and Florence K Keane and Michael Lanuti and Amita Sharma and Florian J Fintelmann},
doi = {10.1016/j.lungcan.2023.107231},
issn = {1872-8332},
year = {2023},
date = {2023-07-01},
journal = {Lung Cancer},
volume = {181},
pages = {107231},
abstract = {OBJECTIVE: To compare the safety and efficacy of cryoablation of treatment-naïve stage IA non-small cell lung cancer (NSCLC) in patients with and without interstitial lung disease (ILD).nnMATERIALS AND METHODS: This retrospective single-center cohort study evaluated 33 consecutive patients (24 females, median age 75 years, Eastern Cooperative Oncology Group performance score 0-3) with ILD (9 patients) and without ILD (24 patients) who underwent 39 percutaneous cryoablations to treat 42 stage IA (8th IASLC edition) NSCLC measuring 1.2 cm (range 0.5-2.6 cm) from 2018 to 2022. Presence of ILD was determined according to 2018 American Thoracic Society Criteria on pre-ablation CT scans. The primary outcome was 90-day adverse events graded by the Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Secondary outcomes were hospital length of stay (LOS), local recurrence-free survival, overall survival, and the cumulative incidence of local recurrence with death as a competing risk.nnRESULTS: Adverse events ranged from grade 1-3 and occurred more often in the non-ILD group (p <.001). No acute exacerbation of ILD or death occurred within 90 days after cryoablation. The median LOS was 1 day (interquartile range 1-2 days) and did not differ between groups. One patient with ILD and two patients without ILD died after 22, 26, and 27 months from causes unrelated to cryoablation. Median imaging follow-up was 11 months (range, 0-47 months) and three tumors (7%) showed local recurrence after 4, 17, and 22 months. No difference in the cumulative incidence of local recurrence (p =.56) was found. Among all patients, local recurrence-free survival on a per-tumor basis and overall survival were 97% and 100% at 1 year, respectively.nnCONCLUSION: Adverse events and local recurrence following percutaneous cryoablation of stage IA NSCLC did not differ between patients with and without ILD. No acute exacerbation of ILD or death within 90 days were observed.},
keywords = {},
pubstate = {published},
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OBJECTIVE: To compare the safety and efficacy of cryoablation of treatment-naïve stage IA non-small cell lung cancer (NSCLC) in patients with and without interstitial lung disease (ILD).nnMATERIALS AND METHODS: This retrospective single-center cohort study evaluated 33 consecutive patients (24 females, median age 75 years, Eastern Cooperative Oncology Group performance score 0-3) with ILD (9 patients) and without ILD (24 patients) who underwent 39 percutaneous cryoablations to treat 42 stage IA (8th IASLC edition) NSCLC measuring 1.2 cm (range 0.5-2.6 cm) from 2018 to 2022. Presence of ILD was determined according to 2018 American Thoracic Society Criteria on pre-ablation CT scans. The primary outcome was 90-day adverse events graded by the Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Secondary outcomes were hospital length of stay (LOS), local recurrence-free survival, overall survival, and the cumulative incidence of local recurrence with death as a competing risk.nnRESULTS: Adverse events ranged from grade 1-3 and occurred more often in the non-ILD group (p <.001). No acute exacerbation of ILD or death occurred within 90 days after cryoablation. The median LOS was 1 day (interquartile range 1-2 days) and did not differ between groups. One patient with ILD and two patients without ILD died after 22, 26, and 27 months from causes unrelated to cryoablation. Median imaging follow-up was 11 months (range, 0-47 months) and three tumors (7%) showed local recurrence after 4, 17, and 22 months. No difference in the cumulative incidence of local recurrence (p =.56) was found. Among all patients, local recurrence-free survival on a per-tumor basis and overall survival were 97% and 100% at 1 year, respectively.nnCONCLUSION: Adverse events and local recurrence following percutaneous cryoablation of stage IA NSCLC did not differ between patients with and without ILD. No acute exacerbation of ILD or death within 90 days were observed.
