- Email: [email protected]
107. Magnetic-resonance-imaging texture analysis predicts early progression in rectal cancer patients undergoing neoadjuvant chemo-radiation
Abstracts / Physica Medica 56 (2018) 59–132
127
Table 1 mean and one SD of ratios between a selection of features computed at tracer activity levels A and at full tracer activity for Fixed VOIs and R64 resampling; (*) statistical significance at 0.01, Bonferroni correction applied (Intensity Direct (ID), Gray-Level Cooccurence Matrix 3D (GLCM), Gray-Level Run Length Matrix 2D (GLRLM)).
Global Entropy (ID) Difference Entropy (GLCM) Inverse difference moment normalized (GLCM) Low grey-level run emphasis (GLRLM) High grey-level run emphasis (GLRLM)
A = 0.6 MBq/kg
A = 1.2 MBq/kg
A = 1.5 MBq/kg
A = 1.8 MBq/kg
A = 2.4 MBq/kg
1.01 ± 0.03 1.00 ± 0.03
1.01 ± 0.03 1.00 ± 0.02
1.01 ± 0.02 1.00 ± 0.02
1.00 ± 0.02 1.00 ± 0.02
1.00 ± 0.02 1.00 ± 0.02
1.00 ± 0.01 1.13 ± 0.39 0.95 ± 0.17 (*)
1.00 ± 0.01 1.16 ± 0.49 0.98 ± 0.14
1.00 ± 0.01 1.16 ± 0.43 0.98 ± 0.13
1.00 ± 0.01 1.10 ± 0.34 0.97 ± 0.11
1.00 ± 0.01 1.09 ± 0.27 0.98 ± 0.06
Figure: coronal view of a patient for standard injected activity of 3 MBq/kg and simulated activity of 1.5 and 0.6 MBq/kg (from left to right) with ROI contour.
a
Conclusions. Selected PET radiomic features can provide reliable information of tumor heterogeneity for low-activity pediatric protocols depending on SUV resampling and lesion delineation strategies.
Reference 1. Yan J, Chu-Shern JL, Loi HY, et al.. Impact of image reconstruction settings on texture features in 18F-FDG PET. J Nucl Med 2015;56(11):1667–73. https://doi.org/10.1016/j.ejmp.2018.04.116
107. Magnetic-resonance-imaging texture analysis predicts early progression in rectal cancer patients undergoing neoadjuvant chemo-radiation M. Biondi a,b, E. Vanzi a, G. De Otto a, G. Belmonte a, V. Nardone c,d, A. Cirigliano e, A. Grassi e, S.F. Carbone e, P. Tini c,d, L. Sebaste c,d, T. Carfagno c,d, G. Battaglia c,d, G. Rubino c,d, P. Pastina c,d, P. Correale c,d, C. Nioche f, L. Pirtoli c,d, F. Banci Buonamici a
Unit of Medical Physics, University Hospital of Siena, Siena, Italy University of Siena, Siena, Italy c IstitutoToscanoTumori, Firenze, Italy d Unit of Radiation Oncology, University Hospital of Siena, Siena, Italy e Unit of Medical Imaging, University Hospital of Siena, Siena, Italy f IMIV, CEA, Inserm, CNRS, Univ. Paris-Sud, Université Paris Saclay, CEA-SHFJ, 91 400 Orsay, France b
Purpose. The purpose of this retrospective study was to This retrospective study aims to evaluate the potential use of MRI TA to predict the outcome and relapse of locally advanced rectal cancer (LARC) in patients undergoing Chemo-radiotherapy (C-RT) before radical surgery (TME). Methods. This study regarded patients affected to glioblastoma and treated with concomitant postoperative radiotherapy with before surgery MRI exams (T1, This study included patients treated with C-RT (45 Gy + 9 Gy 1,8 Gy/day and capecitabine) at our Radiation Oncology Unit between January 2010 and December 2015. Another inclusion criterion was the execution of pelvic MRI (T2 and DWI) examinations (1.5-T system, Signa Excite HD, GE) made at baseline, 30 ± 15 days after the end of C-RT and at 9–12 weeks after TME. The use of Mandard score permits to evaluate the tumour regression grade (TRG). To calculate TA parameters calculation and
128
Abstracts / Physica Medica 56 (2018) 59–132
Characteristic
Number and Percentage
Sex Males Females
28 (74%) 10 (26%)
<70 years >70 years
23 (60%) 15 (40%)
Age
Stage (T) cT2 cT3 cT4
5 (13%) 26 (68%) 7 (19%)
Stage (N) cN0 cN1
6 (16%) 32 (84%)
Grading G1 G2 G3
3 (8%) 30 (79%) 5 (13%)
TRG 1 2 3 4
9 (23%) 14 (37%) 13 (34%) 2 (5%)
ePD Yes No
8 (21%) 30 (79%)
