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Published on: November 8, 2012
Discrimination of paediatric brain tumours using apparent diffusion coefficient histograms
Jonathan G Bull1, Dawn E Saunders, Christopher A Clark
1Imaging and Biophysics Unit, UCL Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Insights
Apparent diffusion coefficient (ADC) histograms effectively differentiate paediatric brain tumours, particularly those in the posterior fossa. This method accurately classified most tumour types, aiding in clinical management decisions.
Area of Science:
- Neuro-oncology
- Radiology
- Medical Imaging
Background:
- Paediatric brain tumours represent a diverse group of neoplasms.
- Accurate pre-operative differentiation is crucial for effective treatment planning and patient management.
- Apparent diffusion coefficient (ADC) mapping is a non-invasive MRI technique that provides information about tissue microstructure.
Purpose of the Study:
- To evaluate the utility of apparent diffusion coefficient (ADC) histograms in distinguishing between various types of paediatric brain tumours.
- To assess the accuracy of ADC histogram metrics in classifying common paediatric posterior fossa tumours.
Main Methods:
- Retrospective review of pre-operative MRI scans with ADC maps from 54 paediatric patients with histologically confirmed brain tumours.
- Calculation of whole-tumour ADC histograms, normalized for volume.
- Application of stepwise logistic regression analysis using histogram parameters for tumour classification.
Main Results:
- ADC histogram analysis correctly classified 74% of all paediatric brain tumours studied.
- High classification accuracy was achieved for posterior fossa tumours: 80% for ependymomas, 100% for juvenile pilocytic astrocytomas, and 94% for primitive neuroectodermal tumours (PNET)-medulloblastoma.
- Primitive neuroectodermal tumours (PNETs) were distinguished from supratentorial atypical teratoid rhabdoid tumours (ATRTs) with 100% accuracy.
Conclusions:
- Apparent diffusion coefficient (ADC) histograms are a valuable tool for differentiating paediatric brain tumours.
- The technique shows particular promise for classifying common posterior fossa tumours in children.
- Accurate differentiation of PNETs from supratentorial ATRTs has significant implications for clinical management strategies.
Objective:
To determine if histograms of apparent diffusion coefficients (ADC) can be used to differentiate paediatric brain tumours.
Methods:
Imaging of histologically confirmed tumours with pre-operative ADC maps were reviewed (54 cases, 32 male, mean age 6.1 years; range 0.1-15.8 years) comprising 6 groups. Whole tumour ADC histograms were calculated; normalised for volume. Stepwise logistic regression analysis was used to differentiate tumour types using histogram metrics, initially for all groups and then for specific subsets.
Results:
All 6 groups (5 dysembryoplastic neuroectodermal tumours, 22 primitive neuroectodermal tumours (PNET), 5 ependymomas, 7 choroid plexus papillomas, 4 atypical teratoid rhabdoid tumours (ATRT) and 9 juvenile pilocytic astrocytomas (JPA)) were compared. 74% (40/54) were correctly classified using logistic regression of ADC histogram parameters. In the analysis of posterior fossa tumours, 80% of ependymomas, 100% of astrocytomas and 94% of PNET-medulloblastoma were classified correctly. All PNETs were discriminated from ATRTs (22 PNET and 4 supratentorial ATRTs) (100%).
Conclusions:
ADC histograms are useful in differentiating paediatric brain tumours, in particular, the common posterior fossa tumours of childhood. PNETs were differentiated from supratentorial ATRTs, in all cases, which has important implications in terms of clinical management. Key Points • MR based apparent diffusion coefficient histograms can help differentiate paediatric brain tumours • ADC histogram parameters correctly classified the great majority of posterior fossa tumours.
