Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer
Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven...
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| Autor*in: |
Hassanzadeh, Elmira [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC 2017 |
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| Übergeordnetes Werk: |
Enthalten in: Abdominal radiology - [Boston, MA] : Springer US, 2016, 43(2017), 5 vom: 24. Aug., Seite 1237-1244 |
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| Übergeordnetes Werk: |
volume:43 ; year:2017 ; number:5 ; day:24 ; month:08 ; pages:1237-1244 |
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| DOI / URN: |
10.1007/s00261-017-1297-y |
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| Katalog-ID: |
SPR003206637 |
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| 024 | 7 | |a 10.1007/s00261-017-1297-y |2 doi | |
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| 035 | |a (SPR)s00261-017-1297-y-e | ||
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| 041 | |a eng | ||
| 100 | 1 | |a Hassanzadeh, Elmira |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer |
| 264 | 1 | |c 2017 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
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| 500 | |a © Springer Science+Business Media, LLC 2017 | ||
| 520 | |a Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. | ||
| 650 | 4 | |a Prostate cancer |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Magnetic resonance imaging |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Diffusion-weighted imaging |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Apparent diffusion coefficient |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a PI-RADSv2 |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Gleason score |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Alessandrino, Francesco |0 (orcid)0000-0002-1681-1284 |4 aut | |
| 700 | 1 | |a Olubiyi, Olutayo I. |4 aut | |
| 700 | 1 | |a Glazer, Daniel I. |4 aut | |
| 700 | 1 | |a Mulkern, Robert V. |4 aut | |
| 700 | 1 | |a Fedorov, Andriy |4 aut | |
| 700 | 1 | |a Tempany, Clare M. |4 aut | |
| 700 | 1 | |a Fennessy, Fiona M. |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Abdominal radiology |d [Boston, MA] : Springer US, 2016 |g 43(2017), 5 vom: 24. Aug., Seite 1237-1244 |w (DE-627)847023133 |w (DE-600)2845742-0 |x 2366-0058 |7 nnns |
| 773 | 1 | 8 | |g volume:43 |g year:2017 |g number:5 |g day:24 |g month:08 |g pages:1237-1244 |
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10.1007/s00261-017-1297-y doi (DE-627)SPR003206637 (SPR)s00261-017-1297-y-e DE-627 ger DE-627 rakwb eng Hassanzadeh, Elmira verfasserin aut Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2017 Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. Prostate cancer (dpeaa)DE-He213 Magnetic resonance imaging (dpeaa)DE-He213 Diffusion-weighted imaging (dpeaa)DE-He213 Apparent diffusion coefficient (dpeaa)DE-He213 PI-RADSv2 (dpeaa)DE-He213 Gleason score (dpeaa)DE-He213 Alessandrino, Francesco (orcid)0000-0002-1681-1284 aut Olubiyi, Olutayo I. aut Glazer, Daniel I. aut Mulkern, Robert V. aut Fedorov, Andriy aut Tempany, Clare M. aut Fennessy, Fiona M. aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 43(2017), 5 vom: 24. Aug., Seite 1237-1244 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:43 year:2017 number:5 day:24 month:08 pages:1237-1244 https://dx.doi.org/10.1007/s00261-017-1297-y 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_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_2018 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_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_4393 GBV_ILN_4700 AR 43 2017 5 24 08 1237-1244 |
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10.1007/s00261-017-1297-y doi (DE-627)SPR003206637 (SPR)s00261-017-1297-y-e DE-627 ger DE-627 rakwb eng Hassanzadeh, Elmira verfasserin aut Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2017 Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. Prostate cancer (dpeaa)DE-He213 Magnetic resonance imaging (dpeaa)DE-He213 Diffusion-weighted imaging (dpeaa)DE-He213 Apparent diffusion coefficient (dpeaa)DE-He213 PI-RADSv2 (dpeaa)DE-He213 Gleason score (dpeaa)DE-He213 Alessandrino, Francesco (orcid)0000-0002-1681-1284 aut Olubiyi, Olutayo I. aut Glazer, Daniel I. aut Mulkern, Robert V. aut Fedorov, Andriy aut Tempany, Clare M. aut Fennessy, Fiona M. aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 43(2017), 5 vom: 24. Aug., Seite 1237-1244 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:43 year:2017 number:5 day:24 month:08 pages:1237-1244 https://dx.doi.org/10.1007/s00261-017-1297-y 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_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_2018 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_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_4393 GBV_ILN_4700 AR 43 2017 5 24 08 1237-1244 |
