MRI For Prediction Of Response Research Articles

Radiomic analysis of MRI for prediction of response to induction chemotherapy in nasopharyngeal carcinoma patients

To establish and validate radiomic models for response prediction to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC) using the radiomic features from pretreatment MRI. This retrospective analysis included 184 consecutive NPC patients, 132 in the primary cohort and 52 in the validation cohort. Radiomic features were derived from contrast-enhanced T1-weighted imaging (CE-T1) and T2-weighted imaging (T2-WI) for each subject. The radiomic features were then selected and combined with clinical characteristics to build radiomic models. The potential of the radiomic models was evaluated based on its discrimination and calibration. To measure the performance of these radiomic models in predicting the treatment response to IC in NPC, the area under the receiver operating characteristic curve (AUC), and sensitivity, specificity, and accuracy were used. Four radiomic models were constructed in the present study including the radiomic signature of CE-T1, T2-WI, CE-T1 + T2-WI, and the radiomic nomogram of CE-T1. The radiomic signature of CE-T1 + T2-WI performed well in distinguishing response and non-response to IC in patients with NPC, which yielded an AUC of 0.940 (95% CI, 0.885-0.974), sensitivity of 83.1%, specificity of 91.8%, and accuracy of 87.1% in the primary cohort, and AUC of 0.952 (95% CI, 0.855-0.992), sensitivity of 74.2%, specificity of 95.2%, and accuracy of 82.7% in the validation cohort. MRI-based radiomic models could be helpful for personalised risk stratification and treatment in NPC patients receiving IC.

Accuracy of MRI for prediction of response to neo-adjuvant chemotherapy in triple negative breast cancer compared to other molecular types

Accuracy of MRI for prediction of response to neo-adjuvant chemotherapy in triple negative breast cancer compared to other molecular types

Accuracy of MRI for Prediction of Response to Neo-Adjuvant Chemotherapy in Triple Negative Breast Cancer Compared to Other Molecular Types

Abstract Purpose: The aim of this study was to compare the accuracy of MRI for prediction of response to Neo-adjuvant chemotherapy in Triple negative (TN) breast cancer, with respect to other molecular types. Materials and methods: There were a total of 1610 breast cancers diagnosed between March 2009 and August 2014, out of which 82 patients underwent MRI before and after neo-adjuvant chemotherapy but just before surgery. Triple negative cancers were analysed with respect to others subtypes. Accuracy of MRI for prediction of pathological complete response was compared between different subtypes, by obtaining ROC curves. SPSS (version 21) was used for all data analysis with p value of 0.05 as statistically significant. Results: Out of 82 patients, 29 were Luminal (HR+/HER2 -), 23 were triple negative (HR-, HER2-), 11 HER2 positive (HR-, HER2+) and 19 were of hybrid subtype (HR+/HER2+). Triple negative cancers presented as masses on the pre-chemotherapy MRI scan, were grade 3 on histopathology and show concentric shrinkage following chemotherapy. Triple negative cancers were more likely to have both imaging and pathological complete response following chemotherapy (p=0.055) in contrast to Luminal cancers, which show residual cancer. ROC curves were constructed for prediction of PCR by post chemotherapy MR. For the triple negative sub-group, MR had sensitivity of 0.745 and specificity of 0.700 (p=0.035), with an area under curve (AUC) of 0.745(95% CI 0.526-0.965), which was significantly better compared to other subtypes. Conclusion: Triple negative breast cancers present as masses and show concentric shrinkage following chemotherapy. MRI is most sensitive and specific in predicting response to chemotherapy in the TN group, compared to others subtypes. MRI underestimates residual disease in Luminal cancers.

Diffusion MRI for prediction of response of rectal cancer to chemoradiation.

Prediction of tumour response before onset of treatment could have considerable clinical benefit. Since the apparent diffusion coefficient (ADC) of a tumour's water content can show the extent of necrosis, we looked for a possible correlation of ADC with response to treatment. We measured mean tumour water ADC before and after chemotherapy and chemoradiation in 14 patients with locally advanced rectal cancer, with a quantitative magnetic resonance diffusion imaging sequence. We found a strong negative correlation between mean pretreatment tumour water ADC and percentage size change of tumours after chemotherapy (r=-0.67, p=0.01) and chemoradiation (r=-0.83, p=0.001). Persistence of low ADC in responders after chemotherapy could represent loss of a non-viable fraction of the treated tumour.