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Erschienen in: European Radiology 12/2022

28.06.2022 | Neuro

Adding radiomics to the 2021 WHO updates may improve prognostic prediction for current IDH-wildtype histological lower-grade gliomas with known EGFR amplification and TERT promoter mutation status

verfasst von: Yae Won Park, Sooyon Kim, Chae Jung Park, Sung Soo Ahn, Kyunghwa Han, Seok-Gu Kang, Jong Hee Chang, Se Hoon Kim, Seung-Koo Lee

Erschienen in: European Radiology | Ausgabe 12/2022

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Abstract

Objectives

To assess whether radiomic features could improve the accuracy of survival predictions of IDH-wildtype (IDHwt) histological lower-grade gliomas (LGGs) over clinicopathological features.

Methods

Preoperative MRI data of 61 patients with IDHwt histological LGGs were included as the institutional training set. The test set consisted of 32 patients from The Cancer Genome Atlas. Radiomic features (n = 186) were extracted using conventional MRIs. The radiomics risk score (RRS) for overall survival (OS) was derived from the elastic net. Multivariable Cox regression analyses with clinicopathological features (including epidermal growth factor receptor [EGFR] amplification and telomerase reverse transcriptase promoter [TERTp] mutation status) and the RRS were performed. The integrated area under the receiver operating curves (iAUCs) from the models with and without the RRS were compared. The net reclassification index (NRI) for 1-year OS was also calculated. The prognostic value of the RRS was evaluated using the external validation set.

Results

The RRS independently predicted OS (hazard ratio = 48.08; p = 0.001). Compared with the clinicopathological model alone, adding the RRS had a better OS prediction performance (iAUCs 0.775 vs. 0.910), which was internally validated (iAUCs 0.726 vs. 0.884, 1-year OS NRI = 0.497), and a similar trend was found on external validation (iAUCs 0.683 vs. 0.705, 1-year OS NRI = 0.733). The prognostic significance of the RRS was confirmed in the external validation set (p = 0.001).

Conclusions

Integrating radiomics with clinicopathological features (including EGFR amplification and TERTp mutation status) can improve survival prediction in patients with IDHwt LGGs.