Murphy, Mark C; Tahir, Ismail; Saenger, Jonathan A; Kashani, Maya Abrishami; Muniappan, Ashok; Levesque, Vincent M; Shyn, Paul B; Silverman, Stuart G; Fintelmann, Florian J
Safety and Effectiveness of Percutaneous Image-Guided Thermal Ablation of Juxtacardiac Lung Tumors Journal Article
In: J Vasc Interv Radiol, vol. 34, no. 5, pp. 750–758, 2023, ISSN: 1535-7732.
@article{pmid36707028,
title = {Safety and Effectiveness of Percutaneous Image-Guided Thermal Ablation of Juxtacardiac Lung Tumors},
author = {Mark C Murphy and Ismail Tahir and Jonathan A Saenger and Maya Abrishami Kashani and Ashok Muniappan and Vincent M Levesque and Paul B Shyn and Stuart G Silverman and Florian J Fintelmann},
doi = {10.1016/j.jvir.2023.01.020},
issn = {1535-7732},
year = {2023},
date = {2023-05-01},
journal = {J Vasc Interv Radiol},
volume = {34},
number = {5},
pages = {750--758},
abstract = {PURPOSE: To evaluate the safety and effectiveness of percutaneous image-guided thermal ablation (IGTA) for juxtacardiac lung tumors.nnMATERIALS AND METHODS: This bi-institutional retrospective cohort study included 23 consecutive patients (13 [57%] male; mean age, 55 years ± 18) with 30 juxtacardiac lung tumors located ≤10 mm from the pericardium treated in 28 IGTA sessions (25 sessions of cryoablation and 3 sessions of microwave ablation) between April 2008 and August 2022. The primary outcome was any adverse cardiac event within 90 days after ablation. Secondary outcomes included noncardiac adverse events, local tumor progression-free survival (LT-PFS), and the cumulative incidence of local tumor progression with death as a competing risk. Two tumors treated without curative intent or follow-up imaging were considered in the safety analysis but not in the progression analysis.nnRESULTS: The median imaging follow-up duration was 22 months (interquartile range [IQR], 10-53 months). Primary technical success was achieved in 25 (89%) ablations. No adverse cardiac events attributable to IGTA occurred. One patient experienced a phrenic nerve injury. The median LT-PFS duration was 59 months (IQR, 32-73 months). At 1, 3, and 5 years, LT-PFS was 90% (95% CI, 78%-100%), 74% (CI, 53%-100%), and 45% (CI, 20%-97%), respectively, and the cumulative incidence of local tumor progression was 4.3% (CI, 0.29%-19%), 11% (CI, 1.6%-30%), and 26% (CI, 3.3%-58%), respectively.nnCONCLUSIONS: IGTA is safe and effective for lung tumors located ≤10 mm from the pericardium. No adverse cardiac events were not observed within 90 days after ablation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: To evaluate the safety and effectiveness of percutaneous image-guided thermal ablation (IGTA) for juxtacardiac lung tumors.nnMATERIALS AND METHODS: This bi-institutional retrospective cohort study included 23 consecutive patients (13 [57%] male; mean age, 55 years ± 18) with 30 juxtacardiac lung tumors located ≤10 mm from the pericardium treated in 28 IGTA sessions (25 sessions of cryoablation and 3 sessions of microwave ablation) between April 2008 and August 2022. The primary outcome was any adverse cardiac event within 90 days after ablation. Secondary outcomes included noncardiac adverse events, local tumor progression-free survival (LT-PFS), and the cumulative incidence of local tumor progression with death as a competing risk. Two tumors treated without curative intent or follow-up imaging were considered in the safety analysis but not in the progression analysis.nnRESULTS: The median imaging follow-up duration was 22 months (interquartile range [IQR], 10-53 months). Primary technical success was achieved in 25 (89%) ablations. No adverse cardiac events attributable to IGTA occurred. One patient experienced a phrenic nerve injury. The median LT-PFS duration was 59 months (IQR, 32-73 months). At 1, 3, and 5 years, LT-PFS was 90% (95% CI, 78%-100%), 74% (CI, 53%-100%), and 45% (CI, 20%-97%), respectively, and the cumulative incidence of local tumor progression was 4.3% (CI, 0.29%-19%), 11% (CI, 1.6%-30%), and 26% (CI, 3.3%-58%), respectively.nnCONCLUSIONS: IGTA is safe and effective for lung tumors located ≤10 mm from the pericardium. No adverse cardiac events were not observed within 90 days after ablation.
