Prediction of prostate cancer aggressiveness using 18F-Fluciclovine (FACBC) PET and multisequence multiparametric MRI
The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for 18 F-Fluciclovine PET and multisequence multiparametric MRI in the prediction of prostate cancer (PCa) aggressiveness, defined by Gleason Grade Group (GGG...
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Published in | Scientific reports Vol. 10; no. 1; p. 9407 |
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Main Authors | , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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Nature Publishing Group UK
10.06.2020
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Abstract | The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for
18
F-Fluciclovine PET and multisequence multiparametric MRI in the prediction of prostate cancer (PCa) aggressiveness, defined by Gleason Grade Group (GGG). 21 patients with PCa underwent PET/CT, PET/MRI and MRI before prostatectomy. DWI was post-processed using kurtosis (ADC
k
, K), mono- (ADC
m
), and biexponential functions (f, D
p
, D
f
) while Logan plots were used to calculate volume of distribution (V
T
). In total, 16 unique PET (V
T
, SUV) and MRI derived quantitative parameters were evaluated. Univariate and multivariate analysis were carried out to estimate the potential of the quantitative parameters and their combinations to predict GGG 1 vs >1, using logistic regression with a nested leave-pair out cross validation (LPOCV) scheme and recursive feature elimination technique applied for feature selection. The second order rotating frame imaging (RAFF), monoexponential and kurtosis derived parameters had LPOCV AUC in the range of 0.72 to 0.92 while the corresponding value for V
T
was 0.85.
T
he best performance for GGG prediction was achieved by K parameter of kurtosis function followed by quantitative parameters based on DWI, RAFF and
18
F-FACBC PET. No major improvement was achieved using parameter combinations with or without feature selection. Addition of
18
F-FACBC PET derived parameters (V
T
, SUV) to DWI and RAFF derived parameters did not improve LPOCV AUC. |
---|---|
AbstractList | The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for
18
F-Fluciclovine PET and multisequence multiparametric MRI in the prediction of prostate cancer (PCa) aggressiveness, defined by Gleason Grade Group (GGG). 21 patients with PCa underwent PET/CT, PET/MRI and MRI before prostatectomy. DWI was post-processed using kurtosis (ADC
k
, K), mono- (ADC
m
), and biexponential functions (f, D
p
, D
f
) while Logan plots were used to calculate volume of distribution (V
T
). In total, 16 unique PET (V
T
, SUV) and MRI derived quantitative parameters were evaluated. Univariate and multivariate analysis were carried out to estimate the potential of the quantitative parameters and their combinations to predict GGG 1 vs >1, using logistic regression with a nested leave-pair out cross validation (LPOCV) scheme and recursive feature elimination technique applied for feature selection. The second order rotating frame imaging (RAFF), monoexponential and kurtosis derived parameters had LPOCV AUC in the range of 0.72 to 0.92 while the corresponding value for V
T
was 0.85.
T
he best performance for GGG prediction was achieved by K parameter of kurtosis function followed by quantitative parameters based on DWI, RAFF and
18
F-FACBC PET. No major improvement was achieved using parameter combinations with or without feature selection. Addition of
18
F-FACBC PET derived parameters (V
T
, SUV) to DWI and RAFF derived parameters did not improve LPOCV AUC. Abstract The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for 18 F-Fluciclovine PET and multisequence multiparametric MRI in the prediction of prostate cancer (PCa) aggressiveness, defined by Gleason Grade Group (GGG). 21 patients with PCa underwent PET/CT, PET/MRI and MRI before prostatectomy. DWI was post-processed using kurtosis (ADC k , K), mono- (ADC m ), and biexponential functions (f, D p , D f ) while Logan plots were used to calculate volume of distribution (V T ). In total, 16 unique PET (V T , SUV) and MRI derived quantitative parameters were evaluated. Univariate and multivariate analysis were carried out to estimate the potential of the quantitative parameters and their combinations to predict GGG 1 vs >1, using logistic regression with a nested leave-pair out cross validation (LPOCV) scheme and recursive feature elimination technique applied for feature selection. The second order rotating frame imaging (RAFF), monoexponential and kurtosis derived parameters had LPOCV AUC in the range of 0.72 to 0.92 while the corresponding value for V T was 0.85. T he best performance for GGG prediction was achieved by K parameter of kurtosis function followed by quantitative parameters based on DWI, RAFF and 18 F-FACBC PET. No major improvement was achieved using parameter combinations with or without feature selection. Addition of 18 F-FACBC PET derived parameters (V T , SUV) to DWI and RAFF derived parameters did not improve LPOCV AUC. The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for 18F-Fluciclovine PET and multisequence multiparametric MRI in the prediction of prostate cancer (PCa) aggressiveness, defined by Gleason Grade Group (GGG). 