Selection of CT variables and prognostic models for outcome prediction in patients with traumatic brain injury

Background Traumatic brain injuries (TBI) are associated with high risk of morbidity and mortality. Early outcome prediction in patients with TBI require reliable data input and stable prognostic models. The aim of this investigation was to analyze different CT classification systems and prognostic calculators in a representative population of TBI-patients, with known outcomes, in a neurointensive care unit (NICU), to identify the most suitable CT scoring system for continued research. Materials and methods We retrospectively included 158 consecutive patients with TBI admitted to the NICU at a level 1 trauma center in Sweden from 2012 to 2016. Baseline data on admission was recorded, CT scans were reviewed, and patient outcome one year after trauma was assessed according to Glasgow Outcome Scale (GOS). The Marshall classification, Rotterdam scoring system, Helsinki CT score and Stockholm CT score were tested, in addition to the IMPACT and CRASH prognostic calculators. The results were then compared with the actual outcomes. Results Glasgow Coma Scale score on admission was 3–8 in 38%, 9–13 in 27.2%, and 14–15 in 34.8% of the patients. GOS after one year showed good recovery in 15.8%, moderate disability in 27.2%, severe disability in 24.7%, vegetative state in 1.3% and death in 29.7%. When adding the variables from the IMPACT base model to the CT scoring systems, the Stockholm CT score yielded the strongest relationship to actual outcome. The results from the prognostic calculators IMPACT and CRASH were divided into two subgroups of mortality (percentages); ≤50% (favorable outcome) and > 50% (unfavorable outcome). This yielded favorable IMPACT and CRASH scores in 54.4 and 38.0% respectively. Conclusion The Stockholm CT score and the Helsinki score yielded the closest relationship between the models and the actual outcomes in this consecutive patient series, representative of a NICU TBI-population. Furthermore, the Stockholm CT score yielded the strongest overall relationship when adding variables from the IMPACT base model and would be our method of choice for continued research when using any of the current available CT score models.

Talo-calcaneal distraction Ilizarov frame: an ergonomic method to manage intra-articular fractures of calcaneum

Background: Principle of distraction and an indirect reduction was used to promote healing of fractures and adequate regeneration of cartilage at the subtalar joint. Aims and Objectives: The study was aimed to elaborate and develop role of Ilizarov as an alternative biologicalmethod to manage intraarticular fracture calcaneum with minimal chances of infection. Materials and Methods: Twenty-one patients were studied and the mean age of patients was 40.7 years (span: 20 to 65 years). Sanders CT classification was used to divide into type II, 11 (52.38%); type III, 7 (33.33%) and type IV, 3 (14.28%). The average followup was 17.2 months (range: 6 to 24 months). AOFAS scale for ankle and hindfoot was used for assessment of patients- 7 (33.33%) excellent, 7 (33.33%) good, 3 (14.28%) fair, and 4 (19.04%) poor results. The average score was 81.5 ±12.1. The mean period of treatment was 12 weeks (10 to 14 weeks). Results: On radiological assessment, Bohler’s angle change was 19.7±4.4 degrees to 33.51± 5.7 degrees; angle of Gissane changed from 126.4 ± 6.7 degrees preoperatively to 124.9 ± 6.9 degrees postoperatively; calcanealheight changed 40.14 ± 1.98 mm preoperatively to 43.33 ± 1.87 mm and width changed 45.09 ±3.65 mm preoperatively to 43.09 ±3.16 mm postoperatively and reduction malalignment >10 degrees in 5 patients. Superficial skin infection at wire insertion sites was the most common complication encountered in our cases. Conclusion: Our results with this ergonomic technique in a small number of 21 non-randomised cases with a mean followup of 17.2 years attribute towards an alternate surgical substitute to conventional open reduction techniques in the treatment of intra-articular fractures of calcaneum having lesser rate of complications.