Key Points

• Radiomics risk score has the potential to improve survival prediction when added to clinicopathological features (iAUCs increased from 0.775 to 0.910).
• NRIs for 1-year OS showed that the radiomics risk score had incremental value over the clinicopathological model.
• The prognostic significance of the radiomics risk score was confirmed in the external validation set (p = 0.001).
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Literatur
2.
Zurück zum Zitat Aibaidula A, Chan AK-Y, Shi Z et al (2017) Adult IDH wild-type lower-grade gliomas should be further stratified. Neuro Oncol 19:1327–1337 PubMedPubMedCentral Aibaidula A, Chan AK-Y, Shi Z et al (2017) Adult IDH wild-type lower-grade gliomas should be further stratified. Neuro Oncol 19:1327–1337 PubMedPubMedCentral
3.
Zurück zum Zitat Wijnenga MM, Dubbink HJ, French PJ et al (2017) Molecular and clinical heterogeneity of adult diffuse low-grade IDH wild-type gliomas: assessment of TERT promoter mutation and chromosome 7 and 10 copy number status allows superior prognostic stratification. Acta Neuropathol 134:957–959 PubMed Wijnenga MM, Dubbink HJ, French PJ et al (2017) Molecular and clinical heterogeneity of adult diffuse low-grade IDH wild-type gliomas: assessment of TERT promoter mutation and chromosome 7 and 10 copy number status allows superior prognostic stratification. Acta Neuropathol 134:957–959 PubMed
4.
Zurück zum Zitat Tesileanu CMS, Dirven L, Wijnenga MMJ et al (2020) Survival of diffuse astrocytic glioma, IDH1/2 wildtype, with molecular features of glioblastoma, WHO grade IV: a confirmation of the cIMPACT-NOW criteria. Neuro Oncol 22:515–523 PubMed Tesileanu CMS, Dirven L, Wijnenga MMJ et al (2020) Survival of diffuse astrocytic glioma, IDH1/2 wildtype, with molecular features of glioblastoma, WHO grade IV: a confirmation of the cIMPACT-NOW criteria. Neuro Oncol 22:515–523 PubMed
5.
Zurück zum Zitat Louis DN, Wesseling P, Aldape K et al (2020) cIMPACT-NOW update 6: new entity and diagnostic principle recommendations of the cIMPACT-Utrecht meeting on future CNS tumor classification and grading. Brain Pathol 30:844–856 PubMedPubMedCentral Louis DN, Wesseling P, Aldape K et al (2020) cIMPACT-NOW update 6: new entity and diagnostic principle recommendations of the cIMPACT-Utrecht meeting on future CNS tumor classification and grading. Brain Pathol 30:844–856 PubMedPubMedCentral
6.
Zurück zum Zitat Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577 PubMed Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577 PubMed
7.
Zurück zum Zitat Park YW, Han K, Ahn SS et al (2018) Whole-tumor histogram and texture analyses of DTI for evaluation of IDH1-mutation and 1p/19q-codeletion status in World Health Organization Grade II Gliomas. AJNR Am J Neuroradiol 39:693–698 PubMedPubMedCentral Park YW, Han K, Ahn SS et al (2018) Whole-tumor histogram and texture analyses of DTI for evaluation of IDH1-mutation and 1p/19q-codeletion status in World Health Organization Grade II Gliomas. AJNR Am J Neuroradiol 39:693–698 PubMedPubMedCentral
8.
Zurück zum Zitat Park YW, Lee N, Ahn SS, Chang JH, Lee SK (2021) "Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications." Investig Magn Reson Imaging 25(4):266–280 Park YW, Lee N, Ahn SS, Chang JH, Lee SK (2021) "Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications." Investig Magn Reson Imaging 25(4):266–280
9.
Zurück zum Zitat Choi KS, Sunwoo L (2022) "Artificial Intelligence in Neuroimaging: Clinical Applications." Investig Magn Reson Imaging 26(1):1–9 Choi KS, Sunwoo L (2022) "Artificial Intelligence in Neuroimaging: Clinical Applications." Investig Magn Reson Imaging 26(1):1–9
10.
Zurück zum Zitat Choi YS, Ahn SS, Chang JH et al (2020) Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction. Eur Radiol 30:3834–3842 PubMed Choi YS, Ahn SS, Chang JH et al (2020) Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction. Eur Radiol 30:3834–3842 PubMed
11.
Zurück zum Zitat Beig N, Bera K, Prasanna P et al (2020) Radiogenomic-based survival risk stratification of tumor habitat on Gd-T1w MRI is associated with biological processes in glioblastoma. Clin Cancer Res 26:1866–1876 PubMedPubMedCentral Beig N, Bera K, Prasanna P et al (2020) Radiogenomic-based survival risk stratification of tumor habitat on Gd-T1w MRI is associated with biological processes in glioblastoma. Clin Cancer Res 26:1866–1876 PubMedPubMedCentral
12.
Zurück zum Zitat Bae S, Choi YS, Ahn SS et al (2018) Radiomic MRI phenotyping of glioblastoma: improving survival prediction. Radiology 289:797–806 PubMed Bae S, Choi YS, Ahn SS et al (2018) Radiomic MRI phenotyping of glioblastoma: improving survival prediction. Radiology 289:797–806 PubMed
