We investigated the possibility of counting tumor deposits (TDs) as positive lymph nodes (pLNs) in the pN category and evaluated its prognostic value for colorectal cancer (CRC) patients. A new pN category (npN category) was calculated using the numbers of pLNs plus TDs. The npN category included 4 tiers: npN1a (1 tumor node), npN1b (2-3 tumor nodes), npN2a (4-6 tumor nodes), and npN2b (≥7 tumor nodes). We identified 4,121 locally advanced CRC patients, including 717 (11.02%) cases with TDs. Univariate and multivariate analyses were performed to evaluate the disease-free and overall survival (DFS and OS) for npN and pN categories. Multivariate analysis showed that the npN and pN categories were both independent prognostic factors for DFS (HR 1.614, 95% CI 1.541 to 1.673; HR 1.604, 95% CI 1.533 to 1.679) and OS (HR 1.633, 95% CI 1.550 to 1.720; HR 1.470, 95% CI 1.410 to 1.532). However, the npN category was superior to the pN category by Harrell's C statistic. We conclude that it is thus feasible to consider TDs as positive lymph nodes in the pN category when evaluating the prognoses of CRC patients, and the npN category is potentially superior to the TNM (7th edition) pN category for predicting DFS and OS among advanced CRC patients.

We consider a geometric optimization problem of distributed multi-input multi-output (MIMO) radar systems with widely separated radar nodes in this paper. The aim is to maximize the radar surveillance performance in a given area of interest by adjusting the node positions, while satisfying practical spatial distance constraints among radar nodes. Typical constraints can be, for example, the maximum distance constraints between nodes and fusion centers (FCs) due to limited communication and the minimum distance constraints to ensure a better system spatial diversity. To achieve this goal, we first derive an analytical expression for a weighted coverage ratio (WCR) metric to evaluate the system surveillance performance. Then, using the WCR metric as the objective function, we formulate a spatial constrained geometric optimization problem for three typical MIMO radar system architectures, each of which has a unique expression of distance constraints. However, the formulated optimization problem is computationally intractable for practical scenarios due to its high dimensionality, non-convexity and especially the complex spatial constraints. To solve this problem, we propose an enhanced particle swarm optimization (PSO) algorithm, and different from the standard PSO, the particles of the proposed enhanced PSO can properly consider the distance constraints within themselves during swarm optimization process. Finally, various numerical studies show that the proposed method can effectively maximize the surveillance performance while satisfying the complex distance constraints.

The lymph node ratio (LNR), defined as the relation of tumor-infiltrated to resected lymph nodes, has been identified as an independent prognostic factor for colorectal cancer (CRC) after radical surgery. Recently, new guidelines propose counting tumor deposits (TDs) as positive lymph nodes (pLNs). The aim of this study was to investigate whether a novel LNR (nLNR) that considers TDs as pLNs can be used to accurately predict the long-term outcome of CRC patients. In this multicenter retrospective study, clinicopathological and outcome data from 2,051 stage III CRC patients who underwent R0 resection were collected between January 2004 and December 2011. Disease-free survival (DFS) and overall survival (OS) according to the nLNR category were analyzed using Kaplan-Meier survival curves. Univariate and multivariate analyses were performed to determine significant prognostic factors, and ROC curves were computed to measure the predictive capacity of the nLNR category. The 5-year DFS rates of nLNR1-4 were 68.3%, 48.4%, 33.3% and 16.5%, respectively (P<0.0001), and the 5-year OS rate of nLNR1-4 were 71.8%, 60.1%, 42.7% and 21.8%, respectively (P<0.0001). The area of under curve (AUC) of the nLNR was 0.686 (95% CI 0.663-0.710) and 0.672 (95% CI 0.648-0.697) for predicting DFS and OS. Our results demonstrate that the nLNR predicted long-term outcomes better than the LNR, npN and pN, using the cutoff points 0.250, 0.500 and 0.750.

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Highlights 18 F-PSMA-1007 PET/CT demonstrated a high detection rate for PCa patients with a raised PSA level after radical prostatectomy. PSMA-positive lesions were detected in 56 (56/71, 79%) patients. The detection efficacy for patients with PSA level >2.0 ng/mL, 1.1 to ≤2.0 ng/mL, 0.51 ng/mL to ≤1.0 ng/mL and ≤0.5 ng/mL was 100% (28/28), 100% (8/8), 80% (4/5) and 50% (14/28), respectively. Patients with ADT were more likely to have a high detection rate. The detection rate for patients with ADT was 84.6% (33/39), and detection rate for patients only receive RP was 66.7% (16/24). Higher Gleason score (≤7 vs. ≥8) leads to higher detection rate. The detection rate for patients with Gleason score ≥8 was 88.9% (32/36), detection rate for patients with Gleason score ≤7 was 58.3% (14/24).