| allfields_unstemmed |
10.1007/s00261-017-1297-y doi (DE-627)SPR003206637 (SPR)s00261-017-1297-y-e DE-627 ger DE-627 rakwb eng Hassanzadeh, Elmira verfasserin aut Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2017 Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. Prostate cancer (dpeaa)DE-He213 Magnetic resonance imaging (dpeaa)DE-He213 Diffusion-weighted imaging (dpeaa)DE-He213 Apparent diffusion coefficient (dpeaa)DE-He213 PI-RADSv2 (dpeaa)DE-He213 Gleason score (dpeaa)DE-He213 Alessandrino, Francesco (orcid)0000-0002-1681-1284 aut Olubiyi, Olutayo I. aut Glazer, Daniel I. aut Mulkern, Robert V. aut Fedorov, Andriy aut Tempany, Clare M. aut Fennessy, Fiona M. aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 43(2017), 5 vom: 24. Aug., Seite 1237-1244 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:43 year:2017 number:5 day:24 month:08 pages:1237-1244 https://dx.doi.org/10.1007/s00261-017-1297-y 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_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_2018 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_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_4393 GBV_ILN_4700 AR 43 2017 5 24 08 1237-1244 |
| allfieldsGer |
10.1007/s00261-017-1297-y doi (DE-627)SPR003206637 (SPR)s00261-017-1297-y-e DE-627 ger DE-627 rakwb eng Hassanzadeh, Elmira verfasserin aut Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2017 Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. Prostate cancer (dpeaa)DE-He213 Magnetic resonance imaging (dpeaa)DE-He213 Diffusion-weighted imaging (dpeaa)DE-He213 Apparent diffusion coefficient (dpeaa)DE-He213 PI-RADSv2 (dpeaa)DE-He213 Gleason score (dpeaa)DE-He213 Alessandrino, Francesco (orcid)0000-0002-1681-1284 aut Olubiyi, Olutayo I. aut Glazer, Daniel I. aut Mulkern, Robert V. aut Fedorov, Andriy aut Tempany, Clare M. aut Fennessy, Fiona M. aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 43(2017), 5 vom: 24. Aug., Seite 1237-1244 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:43 year:2017 number:5 day:24 month:08 pages:1237-1244 https://dx.doi.org/10.1007/s00261-017-1297-y 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_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_2018 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_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_4393 GBV_ILN_4700 AR 43 2017 5 24 08 1237-1244 |
| allfieldsSound |
10.1007/s00261-017-1297-y doi (DE-627)SPR003206637 (SPR)s00261-017-1297-y-e DE-627 ger DE-627 rakwb eng Hassanzadeh, Elmira verfasserin aut Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2017 Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. Prostate cancer (dpeaa)DE-He213 Magnetic resonance imaging (dpeaa)DE-He213 Diffusion-weighted imaging (dpeaa)DE-He213 Apparent diffusion coefficient (dpeaa)DE-He213 PI-RADSv2 (dpeaa)DE-He213 Gleason score (dpeaa)DE-He213 Alessandrino, Francesco (orcid)0000-0002-1681-1284 aut Olubiyi, Olutayo I. aut Glazer, Daniel I. aut Mulkern, Robert V. aut Fedorov, Andriy aut Tempany, Clare M. aut Fennessy, Fiona M. aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 43(2017), 5 vom: 24. Aug., Seite 1237-1244 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:43 year:2017 number:5 day:24 month:08 pages:1237-1244 https://dx.doi.org/10.1007/s00261-017-1297-y 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_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_2018 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_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_4393 GBV_ILN_4700 AR 43 2017 5 24 08 1237-1244 |
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Enthalten in Abdominal radiology 43(2017), 5 vom: 24. Aug., Seite 1237-1244 volume:43 year:2017 number:5 day:24 month:08 pages:1237-1244 |
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Prostate cancer Magnetic resonance imaging Diffusion-weighted imaging Apparent diffusion coefficient PI-RADSv2 Gleason score |
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Hassanzadeh, Elmira @@aut@@ Alessandrino, Francesco @@aut@@ Olubiyi, Olutayo I. @@aut@@ Glazer, Daniel I. @@aut@@ Mulkern, Robert V. @@aut@@ Fedorov, Andriy @@aut@@ Tempany, Clare M. @@aut@@ Fennessy, Fiona M. @@aut@@ |
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Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. 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|
| author |
Hassanzadeh, Elmira |
| spellingShingle |
Hassanzadeh, Elmira misc Prostate cancer misc Magnetic resonance imaging misc Diffusion-weighted imaging misc Apparent diffusion coefficient misc PI-RADSv2 misc Gleason score Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer |
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Hassanzadeh, Elmira |
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springer |