Diagnosis of COVID-19 using 3D CT scans and vaccination for COVID-19

Purpose For the first time in a decade, a new form of pneumonia virus, coronavirus, COVID-19, appeared in Wuhan, China. To date, it has affected millions of people, killed thousands and resulted in thousands of deaths around the world. To stop the spread of this virus, isolate the infected people. Computed tomography (CT) imaging is very accurate in revealing the details of the lungs and allows oncologists to detect COVID. However, the analysis of CT scans, which can include hundreds of images, may cause delays in hospitals. The use of artificial intelligence (AI) in radiology could help to COVID-19-positive cancer in this manner is the main purpose of the work. Design/methodology/approach CT scans are a medical imaging procedure that gives a three-dimensional (3D) representation of the lungs for clinical purposes. The volumetric 3D data sets can be regarded as axial, coronal and transverse data sets. By using AI, we can diagnose the virus presence. Findings The paper discusses the use of an AI for COVID-19, and CT classification issue and vaccination details of COVID-19 have been detailed in this paper. Originality/value Originality of the work is, all the data can be collected genuinely and did research work doneown methodology.

Comparison of the CO-RADS and the RSNA chest CT classification system concerning sensitivity and reliability for the diagnosis of COVID-19 pneumonia

Background The Radiological Society of North America (RSNA) recently published a chest CT classification system and Dutch Association for Radiology has announced Coronavirus disease 2019 (COVID-19) reporting and data system (CO-RADS) to provide guidelines to radiologists who interpret chest CT images of patients with suspected COVID-19 pneumonia. This study aimed to compare CO-RADS and RSNA classification with respect to their sensitivity and reliability for diagnosis of COVID-19 pneumonia. Results A retrospective study assessed consecutive CT chest imaging of 359 COVID-19-positive patients. Three experienced radiologists who were aware of the final diagnosis of all patients, independently categorized each patient according to CO-RADS and RSNA classification. RT-PCR test performed within one week of chest CT scan was used as a reference standard for calculating sensitivity of each system. Kappa statistics and intraclass correlation coefficient were used to assess reliability of each system. The study group included 359 patients (180 men, 179 women; mean age, 45 ± 16.9 years). Considering combination of CO-RADS 3, 4 and 5 and combination of typical and indeterminate RSNA categories as positive predictors for COVID-19 diagnosis, the overall sensitivity was the same for both classification systems (72.7%). Applying both systems in moderate and severe/critically ill patients resulted in a significant increase in sensitivity (94.7% and 97.8%, respectively). The overall inter-reviewer agreement was excellent for CO-RADS (κ = 0.801), and good for RSNA classification (κ = 0.781). Conclusion CO-RADS and RSNA chest CT classification systems are comparable in diagnosis of COVID-19 pneumonia with similar sensitivity and reliability.

Clinical Pattern of Preoperative Positron Emission Tomography/Computed Tomography (PET/CT) Can Predict the Aggressive Behavior of Resected Solid Pseudopapillary Neoplasm of the Pancreas

Predicting the aggressiveness of solid pseudopapillary neoplasms (SPNs) remains an important goal. The present study aimed to identify perioperative factors that can predict patients who will develop clinically aggressive SPN. Records of individuals with pathologically confirmed SPN from 2006 to 2017 were obtained from the patient registry database of Yonsei University, Severance Hospital. For this study, aggressive behavior was defined as SPN that had recurred, metastasized, or involved adjacent organs. A total of 98 patients diagnosed with SPNs were analyzed retrospectively. Of these, 10 were reported to have SPNs with aggressive characteristics. We found that age (≥40 years; p = 0.039), symptomatic presentation (p = 0.001), tumor size (>10 cm; p < 0.001), positron emission tomography/computed tomography (PET/CT) classification (p < 0.001), and lymphovascular invasion (p = 0.003) were significantly correlated with aggressive behavior of SPNs. Multivariate analysis showed that PET/CT configuration (p = 0.002) (exp(β)111.353 (95% confidence interval (CI): 5.960–2081), age ≥40 years (p = 0.015) (exp(β) 23.242 (95% CI: 1.854–291.4)), and lymphovascular invasion (p = 0.021) (exp(β) 22.511 (95% CI: 1.595–317.6)) were the only independent factors associated with aggressive SPN. Our data suggest that age ≥40 years, PET/CT Type III configuration, and lymphovascular invasion are independent factors associated with aggressive SPN. This information can help clinicians develop individualized management and surveillance plans to manage patients more effectively.