Mikhael, Peter G; Wohlwend, Jeremy; Yala, Adam; Karstens, Ludvig; Xiang, Justin; Takigami, Angelo K; Bourgouin, Patrick P; Chan, PuiYee; Mrah, Sofiane; Amayri, Wael; Juan, Yu-Hsiang; Yang, Cheng-Ta; Wan, Yung-Liang; Lin, Gigin; Sequist, Lecia V; Fintelmann, Florian J; Barzilay, Regina
Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography Journal Article
In: J Clin Oncol, vol. 41, no. 12, pp. 2191–2200, 2023, ISSN: 1527-7755.
@article{pmid36634294,
title = {Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography},
author = {Peter G Mikhael and Jeremy Wohlwend and Adam Yala and Ludvig Karstens and Justin Xiang and Angelo K Takigami and Patrick P Bourgouin and PuiYee Chan and Sofiane Mrah and Wael Amayri and Yu-Hsiang Juan and Cheng-Ta Yang and Yung-Liang Wan and Gigin Lin and Lecia V Sequist and Florian J Fintelmann and Regina Barzilay},
doi = {10.1200/JCO.22.01345},
issn = {1527-7755},
year = {2023},
date = {2023-04-01},
journal = {J Clin Oncol},
volume = {41},
number = {12},
pages = {2191--2200},
abstract = {PURPOSE: Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most eligible people are not being screened. Tools that provide personalized future cancer risk assessment could focus approaches toward those most likely to benefit. We hypothesized that a deep learning model assessing the entire volumetric LDCT data could be built to predict individual risk without requiring additional demographic or clinical data.nnMETHODS: We developed a model called Sybil using LDCTs from the National Lung Screening Trial (NLST). Sybil requires only one LDCT and does not require clinical data or radiologist annotations; it can run in real time in the background on a radiology reading station. Sybil was validated on three independent data sets: a heldout set of 6,282 LDCTs from NLST participants, 8,821 LDCTs from Massachusetts General Hospital (MGH), and 12,280 LDCTs from Chang Gung Memorial Hospital (CGMH, which included people with a range of smoking history including nonsmokers).nnRESULTS: Sybil achieved area under the receiver-operator curves for lung cancer prediction at 1 year of 0.92 (95% CI, 0.88 to 0.95) on NLST, 0.86 (95% CI, 0.82 to 0.90) on MGH, and 0.94 (95% CI, 0.91 to 1.00) on CGMH external validation sets. Concordance indices over 6 years were 0.75 (95% CI, 0.72 to 0.78), 0.81 (95% CI, 0.77 to 0.85), and 0.80 (95% CI, 0.75 to 0.86) for NLST, MGH, and CGMH, respectively.nnCONCLUSION: Sybil can accurately predict an individual's future lung cancer risk from a single LDCT scan to further enable personalized screening. Future study is required to understand Sybil's clinical applications. Our model and annotations are publicly available.nn[Media: see text].},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most eligible people are not being screened. Tools that provide personalized future cancer risk assessment could focus approaches toward those most likely to benefit. We hypothesized that a deep learning model assessing the entire volumetric LDCT data could be built to predict individual risk without requiring additional demographic or clinical data.nnMETHODS: We developed a model called Sybil using LDCTs from the National Lung Screening Trial (NLST). Sybil requires only one LDCT and does not require clinical data or radiologist annotations; it can run in real time in the background on a radiology reading station. Sybil was validated on three independent data sets: a heldout set of 6,282 LDCTs from NLST participants, 8,821 LDCTs from Massachusetts General Hospital (MGH), and 12,280 LDCTs from Chang Gung Memorial Hospital (CGMH, which included people with a range of smoking history including nonsmokers).nnRESULTS: Sybil achieved area under the receiver-operator curves for lung cancer prediction at 1 year of 0.92 (95% CI, 0.88 to 0.95) on NLST, 0.86 (95% CI, 0.82 to 0.90) on MGH, and 0.94 (95% CI, 0.91 to 1.00) on CGMH external validation sets. Concordance indices over 6 years were 0.75 (95% CI, 0.72 to 0.78), 0.81 (95% CI, 0.77 to 0.85), and 0.80 (95% CI, 0.75 to 0.86) for NLST, MGH, and CGMH, respectively.nnCONCLUSION: Sybil can accurately predict an individual's future lung cancer risk from a single LDCT scan to further enable personalized screening. Future study is required to understand Sybil's clinical applications. Our model and annotations are publicly available.nn[Media: see text].
