MATERIALS AND METHODS: This consensus statement was formulated by a panel of five experts of primary care and specialist doctors. A lung cancer screening algorithm was proposed for implementation locally.
RESULTS: In an earlier pilot project collaboration, AI-assisted chest radiography had been incorporated into lung cancer screening in the community. Preliminary experience in the pilot project suggests that the system is easy to use, affordable and scalable. Drawing from experience with the pilot project, a standardised lung cancer screening algorithm using AI in Malaysia was proposed. Requirements for such a screening programme, expected outcomes and limitations of AI-assisted chest radiography were also discussed.
CONCLUSION: The combined strategy of AI-assisted chest radiography and complementary LDCT imaging has great potential in detecting early-stage lung cancer in a timely manner, and irrespective of risk status. The proposed screening algorithm provides a guide for clinicians in Malaysia to participate in screening efforts.
METHOD: A group of 19 advisors across different specialties from 11 Asian countries, met on a virtual Steering Committee meeting, to discuss and recommend the most affordable and accessible lung cancer screening modalities and their implementation, for the Asian population.
RESULTS: Significant risk factors identified for lung cancer in smokers in Asia include age 50 to 75 years and smoking history of more than or equal to 20 pack-years. Family history is the most common risk factor for nonsmokers. Low-dose computed tomography screening is recommended once a year for patients with screening-detected abnormality and persistent exposure to risk factors. However, for high-risk heavy smokers and nonsmokers with risk factors, reassessment scans are recommended at an initial interval of 6 to 12 months with subsequent lengthening of reassessment intervals, and it should be stopped in patients more than 80 years of age or are unable or unwilling to undergo curative treatment.
CONCLUSIONS: Asian countries face several challenges in implementing low-dose computed tomography screening, such as economic limitations, lack of efforts for early detection, and lack of specific government programs. Various strategies are suggested to overcome these challenges in Asia.
METHODS: In total, 154 patients (wild-type EGFR, 72 patients; Del19 mutation, 45 patients; and L858R mutation, 37 patients) were retrospectively enrolled and randomly divided into 92 training and 62 test cases. Two support vector machine (SVM) models to distinguish between wild-type and mutant EGFR (mutation [M] classification) as well as between the Del19 and L858R subtypes (subtype [S] classification) were trained using 3DBN features. These features were computed from 3DBN maps by using histogram and texture analyses. The 3DBN maps were generated using computed tomography (CT) images based on the Čech complex constructed on sets of points in the images. These points were defined by coordinates of voxels with CT values higher than several threshold values. The M classification model was built using image features and demographic parameters of sex and smoking status. The SVM models were evaluated by determining their classification accuracies. The feasibility of the 3DBN model was compared with those of conventional radiomic models based on pseudo-3D BN (p3DBN), two-dimensional BN (2DBN), and CT and wavelet-decomposition (WD) images. The validation of the model was repeated with 100 times random sampling.
RESULTS: The mean test accuracies for M classification with 3DBN, p3DBN, 2DBN, CT, and WD images were 0.810, 0.733, 0.838, 0.782, and 0.799, respectively. The mean test accuracies for S classification with 3DBN, p3DBN, 2DBN, CT, and WD images were 0.773, 0.694, 0.657, 0.581, and 0.696, respectively.
CONCLUSION: 3DBN features, which showed a radiogenomic association with the characteristics of the EGFR Del19/L858R mutation subtypes, yielded higher accuracy for subtype classifications in comparison with conventional features.
METHODS: Medline and Embase databases were searched without date restriction on May 2022 for articles that examined EAT and cardiovascular outcomes. The inclusion criteria were (1) studies measuring EAT of adult patients at baseline and (2) reporting follow-up data on study outcomes of interest. The primary study outcome was major adverse cardiovascular events. Secondary study outcomes included cardiac death, myocardial infarction, coronary revascularization, and atrial fibrillation.
