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Erschienen in: Strahlentherapie und Onkologie 8/2022

21.01.2022 | Original Article

Radiomics-based prognosis classification for high-risk prostate cancer treated with radiotherapy

verfasst von: Ciro Franzese, MD, Luca Cozzi, PhD, Marco Badalamenti, MD, Davide Baldaccini, MD, Giuseppe D’Agostino, MD, Antonella Fogliata, MSc, Pierina Navarria, MD, Davide Franceschini, MD, Tiziana Comito, MD, Elena Clerici, MD, Giacomo Reggiori, MSc, Stefano Tomatis, MSc, Marta Scorsetti, MD

Erschienen in: Strahlentherapie und Onkologie | Ausgabe 8/2022

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Abstract

Objective

The present study aimed to investigate if CT-based radiomics features could correlate to the risk of metastatic progression in high-risk prostate cancer patients treated with radical RT and long-term androgen deprivation therapy (ADT).

Materials and methods

A total of 157 patients were investigated and radiomics features extracted from the contrast-free treatment planning CT series. Three volumes were segmented: the prostate gland only (CTV_p), the prostate gland with seminal vesicles (CTV_psv), and the seminal vesicles only (CTV_sv). The patients were split into two subgroups of 100 and 57 patients for training and validation. Five clinical and 62 radiomics features were included in the analysis. Considering metastases-free survival (MFS) as an endpoint, the predictive model was used to identify the subgroups with favorable or unfavorable prognoses (separated by a threshold selected according to the Youden method). Pure clinical, pure radiomic, and combined predictive models were investigated.

Results

With a median follow-up of 30.7 months, the MFS at 1 and 3 years was 97.2% ± 1.5 and 92.1% ± 2.0, respectively. Univariate analysis identified seven potential predictors for MFS in the CTV_p group, 11 in the CTV_psv group, and 9 in the CTV_sv group. After elastic net reduction, these were 4 predictors for MFS in the CTV_p group (positive lymph nodes, Gleason score, H_Skewness, and NGLDM_Contrast), 5 in the CTV_psv group (positive lymph nodes, Gleason score, H_Skewnesss, Shape_Surface, and NGLDM_Contrast), and 6 in the CTV_sv group (positive lymph nodes, Gleason score, H_Kurtosis, GLCM_Correlation, GLRLM_LRHGE, and GLZLM_SZLGE). The patients’ group of the training and validation cohorts were stratified into favorable and unfavorable prognosis subgroups. For the combined model, for CTV_p, the mean MFS was 134 ± 14.5 vs. 96.9 ± 22.2 months for the favorable and unfavorable subgroups, respectively, and 136.5 ± 14.6 vs. 70.5 ± 4.3 months for CTV_psv and 150.0 ± 4.2 vs. 91.1 ± 8.6 months for CTV_sv, respectively.

