Utilising functional imaging to predict survival in paediatric brain tumours. (12th October 2019)
- Record Type:
- Journal Article
- Title:
- Utilising functional imaging to predict survival in paediatric brain tumours. (12th October 2019)
- Main Title:
- Utilising functional imaging to predict survival in paediatric brain tumours.
- Authors:
- Grist, James
Withey, Stephanie
MacPherson, Lesley
Oates, Adam
Stephen Powell, Mr
Novak, Jan
Abernethy, Laurence
Pizer, Barry
Grundy, Richard
Bailey, Simon
Mitra, Dipayan
Arvantis, Theodoros
Auer, Dorothee
Avula, Shivaram
Peet, Andrew - Abstract:
- Abstract: Introduction: Brain tumours are a common cause of death in the paediatric population. We have previously shown that MR imaging and spectroscopy can be used to non-invasively differentiate between tumour types. Here, we demonstrate that functional imaging can be highly predictive of survival and grade in a paediatric cohort. Methods: Perfusion (PWI) and diffusion weighted imaging (DWI) were performed in a multi-site (Birmingham Children's Hospital, Royal Victoria Infirmary, Alder Hey, Nottingham) cohort ([grade, 5-year survival alive:dead number] = [I, 15:1], [II, 5:1], [III, 2:3], [IV, 8:11]). ROIs were drawn on T2 imaging and functional imaging features (mean, standard deviation, skewness, and kurtosis) were derived. Supervised machine learning was used to predict 5-year survival and tumour grade from features. ANOVA and post-hoc tests were used to assess differences in features between grade and 5-year survival status. Results: 5-year survival was predicted with 89%, 85%, and 87% accuracy with all imaging, perfusion, or diffusion features, respectively. A significant difference in perfusion was found between surviving and diseased participants (1.71 ± 0.82 vs 2.62 ± 1 mL/100g/min, respectively, p < 0.05). A significant difference in ADC (mm 2 s -1 ) between tumour grades was found (1 vs 4 (1533 ± 458 vs 857 ± 239), 4 vs 3 (857 ± 239 vs 1197 ± 137), 4 vs 2 (857 ± 239 vs 1440 ± 557), corrected p < 0.05). Conclusion: We have shown that perfusion and diffusionAbstract: Introduction: Brain tumours are a common cause of death in the paediatric population. We have previously shown that MR imaging and spectroscopy can be used to non-invasively differentiate between tumour types. Here, we demonstrate that functional imaging can be highly predictive of survival and grade in a paediatric cohort. Methods: Perfusion (PWI) and diffusion weighted imaging (DWI) were performed in a multi-site (Birmingham Children's Hospital, Royal Victoria Infirmary, Alder Hey, Nottingham) cohort ([grade, 5-year survival alive:dead number] = [I, 15:1], [II, 5:1], [III, 2:3], [IV, 8:11]). ROIs were drawn on T2 imaging and functional imaging features (mean, standard deviation, skewness, and kurtosis) were derived. Supervised machine learning was used to predict 5-year survival and tumour grade from features. ANOVA and post-hoc tests were used to assess differences in features between grade and 5-year survival status. Results: 5-year survival was predicted with 89%, 85%, and 87% accuracy with all imaging, perfusion, or diffusion features, respectively. A significant difference in perfusion was found between surviving and diseased participants (1.71 ± 0.82 vs 2.62 ± 1 mL/100g/min, respectively, p < 0.05). A significant difference in ADC (mm 2 s -1 ) between tumour grades was found (1 vs 4 (1533 ± 458 vs 857 ± 239), 4 vs 3 (857 ± 239 vs 1197 ± 137), 4 vs 2 (857 ± 239 vs 1440 ± 557), corrected p < 0.05). Conclusion: We have shown that perfusion and diffusion imaging features can be used to non-invasively assess tumour grade and estimate 5-year survival status in a cohort of paediatric brain tumours. … (more)
- Is Part Of:
- Neuro-oncology. Volume 21(2019)Supplement 4
- Journal:
- Neuro-oncology
- Issue:
- Volume 21(2019)Supplement 4
- Issue Display:
- Volume 21, Issue 4 (2019)
- Year:
- 2019
- Volume:
- 21
- Issue:
- 4
- Issue Sort Value:
- 2019-0021-0004-0000
- Page Start:
- iv5
- Page End:
- iv5
- Publication Date:
- 2019-10-12
- Subjects:
- Brain Neoplasms -- Periodicals
Brain -- Tumors -- Periodicals
Brain -- Cancer -- Periodicals
Nervous system -- Cancer -- Periodicals
616.99481 - Journal URLs:
- http://neuro-oncology.dukejournals.org/ ↗
http://neuro-oncology.oxfordjournals.org/ ↗
http://www.oxfordjournals.org/content?genre=journal&issn=1522-8517 ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/neuonc/noz167.018 ↗
- Languages:
- English
- ISSNs:
- 1522-8517
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6081.288000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 15027.xml