Adams, Scott J; Stone, Emily; Baldwin, David R; Vliegenthart, Rozemarijn; Lee, Pyng; Fintelmann, Florian J
Lung cancer screening Journal Article
In: Lancet, vol. 401, no. 10374, pp. 390–408, 2023, ISSN: 1474-547X.
@article{pmid36563698,
title = {Lung cancer screening},
author = {Scott J Adams and Emily Stone and David R Baldwin and Rozemarijn Vliegenthart and Pyng Lee and Florian J Fintelmann},
doi = {10.1016/S0140-6736(22)01694-4},
issn = {1474-547X},
year = {2023},
date = {2023-02-01},
journal = {Lancet},
volume = {401},
number = {10374},
pages = {390--408},
abstract = {Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.
2022
Tahir, Ismail; Marquardt, J Peter; Mercaldo, Nathaniel D; Bourgouin, Patrick P; Wrobel, Maria M; Mrah, Sofiane; Sharp, Gregory C; Khandekar, Melin J; Willers, Henning; Keane, Florence K; Fintelmann, Florian J
In: AJR Am J Roentgenol, vol. 219, no. 4, pp. 579–589, 2022, ISSN: 1546-3141.
@article{pmid35416054,
title = {Utility of Noncancerous Chest CT Features for Predicting Overall Survival and Noncancer Death in Patients With Stage I Lung Cancer Treated With Stereotactic Body Radiotherapy},
author = {Ismail Tahir and J Peter Marquardt and Nathaniel D Mercaldo and Patrick P Bourgouin and Maria M Wrobel and Sofiane Mrah and Gregory C Sharp and Melin J Khandekar and Henning Willers and Florence K Keane and Florian J Fintelmann},
doi = {10.2214/AJR.22.27484},
issn = {1546-3141},
year = {2022},
date = {2022-10-01},
journal = {AJR Am J Roentgenol},
volume = {219},
number = {4},
pages = {579--589},
abstract = { Noncancerous imaging markers can be readily derived from pre-treatment diagnostic and radiotherapy planning chest CT examinations. The purpose of this article was to explore the ability of noncancerous features on chest CT to predict overall survival (OS) and noncancer-related death in patients with stage I lung cancer treated with stereotactic body radiation therapy (SBRT). This retrospective study included 282 patients (168 female, 114 male; median age, 75 years) with stage I lung cancer treated with SBRT between January 2009 and June 2017. Pretreatment chest CT was used to quantify coronary artery calcium (CAC) score, pulmonary artery (PA)-to-aorta ratio, emphysema, and body composition in terms of the cross-sectional area and attenuation of skeletal muscle and subcutaneous adipose tissue at the T5, T8, and T10 vertebral levels. Associations of clinical and imaging features with OS were quantified using a multivariable Cox proportional hazards (PH) model. Penalized multivariable Cox PH models to predict OS were constructed using clinical features only and using both clinical and imaging features. The models' discriminatory ability was assessed by constructing time-varying ROC curves and computing AUC at prespecified times. After a median OS of 60.8 months (95% CI, 55.8-68.0), 148 (52.5%) patients had died, including 83 (56.1%) with noncancer deaths. Higher CAC score (11-399: hazard ratio [HR], 1.83 [95% CI, 1.15-2.91], .01; ≥ 400: HR, 1.63 [95% CI, 1.01-2.63], .04), higher PA-to-aorta ratio (HR, 1.33 [95% CI, 1.16-1.52], .001, per 0.1-unit increase), and lower thoracic skeletal muscle index (HR, 0.88 [95% CI, 0.79-0.98], .02, per 10-cm/m increase) were independently associated with shorter OS. Discriminatory ability for 5-year OS was greater for the model including clinical and imaging features than for the model including clinical features only (AUC, 0.75 [95% CI, 0.68-0.83] vs 0.61 [95% CI, 0.53-0.70]; < .01). The model's most important clinical or imaging feature according to mean standardized regression coefficients was the PA-to-aorta ratio. In patients undergoing SBRT for stage I lung cancer, higher CAC score, higher PA-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse OS. Noncancerous imaging features on chest CT performed before SBRT improve survival prediction compared with clinical features alone.