13.
Zurück zum Zitat Park JE, Kim HS, Jo Y et al (2020) Radiomics prognostication model in glioblastoma using diffusion- and perfusion-weighted MRI. Sci Rep 10:4250 PubMedPubMedCentral Park JE, Kim HS, Jo Y et al (2020) Radiomics prognostication model in glioblastoma using diffusion- and perfusion-weighted MRI. Sci Rep 10:4250 PubMedPubMedCentral
14.
Zurück zum Zitat Choi Y, Nam Y, Jang J et al (2021) Radiomics may increase the prognostic value for survival in glioblastoma patients when combined with conventional clinical and genetic prognostic models. Eur Radiol 31:2084–2093 PubMed Choi Y, Nam Y, Jang J et al (2021) Radiomics may increase the prognostic value for survival in glioblastoma patients when combined with conventional clinical and genetic prognostic models. Eur Radiol 31:2084–2093 PubMed
15.
Zurück zum Zitat Park CJ, Han K, Kim H et al (2020) Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas. Eur Radiol 30:6464–6474 PubMed Park CJ, Han K, Kim H et al (2020) Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas. Eur Radiol 30:6464–6474 PubMed
16.
17.
Zurück zum Zitat Park YW, Han k, Ahn SS et al. (2018) "Prediction of IDH1-mutation and 1p/19q-codeletion status using preoperative MR imaging phenotypes in lower grade gliomas." AJNR Am J Neuroradiol 39(1):37–42 Park YW, Han k, Ahn SS et al. (2018) "Prediction of IDH1-mutation and 1p/19q-codeletion status using preoperative MR imaging phenotypes in lower grade gliomas." AJNR Am J Neuroradiol 39(1):37–42
18.
Zurück zum Zitat Sahm F, Schrimpf D, Jones DT et al (2016) Next-generation sequencing in routine brain tumor diagnostics enables an integrated diagnosis and identifies actionable targets. Acta Neuropathol 131:903–910 PubMed Sahm F, Schrimpf D, Jones DT et al (2016) Next-generation sequencing in routine brain tumor diagnostics enables an integrated diagnosis and identifies actionable targets. Acta Neuropathol 131:903–910 PubMed
19.
Zurück zum Zitat Na K, Kim H-S, Shim HS, Chang JH, Kang S-G, Kim SH (2019) Targeted next-generation sequencing panel (TruSight Tumor 170) in diffuse glioma: a single institutional experience of 135 cases. J Neurooncol 142:445–454 Na K, Kim H-S, Shim HS, Chang JH, Kang S-G, Kim SH (2019) Targeted next-generation sequencing panel (TruSight Tumor 170) in diffuse glioma: a single institutional experience of 135 cases. J Neurooncol 142:445–454
20.
Zurück zum Zitat Bakas S, Akbari H, Sotiras A et al (2017) Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. Sci Data 4:170117 PubMedPubMedCentral Bakas S, Akbari H, Sotiras A et al (2017) Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. Sci Data 4:170117 PubMedPubMedCentral
21.
Zurück zum Zitat Roy S, Butman JA, Pham DL (2017) Robust skull stripping using multiple MR image contrasts insensitive to pathology. Neuroimage 146:132–147 PubMed Roy S, Butman JA, Pham DL (2017) Robust skull stripping using multiple MR image contrasts insensitive to pathology. Neuroimage 146:132–147 PubMed
22.
Zurück zum Zitat Kickingereder P, Isensee F, Tursunova I et al (2019) Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study. Lancet Oncol 20:728–740 PubMed Kickingereder P, Isensee F, Tursunova I et al (2019) Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study. Lancet Oncol 20:728–740 PubMed
23.
Zurück zum Zitat Park YW,  Eom J, Kim Det al (2022) "A fully automatic multiparametric radiomics model for differentiation of adult pilocytic astrocytomas from high-grade gliomas." Eur Radiol 1–10 Park YW,  Eom J, Kim Det al (2022) "A fully automatic multiparametric radiomics model for differentiation of adult pilocytic astrocytomas from high-grade gliomas." Eur Radiol 1–10
24.
Zurück zum Zitat van Griethuysen JJM, Fedorov A, Parmar C et al (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77:e104–e107 PubMedPubMedCentral van Griethuysen JJM, Fedorov A, Parmar C et al (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77:e104–e107 PubMedPubMedCentral
25.
Zurück zum Zitat Zwanenburg A, Leger S, Vallières M, Löck S (2016) Image biomarker standardisation initiative. arXiv preprint arXiv:161207003 Zwanenburg A, Leger S, Vallières M, Löck S (2016) Image biomarker standardisation initiative. arXiv preprint arXiv:161207003
26.
Zurück zum Zitat Lin LI (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255–268 PubMed Lin LI (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255–268 PubMed
27.
Zurück zum Zitat Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. J R Stat Soc Series B Stat Methodol 67:301–320 Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. J R Stat Soc Series B Stat Methodol 67:301–320
