Ultrasound-guided placement of an anchor wire or injection of methylene blue to aid in the intraoperative localization and excision of peripheral lymph nodes in dogs and cats

OBJECTIVE To evaluate ultrasound-guided placement of an anchor wire (AW) or injection of methylene blue (MB) to aid in the intraoperative localization of peripheral lymph nodes in dogs and cats. ANIMALS 125 dogs and 10 cats with a total of 171 lymphadenectomies. PROCEDURES Medical records of dogs and cats that underwent peripheral lymphadenectomies with or without (N) the AW or MB localization technique were reviewed. Data retrieved included clinical, surgical, and histologic findings. The proportions of successful lymphadenectomies, lymph node characteristics, and complications among the 3 groups were analyzed. RESULTS 143 (84%) lymph nodes were successfully excised. Lymphadenectomy success was significantly affected by the localization technique, with 94% for group AW, 87% for group MB, and 72% for group N. Lymph node size was smaller in groups AW and MB, compared with group N. Duration of lymphadenectomy was shorter in group AW, compared with groups MB and N, and in group MB, compared with group N. Intra- (7%) and postoperative (10%) complications and final diagnosis did not significantly differ among groups. CONCLUSIONS AND CLINICAL RELEVANCE Both lymph node localization techniques were highly successful and reduced surgery time, compared with unassisted lymphadenectomy. Specifically, these techniques were effective for localization of normal-sized and nonpalpable lymph nodes and were efficient and practical options for peripheral lymphadenectomies, particularly for those that were small or nonpalpable.

A novel localization technique for peripheral ground glass opacity using geometric parameters measured on CT images

Background Currently no optimal localization technique has been established for localization of ground glass opacity (GGO). We aimed to introduce a localization technique using geometric localization for peripheral GGO. Methods We delineated the location of pulmonary GGO using geometric method which was similar with localization of a point in a spatial coordinate system. The localization technique was based on the anatomical landmarkers (ribs or intercostal spaces, capitulum costae and sternocostal joints). The geometric parameters were measured on preoperative CT images and the targeted GGO could be identified intraoperatively according to the parameters. We retrospectively collected the data of the patients with peripheral GGOs which were localized using this method and were wedge resected between June 2019 and July 2020. The efficacy and feasibility of the localization technique were assessed. Results There were 93 patients (male 34, median = 55 years) with 108 peripheral GGOs in the study. All the targeted GGOs were successfully wedge resected in the operative field with negative surgical margin at the first attempt. For each GGO, the localization parameters could be measured in 2–4 min (median = 3 min) on CT images before operation, and surgical resection could be completed in 5–10 min (median = 7 min). A total of 106 (98.15%) GGOs achieved sufficient resection margin. No complications and deaths occurred related to the localization and surgical procedure. Conclusions The localization technique can achieve satisfactory localization success rate and good safety profile. It can provide an easy-to-use alternative to localize peripheral GGO.

Social Learning Class Topper Optimization (SL-CTO) Based Hop Localization Technique for Wireless Sensor Network

To address the current situation limitation of traditional DV-Hop, we suggested a DV-Hop localization based on a rectification factor using the Social Learning Class Topper Optimization (SL - CTO) algorithm in that paper. In order to adjust the number of hops between beacon nodes, we have implemented a rectification factor in the suggested method. By measuring the dimensions of all the beacons at dumb nodes, the suggested algorithm decreases communication among unknown or dumb and beacon nodes. The model of network imbalance, It is often considered to be demonstrate a applicability of the Proposed approach in the anisotropic network. Simulations have been performed on LabVIEW@2015, and Comparisons were made with conventional DV-Hop, particle swarm optimization-based DV-Hop and runner-root optimization-based DV-Hop for our proposed algorithm. In comparison to current localization methods, simulation outcomes showed that the proposed localization technique reduces computing time, localization error variance and localization error.

MuSim: Mutation-based Fault Localization Using Test Case Proximity

Fault localization techniques aim to localize faulty statements using the information gathered from both passed and failed test cases. We present a mutation-based fault localization technique called MuSim. MuSim identifies the faulty statement based on its computed proximity to different mutants. We study the performance of MuSim by using four different similarity metrics. To satisfactorily measure the effectiveness of our proposed approach, we present a new evaluation metric called Mut_Score. Based on this metric, on an average, MuSim is 33.21% more effective than existing fault localization techniques such as DStar, Tarantula, Crosstab, Ochiai.