One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer
Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung ca...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kwon, Soo Jin [verfasserIn] O, Joo Hyun [verfasserIn] Yoo, Ie Ryung [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© Korean Society of Nuclear Medicine 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Nuclear medicine and molecular imaging - Berlin : Springer, 2010, 55(2021), 3 vom: 27. Apr., Seite 123-129 |
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| Übergeordnetes Werk: |
volume:55 ; year:2021 ; number:3 ; day:27 ; month:04 ; pages:123-129 |
| Links: |
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| DOI / URN: |
10.1007/s13139-021-00697-4 |
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| Katalog-ID: |
SPR04410930X |
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| 100 | 1 | |a Kwon, Soo Jin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer |
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| 520 | |a Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. | ||
| 650 | 4 | |a PET/CT |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Lung cancer |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a PERCIST |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Response assessment |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a O, Joo Hyun |e verfasserin |4 aut | |
| 700 | 1 | |a Yoo, Ie Ryung |e verfasserin |4 aut | |
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10.1007/s13139-021-00697-4 doi (DE-627)SPR04410930X (DE-599)SPRs13139-021-00697-4-e (SPR)s13139-021-00697-4-e DE-627 ger DE-627 rakwb eng 610 ASE Kwon, Soo Jin verfasserin aut One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Nuclear Medicine 2021 Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. PET/CT (dpeaa)DE-He213 Lung cancer (dpeaa)DE-He213 PERCIST (dpeaa)DE-He213 Response assessment (dpeaa)DE-He213 O, Joo Hyun verfasserin aut Yoo, Ie Ryung verfasserin aut Enthalten in Nuclear medicine and molecular imaging Berlin : Springer, 2010 55(2021), 3 vom: 27. Apr., Seite 123-129 (DE-627)620146869 (DE-600)2541855-5 1869-3482 nnns volume:55 year:2021 number:3 day:27 month:04 pages:123-129 https://dx.doi.org/10.1007/s13139-021-00697-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 55 2021 3 27 04 123-129 |
| spelling |
10.1007/s13139-021-00697-4 doi (DE-627)SPR04410930X (DE-599)SPRs13139-021-00697-4-e (SPR)s13139-021-00697-4-e DE-627 ger DE-627 rakwb eng 610 ASE Kwon, Soo Jin verfasserin aut One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Nuclear Medicine 2021 Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. PET/CT (dpeaa)DE-He213 Lung cancer (dpeaa)DE-He213 PERCIST (dpeaa)DE-He213 Response assessment (dpeaa)DE-He213 O, Joo Hyun verfasserin aut Yoo, Ie Ryung verfasserin aut Enthalten in Nuclear medicine and molecular imaging Berlin : Springer, 2010 55(2021), 3 vom: 27. Apr., Seite 123-129 (DE-627)620146869 (DE-600)2541855-5 1869-3482 nnns volume:55 year:2021 number:3 day:27 month:04 pages:123-129 https://dx.doi.org/10.1007/s13139-021-00697-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 55 2021 3 27 04 123-129 |
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10.1007/s13139-021-00697-4 doi (DE-627)SPR04410930X (DE-599)SPRs13139-021-00697-4-e (SPR)s13139-021-00697-4-e DE-627 ger DE-627 rakwb eng 610 ASE Kwon, Soo Jin verfasserin aut One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Nuclear Medicine 2021 Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. PET/CT (dpeaa)DE-He213 Lung cancer (dpeaa)DE-He213 PERCIST (dpeaa)DE-He213 Response assessment (dpeaa)DE-He213 O, Joo Hyun verfasserin aut Yoo, Ie Ryung verfasserin aut Enthalten in Nuclear medicine and molecular imaging Berlin : Springer, 2010 55(2021), 3 vom: 27. Apr., Seite 123-129 (DE-627)620146869 (DE-600)2541855-5 1869-3482 nnns volume:55 year:2021 number:3 day:27 month:04 pages:123-129 https://dx.doi.org/10.1007/s13139-021-00697-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 55 2021 3 27 04 123-129 |
| allfieldsGer |
10.1007/s13139-021-00697-4 doi (DE-627)SPR04410930X (DE-599)SPRs13139-021-00697-4-e (SPR)s13139-021-00697-4-e DE-627 ger DE-627 rakwb eng 610 ASE Kwon, Soo Jin verfasserin aut One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Nuclear Medicine 2021 Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. PET/CT (dpeaa)DE-He213 Lung cancer (dpeaa)DE-He213 PERCIST (dpeaa)DE-He213 Response assessment (dpeaa)DE-He213 O, Joo Hyun verfasserin aut Yoo, Ie Ryung verfasserin aut Enthalten in Nuclear medicine and molecular imaging Berlin : Springer, 2010 55(2021), 3 vom: 27. Apr., Seite 123-129 (DE-627)620146869 (DE-600)2541855-5 1869-3482 nnns volume:55 year:2021 number:3 day:27 month:04 pages:123-129 https://dx.doi.org/10.1007/s13139-021-00697-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 55 2021 3 27 04 123-129 |
| allfieldsSound |
10.1007/s13139-021-00697-4 doi (DE-627)SPR04410930X (DE-599)SPRs13139-021-00697-4-e (SPR)s13139-021-00697-4-e DE-627 ger DE-627 rakwb eng 610 ASE Kwon, Soo Jin verfasserin aut One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Nuclear Medicine 2021 Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. PET/CT (dpeaa)DE-He213 Lung cancer (dpeaa)DE-He213 PERCIST (dpeaa)DE-He213 Response assessment (dpeaa)DE-He213 O, Joo Hyun verfasserin aut Yoo, Ie Ryung verfasserin aut Enthalten in Nuclear medicine and molecular imaging Berlin : Springer, 2010 55(2021), 3 vom: 27. Apr., Seite 123-129 (DE-627)620146869 (DE-600)2541855-5 1869-3482 nnns volume:55 year:2021 number:3 day:27 month:04 pages:123-129 https://dx.doi.org/10.1007/s13139-021-00697-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 55 2021 3 27 04 123-129 |