Conclusion

Radiomic features were able to predict the risk of metastatic progression in high-risk prostate cancer. Combining the radiomic features and clinical characteristics can classify high-risk patients into favorable and unfavorable prognostic groups.
Literatur
1.
Zurück zum Zitat Gillies R, Schabath M (2020) Radiomics improves cancer screening and early detection. Cancer Epidemiol Biomarkers Prev 29:2556–2567CrossRef Gillies R, Schabath M (2020) Radiomics improves cancer screening and early detection. Cancer Epidemiol Biomarkers Prev 29:2556–2567CrossRef
2.
Zurück zum Zitat Schick U, Lucia F, Bourbonne V, Dissaux G, Pradier O, Jaouen V et al (2020) Use of radiomics in the radiation oncology setting: Where do we stand and what do we need? Cancer/Radiothérapie 24:755–761CrossRef Schick U, Lucia F, Bourbonne V, Dissaux G, Pradier O, Jaouen V et al (2020) Use of radiomics in the radiation oncology setting: Where do we stand and what do we need? Cancer/Radiothérapie 24:755–761CrossRef
3.
Zurück zum Zitat Cozzi L, Comito T, Fogliata A, Franzese C, Franceschini D, Bonifacio C et al (2019) Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma. PLoS One 14:e0210758CrossRef Cozzi L, Comito T, Fogliata A, Franzese C, Franceschini D, Bonifacio C et al (2019) Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma. PLoS One 14:e0210758CrossRef
4.
Zurück zum Zitat Cozzi L, Franzese C, Fogliata A, Franceschini D, Navarria P, Tomatis S et al (2019) Predicting survival and local control after radiochemotherapy in locally advanced head and neck cancer by means of computed tomography based radiomics. Strahlenther Onkol 195:805–818CrossRef Cozzi L, Franzese C, Fogliata A, Franceschini D, Navarria P, Tomatis S et al (2019) Predicting survival and local control after radiochemotherapy in locally advanced head and neck cancer by means of computed tomography based radiomics. Strahlenther Onkol 195:805–818CrossRef
5.
Zurück zum Zitat Wibmer A, Hricak H, Gondo T, Matsumoto K, Veeraraghavan H, Fehr D et al (2015) Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores. Eur Radiol 25:2840–2850CrossRef Wibmer A, Hricak H, Gondo T, Matsumoto K, Veeraraghavan H, Fehr D et al (2015) Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores. Eur Radiol 25:2840–2850CrossRef
6.
Zurück zum Zitat Vignati A, Mazzetti S, Giannini V, Russo F, Bollito E, Porpiglia F et al (2015) Texture features on T2-weighted magnetic resonance imaging: New potential biomarkers for prostate cancer aggressiveness. Phys Med Biol 60:2685–2701CrossRef Vignati A, Mazzetti S, Giannini V, Russo F, Bollito E, Porpiglia F et al (2015) Texture features on T2-weighted magnetic resonance imaging: New potential biomarkers for prostate cancer aggressiveness. Phys Med Biol 60:2685–2701CrossRef
7.
Zurück zum Zitat Fehr D, Veeraraghavan H, Wibmer A, Gondo T, Matsumoto K, Vargas HA et al (2015) Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images. Proc Natl Acad Sci U S A 112:E6265–73CrossRef Fehr D, Veeraraghavan H, Wibmer A, Gondo T, Matsumoto K, Vargas HA et al (2015) Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images. Proc Natl Acad Sci U S A 112:E6265–73CrossRef
8.
Zurück zum Zitat Mostafaei S, Abdollahi H, Kazempour Dehkordi S, Shiri I, Razzaghdoust A, Zoljalali Moghaddam SH et al (2020) CT imaging markers to improve radiation toxicity prediction in prostate cancer radiotherapy by stacking regression algorithm. Radiol Med 125:87–97CrossRef Mostafaei S, Abdollahi H, Kazempour Dehkordi S, Shiri I, Razzaghdoust A, Zoljalali Moghaddam SH et al (2020) CT imaging markers to improve radiation toxicity prediction in prostate cancer radiotherapy by stacking regression algorithm. Radiol Med 125:87–97CrossRef
9.
10.
Zurück zum Zitat Franzese C, Fogliata A, D’Agostino GR, Di Brina L, Comito T, Navarria P et al (2017) Moderate hypofractionated radiotherapy with volumetric modulated arc therapy and simultaneous integrated boost for pelvic irradiation in prostate cancer. J Cancer Res Clin Oncol 143:1301–1309CrossRef Franzese C, Fogliata A, D’Agostino GR, Di Brina L, Comito T, Navarria P et al (2017) Moderate hypofractionated radiotherapy with volumetric modulated arc therapy and simultaneous integrated boost for pelvic irradiation in prostate cancer. J Cancer Res Clin Oncol 143:1301–1309CrossRef
11.