RESULTS: Twenty-nine articles published between 2012 and 2022, comprising 19 709 patients, were included in our analysis. Increased EAT thickness and volume were associated with higher risks of cardiac death (odds ratio, 2.53 [95% CI, 1.17-5.44]; P=0.020; n=4), myocardial infarction (odds ratio, 2.63 [95% CI, 1.39-4.96]; P=0.003; n=5), coronary revascularization (odds ratio, 2.99 [95% CI, 1.64-5.44]; P<0.001; n=5), and atrial fibrillation (adjusted odds ratio, 4.04 [95% CI, 3.06-5.32]; P<0.001; n=3). For 1 unit increment in the continuous measure of EAT, computed tomography volumetric quantification (adjusted hazard ratio, 1.74 [95% CI, 1.42-2.13]; P<0.001) and echocardiographic thickness quantification (adjusted hazard ratio, 1.20 [95% CI, 1.09-1.32]; P<0.001) conferred an increased risk of major adverse cardiovascular events.
CONCLUSIONS: The utility of EAT as an imaging biomarker for predicting and prognosticating cardiovascular disease is promising, with increased EAT thickness and volume being identified as independent predictors of major adverse cardiovascular events.
REGISTRATION: URL: https://www.crd.york.ac.uk/prospero; Unique identifier: CRD42022338075.
MATERIALS AND METHODS: This cross-sectional study with retrospective record review was conducted in Hospital Tengku Ampuan Rahimah, Selangor, Malaysia. We included all hospitalised patients with confirmed COVID-19 infection who had undergone CT pulmonary angiogram (CTPA) examinations for suspected PTE disease between April 2021 and May 2021. Clinical data and laboratory data were extracted by trained data collectors, whilst CT images retrieved were analysed by a senior radiologist. Data analysis was performed using Statistical Package for the Social Sciences (SPSS) version 20.
RESULTS: We studied 184 COVID-19 patients who were suspected to have PTE disease. CTPA examinations revealed a total of 150 patients (81.5%) suffered from concomitant PTE disease. Among the PTE cohort, the commonest comorbidities were diabetes mellitus (n=78, 52.0%), hypertension (n=66, 44.0%) and dyslipidaemia (n=25, 16.7%). They were generally more ill than the non-PTE cohort as they reported a significantly higher COVID-19 disease category during CTPA examination with p=0.042. Expectedly, their length of both intensive care unit stays (median number of days 8 vs. 3; p=0.021) and hospital stays (median number of days 14.5 vs. 12; p=0.006) were significantly longer. Intriguingly, almost all the subjects had received either therapeutic anticoagulation or thromboprophylactic therapy prior to CTPA examination (n=173, 94.0%). Besides, laboratory data analysis identified a significantly higher peak C-reactive protein (median 124.1 vs. 82.1; p=0.027) and ferritin levels (median 1469 vs. 1229; p=0.024) among them. Evaluation of CT features showed that COVID-19 pneumonia pattern (p<0.001) and pulmonary angiopathy (p<0.001) were significantly more profound among the PTE cohort. To note, the most proximal pulmonary thrombosis was located in the segmental (n=3, 2.0%) and subsegmental pulmonary arteries (n=147, 98.0%). Also, the thrombosis predominantly occurred in bilateral lungs with multilobar involvement (n=95, 63.3%).
CONCLUSION: Overall, PTE disease remains prevalent among COVID-19 patients despite timely administration of thromboprophylactic therapy. The presence of hyperinflammatory activities, unique thrombotic locations as well as concurrent pulmonary parenchyma and vasculature aberrations in our PTE cohort implicate immunothrombosis as the principal mechanism of this novel phenomenon. We strongly recommend future researchers to elucidate this important clinical disease among our post- COVID vaccination populations.
METHOD: Prevalence of the anterior ethmoid genu, its morphology and its relationship with the frontal sinus drainage pathway was assessed. Computed tomography scans with multiplanar reconstruction were used to study non-diseased sinonasal complexes.