28.
Zurück zum Zitat Simon N, Friedman J, Hastie T, Tibshirani R (2011) Regularization paths for Cox’s proportional hazards model via coordinate descent. J Stat Softw 39:1 PubMedPubMedCentral Simon N, Friedman J, Hastie T, Tibshirani R (2011) Regularization paths for Cox’s proportional hazards model via coordinate descent. J Stat Softw 39:1 PubMedPubMedCentral
29.
Zurück zum Zitat Heagerty PJ, Zheng Y (2005) Survival model predictive accuracy and ROC curves. Biometrics 61:92–105 PubMed Heagerty PJ, Zheng Y (2005) Survival model predictive accuracy and ROC curves. Biometrics 61:92–105 PubMed
30.
Zurück zum Zitat Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723 Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723
31.
Zurück zum Zitat Pencina MJ, D'Agostino RB Sr, Demler OV (2012) Novel metrics for evaluating improvement in discrimination: net reclassification and integrated discrimination improvement for normal variables and nested models. Stat Med 31:101–113 PubMed Pencina MJ, D'Agostino RB Sr, Demler OV (2012) Novel metrics for evaluating improvement in discrimination: net reclassification and integrated discrimination improvement for normal variables and nested models. Stat Med 31:101–113 PubMed
32.
Zurück zum Zitat Olar A, Wani KM, Alfaro-Munoz KD et al (2015) IDH mutation status and role of WHO grade and mitotic index in overall survival in grade II-III diffuse gliomas. Acta Neuropathol 129:585–596 PubMedPubMedCentral Olar A, Wani KM, Alfaro-Munoz KD et al (2015) IDH mutation status and role of WHO grade and mitotic index in overall survival in grade II-III diffuse gliomas. Acta Neuropathol 129:585–596 PubMedPubMedCentral
33.
Zurück zum Zitat Fujimoto K, Arita H, Satomi K et al (2021) TERT promoter mutation status is necessary and sufficient to diagnose IDH-wildtype diffuse astrocytic glioma with molecular features of glioblastoma. Acta Neuropathol 142:323–338 PubMed Fujimoto K, Arita H, Satomi K et al (2021) TERT promoter mutation status is necessary and sufficient to diagnose IDH-wildtype diffuse astrocytic glioma with molecular features of glioblastoma. Acta Neuropathol 142:323–338 PubMed
34.
Zurück zum Zitat Gittleman H, Sloan AE, Barnholtz-Sloan JS (2020) An independently validated survival nomogram for lower-grade glioma. Neuro Oncol 22:665–674 PubMed Gittleman H, Sloan AE, Barnholtz-Sloan JS (2020) An independently validated survival nomogram for lower-grade glioma. Neuro Oncol 22:665–674 PubMed
35.
Zurück zum Zitat Suzuki H, Aoki K, Chiba K et al (2015) Mutational landscape and clonal architecture in grade II and III gliomas. Nat Genet 47:458–468 PubMed Suzuki H, Aoki K, Chiba K et al (2015) Mutational landscape and clonal architecture in grade II and III gliomas. Nat Genet 47:458–468 PubMed
38.
Zurück zum Zitat Liu X, Li Y, Qian Z et al (2018) A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas. Neuroimage Clin 20:1070–1077 PubMedPubMedCentral Liu X, Li Y, Qian Z et al (2018) A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas. Neuroimage Clin 20:1070–1077 PubMedPubMedCentral
39.
Zurück zum Zitat Brat DJ, Aldape K, Colman H et al (2020) cIMPACT-NOW update 5: recommended grading criteria and terminologies for IDH-mutant astrocytomas. Acta Neuropathol 139:603–608 PubMedPubMedCentral Brat DJ, Aldape K, Colman H et al (2020) cIMPACT-NOW update 5: recommended grading criteria and terminologies for IDH-mutant astrocytomas. Acta Neuropathol 139:603–608 PubMedPubMedCentral
40.
Zurück zum Zitat Park YW, Ahn SS, Park CJ et al (2020) Diffusion and perfusion MRI may predict EGFR amplification and the TERT promoter mutation status of IDH-wildtype lower-grade gliomas. Eur Radiol 30:6475–6484 PubMed Park YW, Ahn SS, Park CJ et al (2020) Diffusion and perfusion MRI may predict EGFR amplification and the TERT promoter mutation status of IDH-wildtype lower-grade gliomas. Eur Radiol 30:6475–6484 PubMed
42.
Zurück zum Zitat Park CJ, Han K, Kim H et al (2021) MRI features may predict molecular features of glioblastoma in isocitrate dehydrogenase wild-type lower-grade gliomas. AJNR Am J Neuroradiol 42:448–456 PubMedPubMedCentral Park CJ, Han K, Kim H et al (2021) MRI features may predict molecular features of glioblastoma in isocitrate dehydrogenase wild-type lower-grade gliomas. AJNR Am J Neuroradiol 42:448–456 PubMedPubMedCentral
44.
Zurück zum Zitat Thibault G, Fertil B, Navarro C et al (2013) Shape and texture indexes application to cell nuclei classification. Int J Pattern Recognit Artif Intell 27:1357002 Thibault G, Fertil B, Navarro C et al (2013) Shape and texture indexes application to cell nuclei classification. Int J Pattern Recognit Artif Intell 27:1357002