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2366-0058 |
| topic_title |
Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer Prostate cancer (dpeaa)DE-He213 Magnetic resonance imaging (dpeaa)DE-He213 Diffusion-weighted imaging (dpeaa)DE-He213 Apparent diffusion coefficient (dpeaa)DE-He213 PI-RADSv2 (dpeaa)DE-He213 Gleason score (dpeaa)DE-He213 |
| topic |
misc Prostate cancer misc Magnetic resonance imaging misc Diffusion-weighted imaging misc Apparent diffusion coefficient misc PI-RADSv2 misc Gleason score |
| topic_unstemmed |
misc Prostate cancer misc Magnetic resonance imaging misc Diffusion-weighted imaging misc Apparent diffusion coefficient misc PI-RADSv2 misc Gleason score |
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misc Prostate cancer misc Magnetic resonance imaging misc Diffusion-weighted imaging misc Apparent diffusion coefficient misc PI-RADSv2 misc Gleason score |
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Elektronische Aufsätze Aufsätze Elektronische Ressource |
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Abdominal radiology |
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847023133 |
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Abdominal radiology |
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(DE-627)847023133 (DE-600)2845742-0 |
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Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer |
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(DE-627)SPR003206637 (SPR)s00261-017-1297-y-e |
| title_full |
Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer |
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Hassanzadeh, Elmira |
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Abdominal radiology |
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Abdominal radiology |
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eng |
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2017 |
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Hassanzadeh, Elmira Alessandrino, Francesco Olubiyi, Olutayo I. Glazer, Daniel I. Mulkern, Robert V. Fedorov, Andriy Tempany, Clare M. Fennessy, Fiona M. |
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43 |
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Elektronische Aufsätze |
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Hassanzadeh, Elmira |
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10.1007/s00261-017-1297-y |
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(ORCID)0000-0002-1681-1284 |
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(orcid)0000-0002-1681-1284 |
| title_sort |
comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system v2 assessment for detection of clinically significant peripheral zone prostate cancer |
| title_auth |
Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer |
| abstract |
Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. © Springer Science+Business Media, LLC 2017 |
| abstractGer |
Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. © Springer Science+Business Media, LLC 2017 |
| abstract_unstemmed |
Purpose To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) $ ADC_{T} $ (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) $ ADC_{T} $ (0.86) was higher than $ ADC_{ratio} $ (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than $ ADC_{ratio} $ (0.56, p = 0.02). $ ADC_{T} $ performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). $ ADC_{ratio} $ performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. Conclusions When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with $ ADC_{T} $ providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than $ ADC_{ratio} $. csPC definition did not affect PI-RADSv2 diagnostic performance. © Springer Science+Business Media, LLC 2017 |
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Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer |
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https://dx.doi.org/10.1007/s00261-017-1297-y |
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Alessandrino, Francesco Olubiyi, Olutayo I. Glazer, Daniel I. Mulkern, Robert V. Fedorov, Andriy Tempany, Clare M. Fennessy, Fiona M. |
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Alessandrino, Francesco Olubiyi, Olutayo I. Glazer, Daniel I. Mulkern, Robert V. Fedorov, Andriy Tempany, Clare M. Fennessy, Fiona M. |
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10.1007/s00261-017-1297-y |
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2024-07-03T17:59:02.366Z |
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Methods We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean $ ADC_{T} $, mean $ ADC_{N} $, $ ADC_{ratio} $ ($ ADC_{T} $/$ ADC_{N} $) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Results Eighty five cases met eligibility requirements. 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| score |
7.4009867 |