Zurück zum Zitat Yao L, Shou J, Wang S, Song Y, Fang H, Lu N et al (2020) Long-term outcomes of moderately hypofractionated radiotherapy (67.5 Gy in 25 fractions) for prostate cancer confined to the pelvis: a single center retrospective analysis. Radiat Oncol 15:231CrossRef Yao L, Shou J, Wang S, Song Y, Fang H, Lu N et al (2020) Long-term outcomes of moderately hypofractionated radiotherapy (67.5 Gy in 25 fractions) for prostate cancer confined to the pelvis: a single center retrospective analysis. Radiat Oncol 15:231CrossRef
12.
Zurück zum Zitat Nioche C, Orlhac F, Boughdad S, Reuze S, Goya-Outi J, Robert C et al (2018) Lifex: A freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterisation of tumor heterogeneity. Cancer Res 78:4786–4789CrossRef Nioche C, Orlhac F, Boughdad S, Reuze S, Goya-Outi J, Robert C et al (2018) Lifex: A freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterisation of tumor heterogeneity. Cancer Res 78:4786–4789CrossRef
13.
Zurück zum Zitat Collins GS, Reitsma JB, Altman DG, Moons KGM (2015) Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD Statement. Eur Urol 67:1142–1151CrossRef Collins GS, Reitsma JB, Altman DG, Moons KGM (2015) Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD Statement. Eur Urol 67:1142–1151CrossRef
14.
Zurück zum Zitat Youden WJ (1950) Index for rating diagnostic tests. Cancer 3:32–35CrossRef Youden WJ (1950) Index for rating diagnostic tests. Cancer 3:32–35CrossRef
16.
Zurück zum Zitat Moris L, Cumberbatch MG, Van den Broeck T, Gandaglia G, Fossati N, Kelly B et al (2020) Benefits and risks of primary treatments for high-risk localized and locally advanced prostate cancer: an international multidisciplinary systematic review. Eur Urol 77:614–627CrossRef Moris L, Cumberbatch MG, Van den Broeck T, Gandaglia G, Fossati N, Kelly B et al (2020) Benefits and risks of primary treatments for high-risk localized and locally advanced prostate cancer: an international multidisciplinary systematic review. Eur Urol 77:614–627CrossRef
17.
Zurück zum Zitat Bolla M, Collette L, Blank L, Warde P, Dubois JB, Mirimanoff RO et al (2002) Long-term results with immediate androgen suppression and external irradiation in patients with locally advanced prostate cancer (an EORTC study): A phase III randomised trial. Lancet 360:103–108CrossRef Bolla M, Collette L, Blank L, Warde P, Dubois JB, Mirimanoff RO et al (2002) Long-term results with immediate androgen suppression and external irradiation in patients with locally advanced prostate cancer (an EORTC study): A phase III randomised trial. Lancet 360:103–108CrossRef
18.
Zurück zum Zitat Ramón y Cajal S, Sesé M, Capdevila C, Aasen T, De Mattos-Arruda L, Diaz-Cano SJ et al (2020) Clinical implications of intratumor heterogeneity: challenges and opportunities. Mol Med 98:161–177CrossRef Ramón y Cajal S, Sesé M, Capdevila C, Aasen T, De Mattos-Arruda L, Diaz-Cano SJ et al (2020) Clinical implications of intratumor heterogeneity: challenges and opportunities. Mol Med 98:161–177CrossRef
19.
Zurück zum Zitat Caswell DR, Swanton C (2017) The role of tumour heterogeneity and clonal cooperativity in metastasis, immune evasion and clinical outcome. BMC Med 15:133CrossRef Caswell DR, Swanton C (2017) The role of tumour heterogeneity and clonal cooperativity in metastasis, immune evasion and clinical outcome. BMC Med 15:133CrossRef
20.
Zurück zum Zitat Schweizer MT, Zhou XC, Wang H, Yang T, Shaukat F, Partin AW et al (2013) Metastasis-free survival is associated with overall survival in men with PSA-recurrent prostate cancer treated with deferred androgen deprivation therapy. Ann Oncol 24:2881–2886CrossRef Schweizer MT, Zhou XC, Wang H, Yang T, Shaukat F, Partin AW et al (2013) Metastasis-free survival is associated with overall survival in men with PSA-recurrent prostate cancer treated with deferred androgen deprivation therapy. Ann Oncol 24:2881–2886CrossRef
21.
Zurück zum Zitat Bosetti DG, Ruinelli L, Piliero MA, van der Gaag LC, Pesce GA, Valli M et al (2020) Cone-beam computed tomography-based radiomics in prostate cancer: a mono-institutional study. Strahlenther Onkol 196:943–951CrossRef Bosetti DG, Ruinelli L, Piliero MA, van der Gaag LC, Pesce GA, Valli M et al (2020) Cone-beam computed tomography-based radiomics in prostate cancer: a mono-institutional study. Strahlenther Onkol 196:943–951CrossRef
