Extracellular volume fraction determined by equilibrium contrast-enhanced CT for the prediction of the pathological complete response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer.

OBJECTIVES: To determine the extracellular volume (ECV) fraction derived from equilibrium contrast-enhanced CT for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer (LARC). METHODS: The ECV fraction before NCRT (ECVpre) and/or ECV after NCRT (ECVpost) of rectal tumors was assessed, and ECVΔ was calculated as ECVpost - ECVpre. The histopathologic tumor regression grading (TRG) was assessed. pCR (TRG 0 grade) was defined as the absence of viable tumor cells in the primary tumor and lymph nodes. Demographic and clinicopathological characteristics and ECV fraction were compared between the pCR and non-pCR groups. A mixed model was constructed by logistic regression. The performance for predicting pCR was assessed with the area under the receiver-operator curve (AUC). The AUCs of the different methods were compared by the method proposed by DeLong et al. RESULTS: Seventy-five patients were included; 17 achieved pCR, and 58 achieved non-pCR. The ECVpost (17.05 ± 2.36% vs. 29.94 ± 1.20%; p < 0.001) and ECVΔ (- 17.01 ± 3.01% vs. 0.44 ± 1.45%; p < 0.001) values in the pCR group were significantly lower than those in the non-pCR group. The mixed model that combined ECVpost with ECVΔ achieved an AUC of 0.92 (95% confidence interval (CI) = 0.81-0.98), which was higher than that of ECVpost (AUC, 0.91 (95% CI = 0.80-0.97); p = 0.60) or ECVΔ (AUC, 0.90 (95% CI = 0.79-0.97); p = 0.61). CONCLUSIONS: ECVpost and ECVΔ determined by using equilibrium contrast-enhanced CT were useful in distinguishing between pCR and non-pCR patients with LARC who received NCRT. KEY POINTS: • ECVpost and ECVΔ (ECVpost - ECVpre) differed significantly between the non-pCR and pCR groups. • ECVpre cannot be used to predict the efficacy of neoadjuvant chemoradiotherapy. • ECVpost combined with ECVΔ had the best performance with an AUC of 0.92 for predicting pCR after NCRT in LARC.

Low-dose CT with tin filter combined with iterative metal artefact reduction for guiding lung biopsy.

BACKGROUND: Computed tomography (CT) is currently the imaging modality of choice for guiding pulmonary percutaneous procedures. The use of a tin filter allows low-energy photons to be absorbed which contribute little to image quality but increases the radiation dose that a patient receives. Iterative metal artefact reduction (iMAR) was developed to diminish metal artefacts. This study investigated the impact of using tin filtration combined with an iMAR algorithm on dose reduction and image quality in CT-guided lung biopsy. METHODS: Ninety-nine consecutive patients undergoing CT-guided lung biopsy were randomly assigned to routine-dose CT protocols (groups A and B; without and with iMAR, respectively) or tin filter CT protocols (groups C and D; without or with iMAR, respectively). Subjective image quality was analysed using a 5-point Likert scale. Objective image quality was assessed, and the noise, contrast-to-noise ratio, and figure of merit were compared among the four groups. Metal artefacts were quantified using CT number reduction and metal diameter blurring. The radiation doses, diagnostic performance, and complication rates were also estimated. RESULTS: The subjective image quality of the two scan types was compared. Images with iMAR reconstruction were superior to those without iMAR reconstruction (group A: 3.49±0.65 vs. group B: 4.63±0.57; P<0.001, and group C: 3.88±0.66 vs. group D: 4.82±0.39; P<0.001). Images taken with a tin filter were found to have a significantly higher figure-of-merit than those taken without a tin filter (group A: 14,041±7,230 vs. group C: 21,866±10,656; P=0.001, and group B: 13,836±6,849 vs. group D: 21,639±9,964; P=0.001). In terms of metal artefact reduction, tin filtration combined with iMAR showed the lowest CT number reduction (116.62±103.48 HU) and metal diameter blurring (0.85±0.30) among the protocols. The effective radiation dose in the tin filter groups was 73.2% lower than that in the routine-dose groups. The complication rate and diagnostic performance (sensitivity, specificity, and overall accuracy) did not differ significantly between the tin filter and routine-dose groups (all P>0.05). CONCLUSIONS: Tin filtration combined with an iMAR algorithm may reduce the radiation dose compared to the routine-dose CT protocol, while maintaining comparable diagnostic accuracy and image quality and producing fewer metal artefacts.