SARS-CoV-2 serology increases diagnostic accuracy in CT-suspected, PCR-negative COVID-19 patients during pandemic

Background In the absence of PCR detection of SARS-CoV-2 RNA, accurate diagnosis of COVID-19 is challenging. Low-dose computed tomography (CT) detects pulmonary infiltrates with high sensitivity, but findings may be non-specific. This study assesses the diagnostic value of SARS-CoV-2 serology for patients with distinct CT features but negative PCR. Methods IgM/IgG chemiluminescent immunoassay was performed for 107 patients with confirmed (group A: PCR + ; CT ±) and 46 patients with suspected (group B: repetitive PCR-; CT +) COVID-19, admitted to a German university hospital during the pandemic’s first wave. A standardized, in-house CT classification of radiological signs of a viral pneumonia was used to assess the probability of COVID-19. Results Seroconversion rates (SR) determined on day 5, 10, 15, 20 and 25 after symptom onset (SO) were 8%, 25%, 65%, 76% and 91% for group A, and 0%, 10%, 19%, 37% and 46% for group B, respectively; (p < 0.01). Compared to hospitalized patients with a non-complicated course (non-ICU patients), seroconversion tended to occur at lower frequency and delayed in patients on intensive care units. SR of patients with CT findings classified as high certainty for COVID-19 were 8%, 22%, 68%, 79% and 93% in group A, compared with 0%, 15%, 28%, 50% and 50% in group B (p < 0.01). SARS-CoV-2 serology established a definite diagnosis in 12/46 group B patients. In 88% (8/9) of patients with negative serology > 14 days after symptom onset (group B), clinico-radiological consensus reassessment revealed probable diagnoses other than COVID-19. Sensitivity of SARS-CoV-2 serology was superior to PCR > 17d after symptom onset. Conclusions Approximately one-third of patients with distinct COVID-19 CT findings are tested negative for SARS-CoV-2 RNA by PCR rendering correct diagnosis difficult. Implementation of SARS-CoV-2 serology testing alongside current CT/PCR-based diagnostic algorithms improves discrimination between COVID-19-related and non-related pulmonary infiltrates in PCR negative patients. However, sensitivity of SARS-CoV-2 serology strongly depends on the time of testing and becomes superior to PCR after the 2nd week following symptom onset.

Predictive Value of Rotterdam Score and Marshall Score in Traumatic Brain Injury: A Contemporary Review

This article conducts a contemporary comparative review of the medical literature to update and establish evidence as to which framework among Rotterdam and Marshall computed tomography (CT)-based scoring systems predicts traumatic brain injury (TBI) outcomes better. The scheme followed was following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines for literature search. The search started on August 15, 2020 and ended on December 31, 2020. The combination terms used were Medical Subject Headings terms, combination keywords, and specific words used for describing various pathologies of TBI to identify the most relevant article in each database. PICO question to guide the search strategy was: “what is the use of Marshall (I) versus Rotterdam score (C) in TBI patients (P) for mortality risk stratification (O).” The review is based on 46 references which included a full review of 14 articles for adult TBI patients and 6 articles for pediatric TBI articles comparing Rotterdam and Marshall CT scores. The review includes 8,243 patients, of which 2,365 were pediatric and 5,878 were adult TBI patients. Marshall CT classification is not ordinal, is more descriptive, has better inter-rater reliability, and poor performance in a specific group of TBI patients requiring decompressive craniectomy. Rotterdam CT classification is ordinal, has better discriminatory power, and a better description of the dynamics of intracranial changes. The two scoring systems are complimentary. A combination of clinical parameters, severity, ischemic and hemodynamic parameters, and CT scoring system could predict the prognosis of TBI patients with significant accuracy. None of the classifications has good evidence for use in pediatric patients.