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Introduction Tumor growth rate (TGR; percent size change per month [%/m]) is postulated to be an early radiological biomarker to overcome limitations of RECIST. This study aimed to assess the impact of TGR in neuroendocrine tumors (NETs) and potential clinical and therapeutic applications. Materials and Methods Patients (pts) with advanced grade (G) 1/2 NETs from the pancreas or small bowel initiating systemic treatment (ST) or watch and wait (WW) were eligible. Baseline and follow‐up scans were retrospectively reviewed to calculate TGR at pretreatment (TGR0), first follow‐up (TGRfirst), and 3(±1) months of study entry (TGR3m). Results Out of 905 pts screened, 222 were eligible. Best TGRfirst (222 pts) cutoff was 0.8 (area under the curve, 0.74). When applied to TGR3m (103 pts), pts with TGR3m <0.8 (66.9%) versus TGR3m ≥ 0.8 (33.1%) had longer median progression‐free survival (PFS; 26.3 m; 95% confidence interval [CI] 19.5–32.4 vs. 9.3 m; 95% CI, 6.1–22.9) and lower progression rate at 12 months (7.3% vs. 56.8%; p = .001). WW (vs. ST) and TGR3m ≥ 0.8 (hazard ratio [HR], 3.75; 95% CI, 2.21–6.34; p < .001) were retained as factors associated with a shorter PFS in multivariable Cox regression. TGR3m (HR, 3.62; 95% CI, 1.97–6.64; p < .001) was also an independent factor related to shorter PFS when analysis was limited to pts with stable disease (81 pts). Out of the 60 pts with TGR0 data available, 60% of pts had TGR0 < 4%/month. TGR0 ≥ 4 %/month (HR, 2.22; 95% CI, 1.15–4.31; p = .018) was also an independent factor related to shorter PFS. Conclusion TGR is an early radiological biomarker able to predict PFS and to identify patients with advanced NETs who may require closer radiological follow‐up. Implications for Practice Tumor growth rate at 3 months (TGR3m) is an early radiological biomarker able to predict progression‐free survival and to identify patients with advanced neuroendocrine tumors who may require closer radiological follow‐up. It is feasible to calculate TGR3m in clinical practice and it could be a useful tool for guiding patient management. This biomarker could also be implemented in future clinical trials to assess response to therapy.

Objectives The primary objective was to compare the performance of 3 different abbreviated MRI (AMRI) sets extracted from a complete gadoxetate-enhanced MRI obtained for hepatocellular carcinoma (HCC) screening. Secondary objective was to perform a preliminary cost-effectiveness analysis, comparing each AMRI set to published ultrasound performance for HCC screening in the USA. Methods This retrospective study included 237 consecutive patients (M/F, 146/91; mean age, 58 years) with chronic liver disease who underwent a complete gadoxetate-enhanced MRI for HCC screening in 2017 in a single institution. Two radiologists independently reviewed 3 AMRI sets extracted from the complete exam: non-contrast (NC-AMRI: T2-weighted imaging (T2wi)+diffusion-weighted imaging (DWI)), dynamic-AMRI (Dyn-AMRI: T2wi+DWI+dynamic T1wi), and hepatobiliary phase AMRI (HBP-AMRI: T2wi+DWI+T1wi during the HBP). Each patient was classified as HCC-positive/HCC-negative based on the reference standard, which consisted in all available patient data. Diagnostic performance for HCC detection was compared between sets. Estimated set characteristics, including historical ultrasound data, were incorporated into a microsimulation model for cost-effectiveness analysis. ResultsThe reference standard identified 13/237 patients with HCC (prevalence, 5.5%; mean size, 33.7 ± 30 mm). Pooled sensitivities were 61.5% for NC-AMRI (95% confidence intervals, 34.4-83%), 84.6% for Dyn-AMRI (60.8-95.1%), and 80.8% for HBP-AMRI (53.6-93.9%), without difference between sets (p range, 0.06-0.16). Pooled specificities were 95.5% (92.4-97.4%), 99.8% (98.4-100%), and 94.9% (91.6-96.9%), respectively, with a significant difference between Dyn-AMRI and the other sets (p < 0.01). All AMRI methods were effective compared with ultrasound, with life-year gain of 3-12 months against incremental costs of US$ < 12,000.

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