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Noncancerous imaging markers can be readily derived from pre-treatment diagnostic and radiotherapy planning chest CT examinations. The purpose of this article was to explore the ability of noncancerous features on chest CT to predict overall survival (OS) and noncancer-related death in patients with stage I lung cancer treated with stereotactic body radiation therapy (SBRT). This retrospective study included 282 patients (168 female, 114 male; median age, 75 years) with stage I lung cancer treated with SBRT between January 2009 and June 2017. Pretreatment chest CT was used to quantify coronary artery calcium (CAC) score, pulmonary artery (PA)-to-aorta ratio, emphysema, and body composition in terms of the cross-sectional area and attenuation of skeletal muscle and subcutaneous adipose tissue at the T5, T8, and T10 vertebral levels. Associations of clinical and imaging features with OS were quantified using a multivariable Cox proportional hazards (PH) model. Penalized multivariable Cox PH models to predict OS were constructed using clinical features only and using both clinical and imaging features. The models' discriminatory ability was assessed by constructing time-varying ROC curves and computing AUC at prespecified times. After a median OS of 60.8 months (95% CI, 55.8-68.0), 148 (52.5%) patients had died, including 83 (56.1%) with noncancer deaths. Higher CAC score (11-399: hazard ratio [HR], 1.83 [95% CI, 1.15-2.91], .01; ≥ 400: HR, 1.63 [95% CI, 1.01-2.63], .04), higher PA-to-aorta ratio (HR, 1.33 [95% CI, 1.16-1.52], .001, per 0.1-unit increase), and lower thoracic skeletal muscle index (HR, 0.88 [95% CI, 0.79-0.98], .02, per 10-cm/m increase) were independently associated with shorter OS. Discriminatory ability for 5-year OS was greater for the model including clinical and imaging features than for the model including clinical features only (AUC, 0.75 [95% CI, 0.68-0.83] vs 0.61 [95% CI, 0.53-0.70]; < .01). The model's most important clinical or imaging feature according to mean standardized regression coefficients was the PA-to-aorta ratio. In patients undergoing SBRT for stage I lung cancer, higher CAC score, higher PA-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse OS. Noncancerous imaging features on chest CT performed before SBRT improve survival prediction compared with clinical features alone.
Murphy, Mark C; Wrobel, Maria M; Fisher, Dane A; Cahalane, Alexis M; Fintelmann, Florian J
Update on Image-Guided Thermal Lung Ablation: Society Guidelines, Therapeutic Alternatives, and Postablation Imaging Findings Journal Article
In: AJR Am J Roentgenol, vol. 219, no. 3, pp. 471–485, 2022, ISSN: 1546-3141.
@article{pmid35319908,
title = {Update on Image-Guided Thermal Lung Ablation: Society Guidelines, Therapeutic Alternatives, and Postablation Imaging Findings},
author = {Mark C Murphy and Maria M Wrobel and Dane A Fisher and Alexis M Cahalane and Florian J Fintelmann},
doi = {10.2214/AJR.21.27099},
issn = {1546-3141},
year = {2022},
date = {2022-09-01},
journal = {AJR Am J Roentgenol},
volume = {219},
number = {3},
pages = {471--485},
abstract = {Percutaneous image-guided thermal ablation (IGTA) has been endorsed by multiple societies as a safe and effective lung-preserving treatment of primary lung cancer and metastases involving the lung and chest wall. This article reviews the role of IGTA in the care continuum of patients with thoracic neoplasms and discusses strategies to identify the optimal local therapy considering patient and tumor characteristics. The advantages and disadvantages of percutaneous thermal ablation compared with surgical resection and stereotactic body radiotherapy are summarized. Principles of radiofrequency ablation, microwave ablation, and cryoablation, as well as the emerging use of transbronchial thermal ablation, are described. Specific considerations are presented regarding the role of thermal ablation for early-stage non-small cell lung cancer (NSCLC), multifocal primary NSCLC, pulmonary metastases, salvage of recurrent NSCLC after surgery or radiation, and pain palliation for tumors involving the chest wall. Recent changes to professional society guidelines regarding the role of thermal ablation in the lung, including for treatment of oligometastatic disease, are highlighted. Finally, recommendations are provided for imaging follow-up after thermal ablation of lung tumors, accompanied by examples of expected postoperative findings and patterns of disease recurrence.