22.
Zurück zum Zitat Osman S, Leijenaar R, Cole A, Lyons C, Hounsell A, Prise K et al (2019) Computed tomography-based radiomics for risk stratification in prostate cancer. Int J Radiat Oncol Biol Phys 105:448–456CrossRef Osman S, Leijenaar R, Cole A, Lyons C, Hounsell A, Prise K et al (2019) Computed tomography-based radiomics for risk stratification in prostate cancer. Int J Radiat Oncol Biol Phys 105:448–456CrossRef
23.
Zurück zum Zitat Tanadini-Lang S, Bogowicz M, Veit-Haibach P, Huellner M, Pauli C, Shukla V et al (2018) Exploratory radiomics in computed tomography perfusion of prostate cancer. Anticancer Res 38:685–690PubMed Tanadini-Lang S, Bogowicz M, Veit-Haibach P, Huellner M, Pauli C, Shukla V et al (2018) Exploratory radiomics in computed tomography perfusion of prostate cancer. Anticancer Res 38:685–690PubMed
24.
Zurück zum Zitat Bautista J, Houshyar R, Verma S, Uchio E, Lall C (2016) Prostate cancer on computed tomography: a direct comparison with multi-parametric magnetic resonance imaging and tissue pathology. Eur J Radiol 85:261–267CrossRef Bautista J, Houshyar R, Verma S, Uchio E, Lall C (2016) Prostate cancer on computed tomography: a direct comparison with multi-parametric magnetic resonance imaging and tissue pathology. Eur J Radiol 85:261–267CrossRef
25.
Zurück zum Zitat Kim B, Kawashima A, Ryu J, Takahashi N, Hartman R, King B (2009) Imaging of the seminal vescicle and vas deferens. Radiographics 29(4):1105–1121CrossRef Kim B, Kawashima A, Ryu J, Takahashi N, Hartman R, King B (2009) Imaging of the seminal vescicle and vas deferens. Radiographics 29(4):1105–1121CrossRef
26.
Zurück zum Zitat Glazer D, Davenport M, Khalatbari S, Cohan R, Ellis J, Caoili E et al (2015) Mass-like peripheral zone enhancement on CT is predictive of higher grade (Gleason 4+3) and higher prostate cancer. Abdom Imaging 40(3):560–570CrossRef Glazer D, Davenport M, Khalatbari S, Cohan R, Ellis J, Caoili E et al (2015) Mass-like peripheral zone enhancement on CT is predictive of higher grade (Gleason 4+3) and higher prostate cancer. Abdom Imaging 40(3):560–570CrossRef
27.
Zurück zum Zitat Delgadillo R, Ford JC, Abramowitz MC, Dal Pra A, Pollack A, Stoyanova R (2020) The role of radiomics in prostate cancer radiotherapy. Strahlenther Onkol 196:900–912CrossRef Delgadillo R, Ford JC, Abramowitz MC, Dal Pra A, Pollack A, Stoyanova R (2020) The role of radiomics in prostate cancer radiotherapy. Strahlenther Onkol 196:900–912CrossRef
28.
Zurück zum Zitat Gugliandolo SG, Pepa M, Isaksson LJ, Marvaso G, Raimondi S, Botta F et al (2020) MRI-based radiomics signature for localized prostate cancer: a new clinical tool for cancer aggressiveness prediction? Sub-study of prospective phase II trial on ultra-hypofractionated radiotherapy (AIRC IG-13218). Eur Radiol 31:716–728 Gugliandolo SG, Pepa M, Isaksson LJ, Marvaso G, Raimondi S, Botta F et al (2020) MRI-based radiomics signature for localized prostate cancer: a new clinical tool for cancer aggressiveness prediction? Sub-study of prospective phase II trial on ultra-hypofractionated radiotherapy (AIRC IG-13218). Eur Radiol 31:716–728
29.
Zurück zum Zitat Gnep K, Fargeas A, Gutiérrez-Carvajal RE, Commandeur F, Mathieu R, Ospina JD et al (2017) Haralick textural features on T 2 -weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer. J Magn Reson Imaging 45:103–117CrossRef Gnep K, Fargeas A, Gutiérrez-Carvajal RE, Commandeur F, Mathieu R, Ospina JD et al (2017) Haralick textural features on T 2 -weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer. J Magn Reson Imaging 45:103–117CrossRef
Metadaten
Titel
Radiomics-based prognosis classification for high-risk prostate cancer treated with radiotherapy
verfasst von
Ciro Franzese, MD
Luca Cozzi, PhD
Marco Badalamenti, MD
Davide Baldaccini, MD
Giuseppe D’Agostino, MD
Antonella Fogliata, MSc
Pierina Navarria, MD
Davide Franceschini, MD
Tiziana Comito, MD
Elena Clerici, MD
Giacomo Reggiori, MSc
Stefano Tomatis, MSc
Marta Scorsetti, MD
Publikationsdatum
21.01.2022
Verlag
Springer Berlin Heidelberg
Erschienen in
Strahlentherapie und Onkologie / Ausgabe 8/2022
Print ISSN: 0179-7158
Elektronische ISSN: 1439-099X
DOI
https://doi.org/10.1007/s00066-021-01886-y

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