Preoperative localization of lung nodules: a comparative analysis of hookwire and radio-guided procedures

BackgroundHistological diagnosis of pulmonary nodules requires surgical resection on many occasions. There are multiple localization strategies each with their own benefits and complications. The objective of this study is to compare preoperative lung nodule localization with hookwire and radiotracer injection (radioguided occult lesion localization, ROLL). To compare results, complications, and volume of the sample resected with both techniques.MethodsPatients undergoing resection of pulmonary nodules with video-assisted thoracoscopy and pre-surgical localization with hookwire or ROLL were studied. Eighty-eight pulmonary nodules were resected in 76 patients: 52 with a hook wire and 36 with a radiotracer. The localization rate, the shortest distance between the nodule and the pleura, the intrapulmonary distance of the locator, the complications, the volume of the resection piece, and the histological result were all assessed. In addition, the factors that influence the volume of the surgical piece were analyzed.ResultsAll the nodules were resected with both techniques. The intrapulmonary path of the locator is longer for the ROLL group (23.91 vs. 16.28 mm; P=0.04), with no differences in the distance from the nodule to the pleura. The rate of pneumothorax was significantly higher after the placement of a hook wire (69.2% vs. 24.2%; P<0.0001), while there were no differences in the presence of hemorrhage. The volume of the pieces resected using ROLL was more minor than with hookwire, although not statistically significant (20.19 vs. 34.26 cc; P=0.07).ConclusionsPreoperative localization with the ROLL technique is safer than the placement of hookwire. In addition, the ROLL technique shows a tendency to obtain a smaller volume of resected tissue since the marking is not affected by the intrapulmonary route used during marker placement. ROLL technique allows to locate lung nodules with fewer complications than hookwire and probably gets smaller resection samples.     

Developmental stage specificity and dose response of secalonic acid D-induced cleft palate and the absence of cytotoxicity in developing mouse palate

Incidence of cleft palate (CP) in full-term mouse fetuses was evaluated following administration of 25 mg/kg of the mycotoxin, secalonic acid D (SAD), to groups of female mice on each of Days 10, 11, 12, 13, 14, or 15 of pregnancy. Although the highest numerical incidence (45.3%) of cleft palate resulted following SAD exposure on Day 12 of pregnancy, and the response tapered off to 16.9% on Day 10 and 0% on Day 15 of pregnancy, similar responses were produced also following exposures on Days 11 (38.4%) and 13 (39.9%) of pregnancy. Maternal exposure to doses of 0, 15, 20, 25, or 30 mg/kg of SAD, given on Day 12 of pregnancy indicated that although fetuses in the 30-mg/kg group had the highest incidence (51.9%) of CP, the effect was associated with increased resorptions and decreased fetal weights. The 25-mg/kg dose was optimally teratogenic (45.3% cleft palate) and maximally tolerable with neither an increase in resorptions nor a decrease in fetal body weights. Cytotoxicity of the optimally teratogenic dose of SAD (25 mg/kg given ip) on Day 12 of pregnancy was evaluated as a possible mechanism of SAD teratogenicity using indices such as mesenchymal cell density, mitotic index, and the uptake of [3H]thymidine in the developing palatal shelves. No evidence of SAD cytotoxicity was obtained in palatal shelves indicating a possible role for nonlethal cellular effects of SAD in the pathogenesis of CP. These studies also suggest the suitability of the maternal 25-mg/kg dose of SAD to study cellular biochemical effects in the developing embryo without the complicating influence of cytotoxic effects.     

Insights into pediatric rhabdomyosarcoma research: Challenges and goals

Overall survival rates for pediatric patients with high‐risk or relapsed rhabdomyosarcoma (RMS) have not improved significantly since the 1980s. Recent studies have identified a number of targetable vulnerabilities in RMS, but these discoveries have infrequently translated into clinical trials. We propose streamlining the process by which agents are selected for clinical evaluation in RMS. We believe that strong consideration should be given to the development of combination therapies that add biologically targeted agents to conventional cytotoxic drugs. One example of this type of combination is the addition of the WEE1 inhibitor AZD1775 to the conventional cytotoxic chemotherapeutics, vincristine and irinotecan.     

Intellectual outcome in children with fetal hypothyroidism

Eighty children with congenital hypothyroidism detected by newborn screening were grouped for presence of fetal hypothyroidism using skeletal maturity at the time of diagnosis as the index. Forty-five children with bone age less than 36 weeks were assigned to the delayed group; 35 with bone age 37 weeks to term were assigned to the nondelayed group. Although most children with athyrosis were found in the delayed group, the groups did not differ in birth weight, hormone levels, or family background. Assessments of intellectual and behavioral characteristics at 1, 2, 3, 4, and 5 years of age revealed that, although children in the delayed group performed within the normal range, their scores were significantly lower than those of the nondelayed group from age 2 years on. Perceptual-motor, visuospatial, and language areas were most affected. There were no differences in behavior or temperamental characteristics.     

Reaching the Final Endgame for Constant Waves of COVID-19

Despite intramuscular vaccines saving millions of lives, constant devastating waves of SARS-CoV-2 infections continue. The elimination of COVID-19 is challenging, but necessary in order to avoid millions more people who would suffer from long COVID if we fail. Our paper describes rapidly advancing and innovative therapeutic strategies for the early stage of infection with COVID-19 so that tolerating continuing cycles of infection should be unnecessary in the future. These therapies include new vaccines with broader specificities, nasal therapies and antiviral drugs some targeting COVID-19 at the first stage of infection and preventing the virus entering the body in the first place. Our article describes the advantages and disadvantages of each of these therapeutic options which in various combinations could eventually prevent renewed waves of infection. Finally, important consideration is given to political, social and economic barriers that since 2020 hindered vaccine application and are likely to interfere again with any COVID-19 endgame.     

Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19

To tune and test the generalizability of a deep learning-based model for assessment of COVID-19 lung disease severity on chest radiographs (CXRs) from different patient populations.A published convolutional Siamese neural network-based model previously trained on hospitalized patients with COVID-19 was tuned using 250 outpatient CXRs. This model produces a quantitative measure of COVID-19 lung disease severity (pulmonary x-ray severity (PXS) score). The model was evaluated on CXRs from 4 test sets, including 3 from the United States (patients hospitalized at an academic medical center (N = 154), patients hospitalized at a community hospital (N = 113), and outpatients (N = 108)) and 1 from Brazil (patients at an academic medical center emergency department (N = 303)). Radiologists from both countries independently assigned reference standard CXR severity scores, which were correlated with the PXS scores as a measure of model performance (Pearson R). The Uniform Manifold Approximation and Projection (UMAP) technique was used to visualize the neural network results.Tuning the deep learning model with outpatient data showed high model performance in 2 United States hospitalized patient datasets (R = 0.88 and R = 0.90, compared to baseline R = 0.86). Model performance was similar, though slightly lower, when tested on the United States outpatient and Brazil emergency department datasets (R = 0.86 and R = 0.85, respectively). UMAP showed that the model learned disease severity information that generalized across test sets.A deep learning model that extracts a COVID-19 severity score on CXRs showed generalizable performance across multiple populations from 2 continents, including outpatients and hospitalized patients.