MRI Evaluation of Complete and Near-Complete Response after Neoadjuvant Therapy in Patients with Locally Advanced Rectal Cancer.
Anca-Raluca PopitaCosmin LisencuAdriana RusuCristian PopitaCalin Ioan CăinapAlexandru IrimieLiliana ResigaAlina MunteanuZsolt FeketeRadu BadeaPublished in: Diagnostics (Basel, Switzerland) (2022)
Purpose To evaluate MRI performance in restaging locally advanced rectal cancers (LARC) after neoadjuvant chemoradiotherapy (nCRT) and interobserver agreement in identifying complete response (CR) and near-complete response (nCR). Methods 40 patients with CR and nCR on restaging MRI, surgery and/or endoscopy were enrolled. Two radiologists independently scored the restaging MRI and reported the presence of split scar sign (SSS) and MRI tumor regression grade (mrTRG). Diagnostic accuracy and ROC curves were calculated for single and combined sequences, with inter-reader agreement. Results Diagnostic performance was good for detecting CR and weaker for nCR. T2WI had the highest AUCs among individual sequences. There was a significant positive correlation between SSS and CR, with high Sp (89.5%/73.7%) and PPV (90%/79.2%) for both Readers. Similar accuracy rates were observed for the combination of sequences, with AUCs of 0.828-0.847 for CR and 0.690-0.762 for nCR. Interobserver agreement was strong for SSS, moderate for T2WI, weak for the combination of sequences. Conclusions Restaging MRI had good diagnostic performance in identifying CR and nCR. SSS had high Sp and PPV in diagnosing CR, with a strong level of interobserver agreement. T2WI with DWI was the optimal combination of sequences for selecting good responders.
Keyphrases
- rectal cancer
- locally advanced
- contrast enhanced
- magnetic resonance imaging
- diffusion weighted imaging
- neoadjuvant chemotherapy
- squamous cell carcinoma
- phase ii study
- radiation therapy
- diffusion weighted
- computed tomography
- minimally invasive
- artificial intelligence
- clinical trial
- high intensity
- machine learning
- young adults
- deep learning