21 patients with PCa underwent PET/CT, PET/MRI and MRI before prostatectomy. DWI was post-processed using kurtosis (ADCk, K), mono- (ADCm), and biexponential functions (f, Dp, Df) while Logan plots were used to calculate volume of distribution (VT). In total, 16 unique PET (VT, SUV) and MRI derived quantitative parameters were evaluated. Univariate and multivariate analysis were carried out to estimate the potential of the quantitative parameters and their combinations to predict GGG 1 vs >1, using logistic regression with a nested leave-pair out cross validation (LPOCV) scheme and recursive feature elimination technique applied for feature selection. The second order rotating frame imaging (RAFF), monoexponential and kurtosis derived parameters had LPOCV AUC in the range of 0.72 to 0.92 while the corresponding value for VT was 0.85. The best performance for GGG prediction was achieved by K parameter of kurtosis function followed by quantitative parameters based on DWI, RAFF and 18F-FACBC PET. No major improvement was achieved using parameter combinations with or without feature selection. Addition of 18F-FACBC PET derived parameters (VT, SUV) to DWI and RAFF derived parameters did not improve LPOCV AUC. The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for 18F-Fluciclovine PET and multisequence multiparametric MRI in the prediction of prostate cancer (PCa) aggressiveness, defined by Gleason Grade Group (GGG). 21 patients with PCa underwent PET/CT, PET/MRI and MRI before prostatectomy. DWI was post-processed using kurtosis (ADCk, K), mono- (ADCm), and biexponential functions (f, Dp, Df) while Logan plots were used to calculate volume of distribution (VT). In total, 16 unique PET (VT, SUV) and MRI derived quantitative parameters were evaluated. Univariate and multivariate analysis were carried out to estimate the potential of the quantitative parameters and their combinations to predict GGG 1 vs >1, using logistic regression with a nested leave-pair out cross validation (LPOCV) scheme and recursive feature elimination technique applied for feature selection. The second order rotating frame imaging (RAFF), monoexponential and kurtosis derived parameters had LPOCV AUC in the range of 0.72 to 0.92 while the corresponding value for VT was 0.85. The best performance for GGG prediction was achieved by K parameter of kurtosis function followed by quantitative parameters based on DWI, RAFF and 18F-FACBC PET. No major improvement was achieved using parameter combinations with or without feature selection. Addition of 18F-FACBC PET derived parameters (VT, SUV) to DWI and RAFF derived parameters did not improve LPOCV AUC.The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for 18F-Fluciclovine PET and multisequence multiparametric MRI in the prediction of prostate cancer (PCa) aggressiveness, defined by Gleason Grade Group (GGG). 21 patients with PCa underwent PET/CT, PET/MRI and MRI before prostatectomy. DWI was post-processed using kurtosis (ADCk, K), mono- (ADCm), and biexponential functions (f, Dp, Df) while Logan plots were used to calculate volume of distribution (VT). In total, 16 unique PET (VT, SUV) and MRI derived quantitative parameters were evaluated. Univariate and multivariate analysis were carried out to estimate the potential of the quantitative parameters and their combinations to predict GGG 1 vs >1, using logistic regression with a nested leave-pair out cross validation (LPOCV) scheme and recursive feature elimination technique applied for feature selection. The second order rotating frame imaging (RAFF), monoexponential and kurtosis derived parameters had LPOCV AUC in the range of 0.72 to 0.92 while the corresponding value for VT was 0.85. The best performance for GGG prediction was achieved by K parameter of kurtosis function followed by quantitative parameters based on DWI, RAFF and 18F-FACBC PET. No major improvement was achieved using parameter combinations with or without feature selection. Addition of 18F-FACBC PET derived parameters (VT, SUV) to DWI and RAFF derived parameters did not improve LPOCV AUC. |
ArticleNumber | 9407 |
Author | Merisaari, Harri Eskola, Olli Saunavaara, Jani Liimatainen, Timo Jambor, Ivan Aronen, Hannu Minn, Heikki Movahedi, Parisa Teuho, Jarmo Pesola, Marko Ettala, Otto Pahikkala, Tapio Boström, Peter Taimen, Pekka Perez, Ileana Montoya Kemppainen, Jukka Kähkönen, Esa Kuisma, Anna |
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Snippet | The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for
18... Abstract The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for 18... The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for... |
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SubjectTerms | 692/4025 692/4025/1752 692/4028 692/4028/67 Cancer surgery Computed tomography Humanities and Social Sciences Magnetic resonance imaging multidisciplinary Multivariate analysis Predictions Prostate cancer Prostatectomy Science Science (multidisciplinary) |
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Title | Prediction of prostate cancer aggressiveness using 18F-Fluciclovine (FACBC) PET and multisequence multiparametric MRI |
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