Compatibility between 3T super(1)H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T super(1)H SV-MRS spectra

Object: This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing large databases of 1.5T MRS data to be used for diagnostic classification of 3T spe...

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Veröffentlicht in:Magma (New York, N.Y.) N.Y.), 2011-02, Vol.24 (1), p.35-42
Hauptverfasser: Fuster-Garcia, Elies, Navarro, Clara, Vicente, Javier, Tortajada, Salvador, Garcia-Gomez, Juan M, Saez, Carlos, Calvar, Jorge, Griffiths, John, Julia-Sape, Margarida, Howe, Franklyn A, Pujol, Jesus, Peet, Andrew C, Heerschap, Arend, Moreno-Torres, Angel, Martinez-Bisbal, M C, Martinez-Granados, Beatriz, Wesseling, Pieter, Semmler, Wolfhard, Capellades, Jaume, Majos, Carles, Alberich-Bayarri, Angel, Capdevila, Antoni, Monleon, Daniel, Marti-Bonmati, Luis, Arus, Carles, Celda, Bernardo, Robles, Montserrat
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container_issue 1
container_start_page 35
container_title Magma (New York, N.Y.)
container_volume 24
creator Fuster-Garcia, Elies
Navarro, Clara
Vicente, Javier
Tortajada, Salvador
Garcia-Gomez, Juan M
Saez, Carlos
Calvar, Jorge
Griffiths, John
Julia-Sape, Margarida
Howe, Franklyn A
Pujol, Jesus
Peet, Andrew C
Heerschap, Arend
Moreno-Torres, Angel
Martinez-Bisbal, M C
Martinez-Granados, Beatriz
Wesseling, Pieter
Semmler, Wolfhard
Capellades, Jaume
Majos, Carles
Alberich-Bayarri, Angel
Capdevila, Antoni
Monleon, Daniel
Marti-Bonmati, Luis
Arus, Carles
Celda, Bernardo
Robles, Montserrat
description Object: This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing large databases of 1.5T MRS data to be used for diagnostic classification of 3T spectra, and perhaps also the combination of 1.5T and 3T databases. Materials and methods: Brain tumour classifiers trained with 154 1.5T spectra to discriminate among high grade malignant tumours and common grade II glial tumours were evaluated with a subsequently-acquired set of 1551.5T and 373T spectra. A similarity study between spectra and main brain tumour metabolite ratios for both field strengths (1.5T and 3T) was also performed. Results: Our results showed that classifiers trained with 1.5T samples had similar accuracy for both test datasets (0.87 plus or minus 0.03 for 1.5T and 0.88 plus or minus 0.03 for 3.0T). Moreover, non-significant differences were observed with most metabolite ratios and spectral patterns. Conclusion: These results encourage the use of existing classifiers based on 1.5T datasets for diagnosis with 3T super(1)H SV-MRS. The large 1.5T databases compiled throughout many years and the prediction models based on 1.5T acquisitions can therefore continue to be used with data from the new 3T instruments.
doi_str_mv 10.1007/s10334-010-0241-8
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This will allow the existing large databases of 1.5T MRS data to be used for diagnostic classification of 3T spectra, and perhaps also the combination of 1.5T and 3T databases. Materials and methods: Brain tumour classifiers trained with 154 1.5T spectra to discriminate among high grade malignant tumours and common grade II glial tumours were evaluated with a subsequently-acquired set of 1551.5T and 373T spectra. A similarity study between spectra and main brain tumour metabolite ratios for both field strengths (1.5T and 3T) was also performed. Results: Our results showed that classifiers trained with 1.5T samples had similar accuracy for both test datasets (0.87 plus or minus 0.03 for 1.5T and 0.88 plus or minus 0.03 for 3.0T). Moreover, non-significant differences were observed with most metabolite ratios and spectral patterns. Conclusion: These results encourage the use of existing classifiers based on 1.5T datasets for diagnosis with 3T super(1)H SV-MRS. The large 1.5T databases compiled throughout many years and the prediction models based on 1.5T acquisitions can therefore continue to be used with data from the new 3T instruments.</abstract><doi>10.1007/s10334-010-0241-8</doi><tpages>8</tpages></addata></record>
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subjects Brain
Classifiers
Diagnosis
Diagnostic systems
Quality
Spectra
Tumours
title Compatibility between 3T super(1)H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T super(1)H SV-MRS spectra
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