to perform the necessary statistical analysis is possible with the programs LifeX and SPSS. The research of the correlation of TA parameters and multiple prognostic factors with early progression of disease (ePD) was the primary focus of this study. The omission of the variables with the lowest Pearson correlation coefficient permitted to avoid the model overfitting. With k-fold and ROC analysis was possible to validate our performance model. Results. This study included 73 patient38 patients included in this study had characteristic reported in the table. The reliability analysis performed with ICC showed that the TA parameters that resulted significantly reproducible (ICC > 0.70) were 48% for the T2, 56% for the DWI and 84% for the ADC. The figure shows Pearson correlation analysis significant results. Logistic regression also showed a significant association of DWI GLCM Correlation
(p:0.006) and T stage (p:0.036), with an overall R2 of 0.641, a ROC AUC of 0.938 (95% CI 0.854–1.00) and a successful k-fold validation. 38 patients included in this study had characteristic reported in the table. The reliability analysis performed with ICC showed that the TA parameters that resulted significantly reproducible (ICC > 0.70) were 48% for the T2, 56% for the DWI and 84% for the ADC. The figure shows Pearson correlation analysis significant results. Logistic regression also showed a significant association of DWI GLCM Correlation (p:0.006) and T stage (p:0.036), with an overall R2 of 0.641, a ROC AUC of 0.938 (95% CI 0.854-1.00) and a successful k-fold validation. Conclusion. This study shows that there is a correlation between TA GLCM parameters ex A non-invasive mathematical analysis of MRI imaging such as TA, can be used to predict the outcome of patients with LARC and may help to the selection of patients who need additional treatments over the classical neoadjuvant C-RT. https://doi.org/10.1016/j.ejmp.2018.04.117
108. Verification of skin dose values calculated by a dose tracking software using GAFCHROMIC films measurements F. Rottoli a, C. De Mattia a, M. Sutto a, P.E. Colombo a, A. Rampoldi b, A. Torresin a a
ASST Grande Ospedale Metropolitano Niguarda, S.C. Fisica Sanitaria, Milano, Italy b ASST Grande Ospedale Metropolitano Niguarda, S.C. Radiologia Interventistica, Milano, Italy Purpose . To compare skin dose values and their spatial distribution obtained with the radiation dose tracking software with measurements on gafchromic films on phantom and patients. Methods. In NEXO[DOSE]Ò (Bracco, Milan) the distribution of skin dose of interventional radiology procedures is calculated on the surface of a mathematical torso phantom using exposure parameters of each irradiation event from the Radiation Dose Structured Report and additional angiography-specific information (table and mattress
127
Table 1 mean and one SD of ratios between a selection of features computed at tracer activity levels A and at full tracer activity for Fixed VOIs and R64 resampling; (*) statistical significance at 0.01, Bonferroni correction applied (Intensity Direct (ID), Gray-Level Cooccurence Matrix 3D (GLCM), Gray-Level Run Length Matrix 2D (GLRLM)).
Global Entropy (ID) Difference Entropy (GLCM) Inverse difference moment normalized (GLCM) Low grey-level run emphasis (GLRLM) High grey-level run emphasis (GLRLM)
A = 0.6 MBq/kg
A = 1.2 MBq/kg
A = 1.5 MBq/kg
A = 1.8 MBq/kg
A = 2.4 MBq/kg
1.01 ± 0.03 1.00 ± 0.03
1.01 ± 0.03 1.00 ± 0.02
1.01 ± 0.02 1.00 ± 0.02
1.00 ± 0.02 1.00 ± 0.02
1.00 ± 0.02 1.00 ± 0.02
1.00 ± 0.01 1.13 ± 0.39 0.95 ± 0.17 (*)
1.00 ± 0.01 1.16 ± 0.49 0.98 ± 0.14
1.00 ± 0.01 1.16 ± 0.43 0.98 ± 0.13
1.00 ± 0.01 1.10 ± 0.34 0.97 ± 0.11
1.00 ± 0.01 1.09 ± 0.27 0.98 ± 0.06
Figure: coronal view of a patient for standard injected activity of 3 MBq/kg and simulated activity of 1.5 and 0.6 MBq/kg (from left to right) with ROI contour.
a
Conclusions. Selected PET radiomic features can provide reliable information of tumor heterogeneity for low-activity pediatric protocols depending on SUV resampling and lesion delineation strategies.