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English |
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Enthalten in Nuclear medicine and molecular imaging 55(2021), 3 vom: 27. Apr., Seite 123-129 volume:55 year:2021 number:3 day:27 month:04 pages:123-129 |
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Enthalten in Nuclear medicine and molecular imaging 55(2021), 3 vom: 27. Apr., Seite 123-129 volume:55 year:2021 number:3 day:27 month:04 pages:123-129 |
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PET/CT Lung cancer PERCIST Response assessment |
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Kwon, Soo Jin @@aut@@ O, Joo Hyun @@aut@@ Yoo, Ie Ryung @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR04410930X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230519170001.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210522s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s13139-021-00697-4</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR04410930X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)SPRs13139-021-00697-4-e</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13139-021-00697-4-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kwon, Soo Jin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Korean Society of Nuclear Medicine 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PET/CT</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Lung cancer</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PERCIST</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Response assessment</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">O, Joo Hyun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yoo, Ie Ryung</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Nuclear medicine and molecular imaging</subfield><subfield code="d">Berlin : Springer, 2010</subfield><subfield code="g">55(2021), 3 vom: 27. 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Kwon, Soo Jin |
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Kwon, Soo Jin ddc 610 misc PET/CT misc Lung cancer misc PERCIST misc Response assessment One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer |
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610 ASE One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer PET/CT (dpeaa)DE-He213 Lung cancer (dpeaa)DE-He213 PERCIST (dpeaa)DE-He213 Response assessment (dpeaa)DE-He213 |
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ddc 610 misc PET/CT misc Lung cancer misc PERCIST misc Response assessment |
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ddc 610 misc PET/CT misc Lung cancer misc PERCIST misc Response assessment |
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One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer |
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One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer |
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Kwon, Soo Jin |
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Nuclear medicine and molecular imaging |
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Kwon, Soo Jin O, Joo Hyun Yoo, Ie Ryung |
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one versus up-to-5 lesion measurements for response assessment by percist in patients with lung cancer |
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One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer |
| abstract |
Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. © Korean Society of Nuclear Medicine 2021 |
| abstractGer |
Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. © Korean Society of Nuclear Medicine 2021 |
| abstract_unstemmed |
Purpose The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). Methods Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass ($ SUL_{peak} $) of up-to-5 hottest target lesions was measured at each time point. The percent changes of $ SUL_{peak} $ of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of $ SUL_{peak} $ values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in $ SUL_{peak} $; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. Results A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson’s r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). Conclusion Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. © Korean Society of Nuclear Medicine 2021 |
| collection_details |
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| title_short |
One Versus Up-to-5 Lesion Measurements for Response Assessment by PERCIST in Patients with Lung Cancer |
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https://dx.doi.org/10.1007/s13139-021-00697-4 |
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O, Joo Hyun Yoo, Ie Ryung |
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O, Joo Hyun Yoo, Ie Ryung |
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| doi_str |
10.1007/s13139-021-00697-4 |
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2024-07-03T22:57:10.950Z |
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| score |
7.4002485 |