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Percutaneous image-guided thermal ablation (IGTA) has been endorsed by multiple societies as a safe and effective lung-preserving treatment of primary lung cancer and metastases involving the lung and chest wall. This article reviews the role of IGTA in the care continuum of patients with thoracic neoplasms and discusses strategies to identify the optimal local therapy considering patient and tumor characteristics. The advantages and disadvantages of percutaneous thermal ablation compared with surgical resection and stereotactic body radiotherapy are summarized. Principles of radiofrequency ablation, microwave ablation, and cryoablation, as well as the emerging use of transbronchial thermal ablation, are described. Specific considerations are presented regarding the role of thermal ablation for early-stage non-small cell lung cancer (NSCLC), multifocal primary NSCLC, pulmonary metastases, salvage of recurrent NSCLC after surgery or radiation, and pain palliation for tumors involving the chest wall. Recent changes to professional society guidelines regarding the role of thermal ablation in the lung, including for treatment of oligometastatic disease, are highlighted. Finally, recommendations are provided for imaging follow-up after thermal ablation of lung tumors, accompanied by examples of expected postoperative findings and patterns of disease recurrence.
Best, Till D; Mercaldo, Sarah F; Bryan, Darren S; Marquardt, Jan Peter; Wrobel, Maria M; Bridge, Christopher P; Troschel, Fabian M; Javidan, Cylen; Chung, Jonathan H; Muniappan, Ashok; Bhalla, Sanjeev; Meyers, Bryan F; Ferguson, Mark K; Gaissert, Henning A; Fintelmann, Florian J
In: Ann Surg, vol. 275, no. 5, pp. e708–e715, 2022, ISSN: 1528-1140.
@article{pmid32773626,
title = {Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications After Lobectomy for Lung Cancer: A Multicenter Study},
author = {Till D Best and Sarah F Mercaldo and Darren S Bryan and Jan Peter Marquardt and Maria M Wrobel and Christopher P Bridge and Fabian M Troschel and Cylen Javidan and Jonathan H Chung and Ashok Muniappan and Sanjeev Bhalla and Bryan F Meyers and Mark K Ferguson and Henning A Gaissert and Florian J Fintelmann},
doi = {10.1097/SLA.0000000000004040},
issn = {1528-1140},
year = {2022},
date = {2022-05-01},
journal = {Ann Surg},
volume = {275},
number = {5},
pages = {e708--e715},
abstract = {OBJECTIVE: To investigate the impact of thoracic body composition on outcomes after lobectomy for lung cancer.nnSUMMARY AND BACKGROUND DATA: Preoperative identification of patients at risk for adverse outcomes permits treatment modification. The impact of body composition on lung resection outcomes has not been investigated in a multicenter setting.nnMETHODS: A total of 958 consecutive patients undergoing lobectomy for lung cancer at 3 centers from 2014 to 2017 were retrospectively analyzed. Muscle and adipose tissue cross-sectional area at the fifth, eighth, and tenth thoracic vertebral body was quantified. Prospectively collected outcomes from a national database were abstracted to characterize the association between sums of muscle and adipose tissue and hospital length of stay (LOS), number of any postoperative complications, and number of respiratory postoperative complications using multivariate regression. A priori determined covariates were forced expiratory volume in 1 second and diffusion capacity of the lungs for carbon monoxide predicted, age, sex, body mass index, race, surgical approach, smoking status, Zubrod and American Society of Anesthesiologists scores.nnRESULTS: Mean patient age was 67 years, body mass index 27.4 kg/m2 and 65% had stage i disease. Sixty-three percent underwent minimally invasive lobectomy. Median LOS was 4 days and 34% of patients experienced complications. Muscle (using 30 cm2 increments) was an independent predictor of LOS (adjusted coefficient 0.972; P = 0.002), any postoperative complications (odds ratio 0.897; P = 0.007) and postoperative respiratory complications (odds ratio 0.860; P = 0.010). Sarcopenic obesity was also associated with LOS and adverse outcomes.nnCONCLUSIONS: Body composition on preoperative chest computed tomography is an independent predictor of LOS and postoperative complications after lobectomy for lung cancer.