Reference 1. Yan J, Chu-Shern JL, Loi HY, et al.. Impact of image reconstruction settings on texture features in 18F-FDG PET. J Nucl Med 2015;56(11):1667–73. https://doi.org/10.1016/j.ejmp.2018.04.116
107. Magnetic-resonance-imaging texture analysis predicts early progression in rectal cancer patients undergoing neoadjuvant chemo-radiation M. Biondi a,b, E. Vanzi a, G. De Otto a, G. Belmonte a, V. Nardone c,d, A. Cirigliano e, A. Grassi e, S.F. Carbone e, P. Tini c,d, L. Sebaste c,d, T. Carfagno c,d, G. Battaglia c,d, G. Rubino c,d, P. Pastina c,d, P. Correale c,d, C. Nioche f, L. Pirtoli c,d, F. Banci Buonamici a
Unit of Medical Physics, University Hospital of Siena, Siena, Italy University of Siena, Siena, Italy c IstitutoToscanoTumori, Firenze, Italy d Unit of Radiation Oncology, University Hospital of Siena, Siena, Italy e Unit of Medical Imaging, University Hospital of Siena, Siena, Italy f IMIV, CEA, Inserm, CNRS, Univ. Paris-Sud, Université Paris Saclay, CEA-SHFJ, 91 400 Orsay, France b
Purpose. The purpose of this retrospective study was to This retrospective study aims to evaluate the potential use of MRI TA to predict the outcome and relapse of locally advanced rectal cancer (LARC) in patients undergoing Chemo-radiotherapy (C-RT) before radical surgery (TME). Methods. This study regarded patients affected to glioblastoma and treated with concomitant postoperative radiotherapy with before surgery MRI exams (T1, This study included patients treated with C-RT (45 Gy + 9 Gy 1,8 Gy/day and capecitabine) at our Radiation Oncology Unit between January 2010 and December 2015. Another inclusion criterion was the execution of pelvic MRI (T2 and DWI) examinations (1.5-T system, Signa Excite HD, GE) made at baseline, 30 ± 15 days after the end of C-RT and at 9–12 weeks after TME. The use of Mandard score permits to evaluate the tumour regression grade (TRG). To calculate TA parameters calculation and
128
Abstracts / Physica Medica 56 (2018) 59–132
Characteristic
Number and Percentage
Sex Males Females
28 (74%) 10 (26%)
<70 years >70 years
23 (60%) 15 (40%)
Age
Stage (T) cT2 cT3 cT4
5 (13%) 26 (68%) 7 (19%)
Stage (N) cN0 cN1
6 (16%) 32 (84%)
Grading G1 G2 G3
3 (8%) 30 (79%) 5 (13%)
TRG 1 2 3 4
9 (23%) 14 (37%) 13 (34%) 2 (5%)
ePD Yes No
8 (21%) 30 (79%)
to perform the necessary statistical analysis is possible with the programs LifeX and SPSS. The research of the correlation of TA parameters and multiple prognostic factors with early progression of disease (ePD) was the primary focus of this study. The omission of the variables with the lowest Pearson correlation coefficient permitted to avoid the model overfitting. With k-fold and ROC analysis was possible to validate our performance model. Results. This study included 73 patient38 patients included in this study had characteristic reported in the table. The reliability analysis performed with ICC showed that the TA parameters that resulted significantly reproducible (ICC > 0.70) were 48% for the T2, 56% for the DWI and 84% for the ADC. The figure shows Pearson correlation analysis significant results. Logistic regression also showed a significant association of DWI GLCM Correlation
(p:0.006) and T stage (p:0.036), with an overall R2 of 0.641, a ROC AUC of 0.938 (95% CI 0.854–1.00) and a successful k-fold validation. 38 patients included in this study had characteristic reported in the table. The reliability analysis performed with ICC showed that the TA parameters that resulted significantly reproducible (ICC > 0.70) were 48% for the T2, 56% for the DWI and 84% for the ADC. The figure shows Pearson correlation analysis significant results. Logistic regression also showed a significant association of DWI GLCM Correlation (p:0.006) and T stage (p:0.036), with an overall R2 of 0.641, a ROC AUC of 0.938 (95% CI 0.854-1.00) and a successful k-fold validation. Conclusion. This study shows that there is a correlation between TA GLCM parameters ex A non-invasive mathematical analysis of MRI imaging such as TA, can be used to predict the outcome of patients with LARC and may help to the selection of patients who need additional treatments over the classical neoadjuvant C-RT. https://doi.org/10.1016/j.ejmp.2018.04.117
108. Verification of skin dose values calculated by a dose tracking software using GAFCHROMIC films measurements F. Rottoli a, C. De Mattia a, M. Sutto a, P.E. Colombo a, A. Rampoldi b, A. Torresin a a
ASST Grande Ospedale Metropolitano Niguarda, S.C. Fisica Sanitaria, Milano, Italy b ASST Grande Ospedale Metropolitano Niguarda, S.C. Radiologia Interventistica, Milano, Italy Purpose . To compare skin dose values and their spatial distribution obtained with the radiation dose tracking software with measurements on gafchromic films on phantom and patients. Methods. In NEXO[DOSE]Ò (Bracco, Milan) the distribution of skin dose of interventional radiology procedures is calculated on the surface of a mathematical torso phantom using exposure parameters of each irradiation event from the Radiation Dose Structured Report and additional angiography-specific information (table and mattress