B Gui1, M Miccò2, A L Valentini2,3, F Cambi2,3, T Pasciuto4,5, A Testa5,6, R Autorino7, G F Zannoni6,8, V Rufini9,10, M A Gambacorta3,7, A Giordano9,10, G Scambia5,6, R Manfredi2,3. 1. Radiologia Diagnostica e Interventistica Generale, Area Diagnostica per Immagini, Dipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli, 8, Rome, 00168, Italy. benedetta.gui@policlinicogemelli.it. 2. Radiologia Diagnostica e Interventistica Generale, Area Diagnostica per Immagini, Dipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli, 8, Rome, 00168, Italy. 3. Istituto di Radiologia, Università Cattolica del Sacro Cuore, Largo F. Vito, 1, Rome, 00168, Italy. 4. STAR Center (Statistics Technology Archiving Research Center), Dipartimento Scienze della Salute della Donna e del Bambino, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli, 8, Rome, 00168, Italy. 5. Istituto di Clinica Ostetrica e Ginecologica, Università Cattolica del Sacro Cuore, Largo F. Vito, 1, Rome, 00168, Italy. 6. Dipartimento Scienze della Salute della Donna e del Bambino, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli, 8, Rome, 00168, Italy. 7. Radioterapia Oncologica, Area Radioterapia Oncologica, Dipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli, 8, Rome, 00168, Italy. 8. Istituto di Anatomia Patologica, Università Cattolica del Sacro Cuore, Largo F. Vito, 1, Rome, 00168, Italy. 9. Medicina Nucleare, Area Diagnostica per Immagini, Dipartimento Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli, 8, Rome, 00168, Italy. 10. Istituto di Medicina Nucleare, Università Cattolica del Sacro Cuore, Largo F. Vito, 1, Rome, 00168, Italy.
Abstract
OBJECTIVES: To assess the diagnostic performance of conventional and DW-MRI parameters in the detection of residual tumor in locally advanced cervical cancer (LACC) patients treated with neoadjuvant chemoradiotherapy (nCRT) and radical surgery METHODS: Between October 2010 and June 2014, 88 patients with histologically documented cervical cancer (FIGO stage IB2-IVA) were prospectively included in the study. Maximum tumor diameters (maxTD), tumor volume (TV), DWI signal intensity (SI), and ADCmean were evaluated at MRI after nCRT. Histology was the reference standard. Treatment response was classified as complete (CR) or partial (PR). Comparisons were made with Mann-Whitney, χ2, and Fisher's exact tests. ROC curves were generated for variables to evaluate diagnostic ability to predict PR and to determine the best cutoff value to predict PR. For each diagnostic test, sensitivity, specificity, and accuracy were calculated. RESULTS: TV and maxTD were significantly smaller in the CR than in the PR group (p < 0.001; p = 0.001) and showed, respectively, sensitivity of 68.8%, specificity of 72.5%, and accuracy of 70.5% and of 47.9, 87.5, and 65.9% in predicting PR. High DWI SI was more frequent in the PR (81.8%) than in the CR group (55.3%) (p < 0.009). ADCmean was higher in the CR (1.3 × 10-3 mm2/s, range 0.8-1.6 × 10-3 mm2/s) than in the PR group (1.1 × 10-3 mm2/s; range 0.7-1.8 × 10-3 mm2/s) (p < 0.018). High DWI SI showed sensitivity, specificity, and accuracy of 81.8, 44.7, and 64.6% in predicting PR. The ADCmean measurement increased sensitivity, specificity, and accuracy to 75.0, 76.2, and 75.4%. CONCLUSIONS: Conventional and DW-MRI is useful for predicting PR after nCRT in LACC. The ADCmean value ≤ 1.1 × 10-3 mm2/s was the best cutoff to predict PR. KEY POINTS: • Conventional and DW-MRI is useful for predicting PR after nCRT in LACC. • The combination of T2 sequences, DW-MRI, and the quantitative measurement of ADC mean showed the best results in predicting pathological PR. • The best cutoff for predicting pathological PR was ADCmeanvalue ≤ 1.1 × 10-3 mm2/s.
OBJECTIVES: To assess the diagnostic performance of conventional and DW-MRI parameters in the detection of residual tumor in locally advanced cervical cancer (LACC) patients treated with neoadjuvant chemoradiotherapy (nCRT) and radical surgery METHODS: Between October 2010 and June 2014, 88 patients with histologically documented cervical cancer (FIGO stage IB2-IVA) were prospectively included in the study. Maximum tumor diameters (maxTD), tumor volume (TV), DWI signal intensity (SI), and ADCmean were evaluated at MRI after nCRT. Histology was the reference standard. Treatment response was classified as complete (CR) or partial (PR). Comparisons were made with Mann-Whitney, χ2, and Fisher's exact tests. ROC curves were generated for variables to evaluate diagnostic ability to predict PR and to determine the best cutoff value to predict PR. For each diagnostic test, sensitivity, specificity, and accuracy were calculated. RESULTS: TV and maxTD were significantly smaller in the CR than in the PR group (p < 0.001; p = 0.001) and showed, respectively, sensitivity of 68.8%, specificity of 72.5%, and accuracy of 70.5% and of 47.9, 87.5, and 65.9% in predicting PR. High DWI SI was more frequent in the PR (81.8%) than in the CR group (55.3%) (p < 0.009). ADCmean was higher in the CR (1.3 × 10-3 mm2/s, range 0.8-1.6 × 10-3 mm2/s) than in the PR group (1.1 × 10-3 mm2/s; range 0.7-1.8 × 10-3 mm2/s) (p < 0.018). High DWI SI showed sensitivity, specificity, and accuracy of 81.8, 44.7, and 64.6% in predicting PR. The ADCmean measurement increased sensitivity, specificity, and accuracy to 75.0, 76.2, and 75.4%. CONCLUSIONS: Conventional and DW-MRI is useful for predicting PR after nCRT in LACC. The ADCmean value ≤ 1.1 × 10-3 mm2/s was the best cutoff to predict PR. KEY POINTS: • Conventional and DW-MRI is useful for predicting PR after nCRT in LACC. • The combination of T2 sequences, DW-MRI, and the quantitative measurement of ADC mean showed the best results in predicting pathological PR. • The best cutoff for predicting pathological PR was ADCmeanvalue ≤ 1.1 × 10-3 mm2/s.
Entities:
Keywords:
Chemoradiotherapy; Diffusion magnetic resonance imaging; Magnetic resonance imaging; Tumor volume; Uterine cervical neoplasms