45.
Zurück zum Zitat Qazi MA, Vora P, Venugopal C et al (2017) Intratumoural heterogeneity: pathways to treatment resistance and relapse in human glioblastoma. Ann Oncol 28:1448–1456 PubMed Qazi MA, Vora P, Venugopal C et al (2017) Intratumoural heterogeneity: pathways to treatment resistance and relapse in human glioblastoma. Ann Oncol 28:1448–1456 PubMed
47.
Zurück zum Zitat Lee JK, Wang J, Sa JK et al (2017) Spatiotemporal genomic architecture informs precision oncology in glioblastoma. Nat Genet 49:594–599 PubMedPubMedCentral Lee JK, Wang J, Sa JK et al (2017) Spatiotemporal genomic architecture informs precision oncology in glioblastoma. Nat Genet 49:594–599 PubMedPubMedCentral
48.
Zurück zum Zitat Aibaidula A, Chan AK, Shi Z et al (2017) Adult IDH wild-type lower-grade gliomas should be further stratified. Neuro Oncol 19:1327–1337 PubMedPubMedCentral Aibaidula A, Chan AK, Shi Z et al (2017) Adult IDH wild-type lower-grade gliomas should be further stratified. Neuro Oncol 19:1327–1337 PubMedPubMedCentral
49.
Zurück zum Zitat Zwanenburg A, Vallières M, Abdalah MA et al (2020) The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295:328–338 PubMed Zwanenburg A, Vallières M, Abdalah MA et al (2020) The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295:328–338 PubMed
50.
Zurück zum Zitat Orlhac F, Lecler A, Savatovski J et al (2021) How can we combat multicenter variability in MR radiomics? Validation of a correction procedure. Eur Radiol 31:2272–2280 PubMed Orlhac F, Lecler A, Savatovski J et al (2021) How can we combat multicenter variability in MR radiomics? Validation of a correction procedure. Eur Radiol 31:2272–2280 PubMed
51.
Zurück zum Zitat Sun X, Shi L, Luo Y et al (2015) Histogram-based normalisation technique on human brain magnetic resonance images from different acquisitions. Biomed Eng Online 14:73 PubMedPubMedCentral Sun X, Shi L, Luo Y et al (2015) Histogram-based normalisation technique on human brain magnetic resonance images from different acquisitions. Biomed Eng Online 14:73 PubMedPubMedCentral
52.
Zurück zum Zitat Carré A, Klausner G, Edjlali M et al (2020) Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics. Sci Rep 10:12340 PubMedPubMedCentral Carré A, Klausner G, Edjlali M et al (2020) Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics. Sci Rep 10:12340 PubMedPubMedCentral
53.
Zurück zum Zitat Chansik A, Park YW, Ahn SS, Han K, Kim H, Lee SK (2021) "Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results." PloS One 16(8):e0256152 Chansik A, Park YW, Ahn SS, Han K, Kim H, Lee SK (2021) "Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results." PloS One 16(8):e0256152
54.
Zurück zum Zitat Park CJ, Park YW, Ahn SS et al (2022) "Quality of radiomics research on brain metastasis: a roadmap to promote clinical translation." Korean J Radiol 23(1):77 Park CJ, Park YW, Ahn SS et al (2022) "Quality of radiomics research on brain metastasis: a roadmap to promote clinical translation." Korean J Radiol 23(1):77
55.
Zurück zum Zitat Brat DJ, Aldape K, Colman H et al (2018) cIMPACT-NOW update 3: recommended diagnostic criteria for “Diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV”. Acta Neuropathol 136:805–810 PubMedPubMedCentral Brat DJ, Aldape K, Colman H et al (2018) cIMPACT-NOW update 3: recommended diagnostic criteria for “Diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV”. Acta Neuropathol 136:805–810 PubMedPubMedCentral
56.
Zurück zum Zitat Stichel D, Ebrahimi A, Reuss D et al (2018) Distribution of EGFR amplification, combined chromosome 7 gain and chromosome 10 loss, and TERT promoter mutation in brain tumors and their potential for the reclassification of IDHwt astrocytoma to glioblastoma. Acta Neuropathol 136:793–803 PubMed Stichel D, Ebrahimi A, Reuss D et al (2018) Distribution of EGFR amplification, combined chromosome 7 gain and chromosome 10 loss, and TERT promoter mutation in brain tumors and their potential for the reclassification of IDHwt astrocytoma to glioblastoma. Acta Neuropathol 136:793–803 PubMed
Metadaten
Titel
Adding radiomics to the 2021 WHO updates may improve prognostic prediction for current IDH-wildtype histological lower-grade gliomas with known EGFR amplification and TERT promoter mutation status
verfasst von
Yae Won Park
Sooyon Kim
Chae Jung Park
Sung Soo Ahn
Kyunghwa Han
Seok-Gu Kang
Jong Hee Chang
Se Hoon Kim
Seung-Koo Lee
Publikationsdatum
28.06.2022
Verlag
Springer Berlin Heidelberg
Erschienen in
European Radiology / Ausgabe 12/2022
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08941-x

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