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1.
J Biomed Sci ; 28(1): 54, 2021 Jul 19.
Artículo en Inglés | MEDLINE | ID: mdl-34281540

RESUMEN

BACKGROUND: Current multiparametric MRI (mp-MRI) in routine clinical practice has poor-to-moderate diagnostic performance for transition zone prostate cancer. The aim of this study was to evaluate the potential diagnostic performance of novel 1H magnetic resonance spectroscopic imaging (MRSI) using a semi-localized adiabatic selective refocusing (sLASER) sequence with gradient offset independent adiabaticity (GOIA) pulses in addition to the routine mp-MRI, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and quantitative dynamic contrast enhancement (DCE) for transition zone prostate cancer detection, localization and grading. METHODS: Forty-one transition zone prostate cancer patients underwent mp-MRI with an external phased-array coil. Normal and cancer regions were delineated by two radiologists and divided into low-risk, intermediate-risk, and high-risk categories based on TRUS guided biopsy results. Support vector machine models were built using different clinically applicable combinations of T2WI, DWI, DCE, and MRSI. The diagnostic performance of each model in cancer detection was evaluated using the area under curve (AUC) of the receiver operating characteristic diagram. Then accuracy, sensitivity and specificity of each model were calculated. Furthermore, the correlation of mp-MRI parameters with low-risk, intermediate-risk and high-risk cancers were calculated using the Spearman correlation coefficient. RESULTS: The addition of MRSI to T2WI + DWI and T2WI + DWI + DCE improved the accuracy, sensitivity and specificity for cancer detection. The best performance was achieved with T2WI + DWI + MRSI where the addition of MRSI improved the AUC, accuracy, sensitivity and specificity from 0.86 to 0.99, 0.83 to 0.96, 0.80 to 0.95, and 0.85 to 0.97 respectively. The (choline + spermine + creatine)/citrate ratio of MRSI showed the highest correlation with cancer risk groups (r = 0.64, p < 0.01). CONCLUSION: The inclusion of GOIA-sLASER MRSI into conventional mp-MRI significantly improves the diagnostic accuracy of the detection and aggressiveness assessment of transition zone prostate cancer.


Asunto(s)
Espectroscopía de Resonancia Magnética/uso terapéutico , Imágenes de Resonancia Magnética Multiparamétrica/estadística & datos numéricos , Neoplasias de la Próstata/diagnóstico , Anciano , Anciano de 80 o más Años , Humanos , Masculino , Persona de Mediana Edad , Neoplasias de la Próstata/diagnóstico por imagen
2.
J Magn Reson Imaging ; 50(6): 1926-1936, 2019 12.
Artículo en Inglés | MEDLINE | ID: mdl-31132193

RESUMEN

BACKGROUND: Due to the histological heterogeneity of the central gland, accurate detection of central gland prostate cancer remains a challenge. PURPOSE: To evaluate the efficacy of in vivo 3D 1 H MR spectroscopic imaging (3D 1 H MRSI) with a semi-localized adiabatic selective refocusing (sLASER) sequence and gradient-modulated offset-independent adiabatic (GOIA) pulses for detection of central gland prostate cancer. Additionally four risk models were developed to differentiate 1) normal vs. cancer, 2) low- vs. high-risk cancer, 3) low- vs. intermediate-risk cancer, and 4) intermediate- vs. high-risk cancer voxels. STUDY TYPE: Prospective. SUBJECTS: Thirty-six patients with biopsy-proven central gland prostate cancer. FIELD STRENGTH/SEQUENCE: 3T MRI / 3D 1 H MRSI using GOIA-sLASER. ASSESSMENT: Cancer and normal regions of interest (ROIs) were selected by an experienced radiologist and 1 H MRSI voxels were placed within the ROIs to calculate seven metabolite signal ratios. Voxels were split into two subsets, 80% for model training and 20% for testing. STATISTICAL TESTS: Four support vector machine (SVM) models were built using the training dataset. The accuracy, sensitivity, and specificity for each model were calculated for the testing dataset. RESULTS: High-quality MR spectra were obtained for the whole central gland of the prostate. The normal vs. cancer diagnostic model achieved the highest predictive performance with an accuracy, sensitivity, and specificity of 96.2%, 95.8%, and 93.1%, respectively. The accuracy, sensitivity, and specificity of the low- vs. high-risk cancer and low- vs. intermediate-risk cancer models were 82.5%, 89.2%, 70.2%, and 73.0%, 84.7%, 60.8%, respectively. The intermediate- vs. high-risk cancer model yielded an accuracy, sensitivity, and specificity lower than 55%. DATA CONCLUSION: The GOIA-sLASER sequence with an external phased-array coil allows for fast assessment of central gland prostate cancer. The classification offers a promising diagnostic tool for discriminating normal vs. cancer, low- vs. high-risk cancer, and low- vs. intermediate-risk cancer. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1926-1936.


Asunto(s)
Interpretación de Imagen Asistida por Computador/métodos , Espectroscopía de Resonancia Magnética/métodos , Próstata/patología , Neoplasias de la Próstata/diagnóstico por imagen , Procesamiento de Señales Asistido por Computador , Anciano , Diagnóstico Diferencial , Humanos , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Reproducibilidad de los Resultados , Medición de Riesgo , Sensibilidad y Especificidad
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