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVE: To investigate the impact of thoracic body composition on outcomes after lobectomy for lung cancer.nnSUMMARY AND BACKGROUND DATA: Preoperative identification of patients at risk for adverse outcomes permits treatment modification. The impact of body composition on lung resection outcomes has not been investigated in a multicenter setting.nnMETHODS: A total of 958 consecutive patients undergoing lobectomy for lung cancer at 3 centers from 2014 to 2017 were retrospectively analyzed. Muscle and adipose tissue cross-sectional area at the fifth, eighth, and tenth thoracic vertebral body was quantified. Prospectively collected outcomes from a national database were abstracted to characterize the association between sums of muscle and adipose tissue and hospital length of stay (LOS), number of any postoperative complications, and number of respiratory postoperative complications using multivariate regression. A priori determined covariates were forced expiratory volume in 1 second and diffusion capacity of the lungs for carbon monoxide predicted, age, sex, body mass index, race, surgical approach, smoking status, Zubrod and American Society of Anesthesiologists scores.nnRESULTS: Mean patient age was 67 years, body mass index 27.4 kg/m2 and 65% had stage i disease. Sixty-three percent underwent minimally invasive lobectomy. Median LOS was 4 days and 34% of patients experienced complications. Muscle (using 30 cm2 increments) was an independent predictor of LOS (adjusted coefficient 0.972; P = 0.002), any postoperative complications (odds ratio 0.897; P = 0.007) and postoperative respiratory complications (odds ratio 0.860; P = 0.010). Sarcopenic obesity was also associated with LOS and adverse outcomes.nnCONCLUSIONS: Body composition on preoperative chest computed tomography is an independent predictor of LOS and postoperative complications after lobectomy for lung cancer.
Marquardt, J Peter; Roeland, Eric J; Seventer, Emily E Van; Best, Till D; Horick, Nora K; Nipp, Ryan D; Fintelmann, Florian J
Percentile-based averaging and skeletal muscle gauge improve body composition analysis: validation at multiple vertebral levels Journal Article
In: J Cachexia Sarcopenia Muscle, vol. 13, no. 1, pp. 190–202, 2022, ISSN: 2190-6009.
@article{pmid34729952,
title = {Percentile-based averaging and skeletal muscle gauge improve body composition analysis: validation at multiple vertebral levels},
author = {J Peter Marquardt and Eric J Roeland and Emily E Van Seventer and Till D Best and Nora K Horick and Ryan D Nipp and Florian J Fintelmann},
doi = {10.1002/jcsm.12848},
issn = {2190-6009},
year = {2022},
date = {2022-02-01},
journal = {J Cachexia Sarcopenia Muscle},
volume = {13},
number = {1},
pages = {190--202},
abstract = {BACKGROUND: Skeletal muscle metrics on computed tomography (CT) correlate with clinical and patient-reported outcomes. We hypothesize that aggregating skeletal muscle measurements from multiple vertebral levels and skeletal muscle gauge (SMG) better predict outcomes than skeletal muscle radioattenuation (SMRA) or -index (SMI) at a single vertebral level.nnMETHODS: We performed a secondary analysis of prospectively collected clinical (overall survival, hospital readmission, time to unplanned hospital readmission or death, and readmission or death within 90 days) and patient-reported outcomes (physical and psychological symptom burden captured as Edmonton Symptom Assessment Scale and Patient Health Questionnaire) of patients with advanced cancer who experienced an unplanned admission to Massachusetts General Hospital from 2014 to 2016. First, we assessed the correlation of skeletal muscle cross-sectional area, SMRA, SMI, and SMG at one or more of the following thoracic (T) or lumbar (L) vertebral levels: T5, T8, T10, and L3 on CT scans obtained ≤50 days before index assessment. Second, we aggregated measurements across all available vertebral levels using percentile-based averaging (PBA) to create the average percentile. Third, we constructed one regression model adjusted for age, sex, sociodemographic factors, cancer type, body mass index, and intravenous contrast for each combination of (i) vertebral level and average percentile, (ii) muscle metrics (SMRA, SMI, & SMG), and (iii) clinical and patient-reported outcomes. Fourth, we compared the performance