Rationale: Fibroblast activation protein (FAP) targeted molecular imaging radiotracers have shown promising preclinical and clinical results in tumor diagnosis. However, rapid clearance and inadequate tumor retention of these molecules have hindered them for further clinical translation in cancer therapy. In this study, we aimed to develop a series of albumin binder-truncated Evans blue (EB) modified FAP targeted radiotracers, and optimize the pharmacokinetic (PK) characteristics to overcome the existing limitations in order to apply in the radionuclide therapy of cancer.

In a prospective study of newly diagnosed or relapsed histologically proven extranodal natural killer/T-cell lymphoma (ENKTL) patients, we aimed to determine the accuracy of midtreatment ¹⁸F-FDG PET for response assessment using both visual and quantitative analyses. Methods: Twenty-four patients (12 men, 12 women; median age, 50 y; age range, 16–83 y) were referred for pre-, mid- (after 2–3 cycles of SMILE [prednisolone, methotrexate, ifosfamide, L-asparaginase, etoposide] chemotherapy), and end-treatment PET/CT scans (n = 24, 24, and 17, respectively) using a standardized protocol. Sixty-five PET/CT scans were analyzed visually using the Deauville 5-point score (DS), and the lesion with the highest maximum standardized uptake value (SUV_max) was recorded. Survival curves were obtained using Kaplan–Meier analysis and compared using the log rank test, followed by multivariate analysis using the Cox proportional hazards model to assess the independent effects of International Prognostic Index (IPI) score (0–1 vs. 2–5), stage (stage I/II vs. stage III/IV), sex, DS (1–3 vs. 4–5), SUV_max, and change in SUV_max on overall survival (OS) and progression-free survival (PFS). The mean (±SD) follow-up period was 32 mo (±21 mo). Results: For 2-y OS, the following parameters were predictive: IPI score (P = 0.047), DS at mid- and end-treatment (P < 0.001), and SUV_max at mid- and end-treatment (P < 0.001 and 0.045, respectively). For 2-y PFS, the following parameters were predictive: sex (P = 0.006), stage (P = 0.034), IPI score (P = 0.038), DS at mid- and end-treatment (P < 0.001 and 0.001, respectively), and SUV_max at midtreatment (P = 0.001). Multivariate analysis showed DS on mid- and end-treatment scans to be the only significant independent predictor of both OS (P = 0.004 and 0.018, respectively) and PFS (P = 0.004 and 0.014, respectively). The 2-y estimate for OS and PFS was 81% and 62%, respectively, in patients with a DS of 1–3, compared with 17% in patients with a DS of 4–5 (P < 0.001 and 0.001, respectively). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the midtreatment DS for prediction of OS and PFS were 63%, 94%, 83%, 83%, and 83%, respectively. Conclusion: Midtreatment PET/CT is a valuable tool for early treatment response assessment in extranodal natural killer/T-cell lymphoma patients.

To examine the prognostic value of a machine learning model trained with pretreatment MRI radiomic features in the assessment of patients with nonmetastatic nasopharyngeal carcinoma (NPC) who are at risk for 3-year disease progression after intensity-modulated radiation therapy and to explain the radiomics features in the model. A total of 277 patients with nonmetastatic NPC admitted between March 2008 and December 2014 at two imaging centers were retrospectively reviewed. Patients were allocated to a discovery or validation cohort based on where they underwent MRI (discovery cohort, n = 217; validation cohort, n = 60). A total of 525 radiomics features extracted from contrast material–enhanced T1- or T2-weighted MRI studies and five clinical features were subjected to radiomic machine learning modeling to predict 3-year disease progression. Feature selection was performed by analyzing robustness to resampling, reproducibility between observers, and redundancy. Features for the final model were selected with Kaplan-Meier analysis and the log-rank test. A support vector machine was used as the classifier for the model. To interpret the pattern learned from the model, Shapley additive explanations (SHAP) was applied. The final model yielded an area under the receiver operating characteristic curve of 0.80 in both the discovery (95% bootstrap confidence interval: 0.80, 0.81) and independent validation (95% bootstrap confidence interval: 0.73, 0.89) cohorts. Analysis with SHAP revealed that tumor shape sphericity, first-order mean absolute deviation, T stage, and overall stage were important factors in 3-year disease progression. These results add to the growing evidence of the role of radiomics in the assessment of NPC. By using explanatory techniques, such as SHAP, the complex interaction of features learned by the model may be understood. © RSNA, 2019 Supplemental material is available for this article.

Background: Epstein-Barr virus (EBV)-associated nasopharyngeal carcinoma (NPC) in endemic regions may have undetectable plasma EBV DNA. Methods: We prospectively recruited 518 patients with non-metastatic NPC and measured their pre-treatment plasma EBV DNA. The stage distribution and prognosis between pre-treatment plasma EBV DNA-negative (0–20 copies/ml) and EBV DNA-positive (>20 copies/ml) patients following radical treatment were compared. Results: Seventy-eight patients (15.1%) were plasma EBV DNA-negative, and 62 in this subset (12.0%) had 0 copy/ml. Only 23/78 (29.5%) plasma EBV DNA-negative patients with advanced NPC (stage III-IVA) had strong EBV encoded RNA (EBER) positivity (score 3) in their tumours compared to 342/440 (77.7%) EBV DNA-positive patients of the same stages (p < 0.001). Though EBV DNA-negative patients had more early-stage disease (p < 0.001) and smaller volumes of the primary tumour and the positive neck nodes (p < 0.001), they had similar 5-year overall survival and cancer-specific survival to those EBV DNA-positive counterparts by stage. Similar results were also seen when plasma EBV DNA cut-off was set at 0 copy/ml. Conclusions: Patients with low-volume NPC may not be identified by plasma/serum tumour markers and caution should be taken in its utility as a screening tool for NPC even in endemic regions. Clinical trial registration: Clinicaltrials.gov Identifier: NCT02476669.

We aim to evaluate the quantitative parameters of ¹⁸F-FDG PET/CT (metabolic parameters) and MRI (morphologic parameters) for prognostication and risk stratification in nasopharyngeal carcinoma (NPC). 200 (147 males, aged 50 ± 13 years-old, mean ± S.D.) newly diagnosed patients with NPC (T_xN_xM₀) were prospectively recruited. Primary tumor and nodal lesions were identified and segmented for both morphologic (volume, VOL) and metabolic (SUV and MTV) quantification. Independent predictive factors for recurrence free survival (RFS) and overall survival (OS) were morphologic nodal volume (VOL_N, p < 0.001), TNM-stage (p = 0.022), N-Stage (p = 0.024) for RFS, and VOL_N (p = 0.014) for OS. Using Classification and Regression Tree (CART) analysis, three risk-layers were identified for RFS: Stage I/II with VOL_N < 18cc (HR = 1), stage III /IV with VOL_N < 18cc (HR = 2.93), VOL_N ≥ 18cc (HR = 7.84) regardless of disease stage (p < 0.001). For OS, two risk layers were identified: VOL_N < 18cc (HR = 1), VOL_N ≥ 18cc (HR = 4.23) (p = 0.001). The 18cc threshold for morphologic nodal volume was validated by an independent cohort (n = 105). Based on the above risk-classification, 35 patients (17.5%) would have a higher risk than suggested by the TNM-staging system. Thus, morphologic nodal volume is an important factor in prognostication and risk stratification in NPC, and should be incorporated into the staging system, while PET parameters have no advantage for this purpose in our cohort.