of vertebral levels and muscle metrics by ranking otherwise identical models by concordance statistic, number of included patients, coefficient of determination, and significance of muscle metric.nnRESULTS: We included 846 patients (mean age: 63.5 ± 12.9 years, 50.5% males) with advanced cancer [predominantly gastrointestinal (32.9%) or lung (18.9%)]. The correlation of muscle measurements between vertebral levels ranged from 0.71 to 0.84 for SMRA and 0.67 to 0.81 for SMI. The correlation of individual levels with the average percentile was 0.90-0.93 for SMRA and 0.86-0.92 for SMI. The intrapatient correlation of SMRA with SMI was 0.21-0.40. PBA allowed for inclusion of 8-47% more patients than any single-level analysis. PBA outperformed single-level analyses across all comparisons with average ranks 2.6, 2.9, and 1.6 for concordance statistic, coefficient of determination, and significance (range 1-5, μ = 3), respectively. On average, SMG outperformed SMRA and SMI across outcomes and vertebral levels: the average rank of SMG was 1.4, 1.4, and 1.4 for concordance statistic, coefficient of determination, and significance (range 1-3, μ = 2), respectively.nnCONCLUSIONS: Multivertebral level skeletal muscle analyses using PBA and SMG independently and additively outperform analyses using individual levels and SMRA or SMI.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Skeletal muscle metrics on computed tomography (CT) correlate with clinical and patient-reported outcomes. We hypothesize that aggregating skeletal muscle measurements from multiple vertebral levels and skeletal muscle gauge (SMG) better predict outcomes than skeletal muscle radioattenuation (SMRA) or -index (SMI) at a single vertebral level.nnMETHODS: We performed a secondary analysis of prospectively collected clinical (overall survival, hospital readmission, time to unplanned hospital readmission or death, and readmission or death within 90 days) and patient-reported outcomes (physical and psychological symptom burden captured as Edmonton Symptom Assessment Scale and Patient Health Questionnaire) of patients with advanced cancer who experienced an unplanned admission to Massachusetts General Hospital from 2014 to 2016. First, we assessed the correlation of skeletal muscle cross-sectional area, SMRA, SMI, and SMG at one or more of the following thoracic (T) or lumbar (L) vertebral levels: T5, T8, T10, and L3 on CT scans obtained ≤50 days before index assessment. Second, we aggregated measurements across all available vertebral levels using percentile-based averaging (PBA) to create the average percentile. Third, we constructed one regression model adjusted for age, sex, sociodemographic factors, cancer type, body mass index, and intravenous contrast for each combination of (i) vertebral level and average percentile, (ii) muscle metrics (SMRA, SMI, & SMG), and (iii) clinical and patient-reported outcomes. Fourth, we compared the performance of vertebral levels and muscle metrics by ranking otherwise identical models by concordance statistic, number of included patients, coefficient of determination, and significance of muscle metric.nnRESULTS: We included 846 patients (mean age: 63.5 ± 12.9 years, 50.5% males) with advanced cancer [predominantly gastrointestinal (32.9%) or lung (18.9%)]. The correlation of muscle measurements between vertebral levels ranged from 0.71 to 0.84 for SMRA and 0.67 to 0.81 for SMI. The correlation of individual levels with the average percentile was 0.90-0.93 for SMRA and 0.86-0.92 for SMI. The intrapatient correlation of SMRA with SMI was 0.21-0.40. PBA allowed for inclusion of 8-47% more patients than any single-level analysis. PBA outperformed single-level analyses across all comparisons with average ranks 2.6, 2.9, and 1.6 for concordance statistic, coefficient of determination, and significance (range 1-5, μ = 3), respectively. On average, SMG outperformed SMRA and SMI across outcomes and vertebral levels: the average rank of SMG was 1.4, 1.4, and 1.4 for concordance statistic, coefficient of determination, and significance (range 1-3, μ = 2), respectively.nnCONCLUSIONS: Multivertebral level skeletal muscle analyses using PBA and SMG independently and additively outperform analyses using individual levels and SMRA or SMI.