RESULTS: The anterior ethmoidal genu was present in all 102 anatomical sides studied, independent of age, gender and race. Its position was within the frontal sinus drainage pathway, and the drainage pathway was medial to it in 98 of 102 cases. The anterior ethmoidal genu sometimes extended laterally and formed a recess bounded by the lamina papyracea laterally, by the uncinate process anteriorly and by the bulla ethmoidalis posteriorly. Distance of the anterior ethmoidal genu to frontal ostia can be determined by the height of the posterior wall of the agger nasi cell rather than its volume or other dimensions.
CONCLUSION: This study confirmed that the anterior ethmoidal genu is a constant anatomical structure positioned within frontal sinus drainage pathway. The description of anterior ethmoidal genu found in this study explained the anatomical connection between the agger nasi cell, uncinate process and bulla ethmoidalis and its structural organisation.
METHODS: 192 patients with MTBI and ICH were treated between November 2019 to December 2020 at a single level II trauma center. The Glasgow Coma Scale (GCS) was used to classify MTBI, and initial head CT was performed according to the Canadian CT head rule. Patients with a higher risk of ICH progression, including the elderly (≥65 years old), patients on antiplatelets or anticoagulants, or patients with an initial head CT that revealed EDH, contusional bleeding, or SDH > 5 mm, and multiple ICH underwent a repeat head CT within 12 to 24 h later. Data regarding types of intervention, length of stay in the hospital, and outcome were collected. The risk of further neurological deterioration and readmission rates were compared between these two groups. All patients were followed up in the clinic after one month or contacted via phone if they did not return.
RESULTS: 189 patients underwent scheduled repeated head CT, 18% had radiological intracranial bleed progression, and 82% had no changes. There were no statistically significant differences in terms of intervention rate, risk of neurological deterioration in the future, or readmission between them.
CONCLUSION: Repeat head CT in mild TBI patients with no neurological deterioration is not recommended, even in patients with a higher risk of ICH progression.
METHOD: Two large datasets, including 1110 3D CT images, were split into five segments of 20% each. Each dataset's first 20% segment was separated as a holdout test set. 3D-CNN training was performed with the remaining 80% from each dataset. Two small external datasets were also used to independently evaluate the trained models.
RESULTS: The total combination of 80% of each dataset has an accuracy of 91% on Iranmehr and 83% on Moscow holdout test datasets. Results indicated that 80% of the primary datasets are adequate for fully training a model. The additional fine-tuning using 40% of a secondary dataset helps the model generalize to a third, unseen dataset. The highest accuracy achieved through transfer learning was 85% on LDCT dataset and 83% on Iranmehr holdout test sets when retrained on 80% of Iranmehr dataset.
CONCLUSION: While the total combination of both datasets produced the best results, different combinations and transfer learning still produced generalizable results. Adopting the proposed methodology may help to obtain satisfactory results in the case of limited external datasets.
METHODS: This is a prospective substudy nested within the CRASH-3 trial, a randomised placebo-controlled trial of TXA (loading dose 1 g over 10 min, then 1 g infusion over 8 hours) in patients with isolated head injury. CRASH-3 trial patients were recruited between July 2012 and January 2019. Participants in the current substudy were a subset of trial patients enrolled at 10 hospitals in the UK and 4 in Malaysia, who had at least one CT head scan performed as part of the routine clinical practice within 28 days of randomisation. The primary outcome was the volume of intraparenchymal haemorrhage (ie, contusion) measured on a CT scan done after randomisation. Secondary outcomes were progressive intracranial haemorrhage (post-randomisation CT shows >25% of volume seen on pre-randomisation CT), new intracranial haemorrhage (any haemorrhage seen on post-randomisation CT but not on pre-randomisation CT), cerebral infarction (any infarction seen on any type of brain scan done post-randomisation, excluding infarction seen pre-randomisation) and intracranial haemorrhage volume (intraparenchymal + intraventricular + subdural + epidural) in those who underwent neurosurgical haemorrhage evacuation. We planned to conduct sensitivity analyses excluding patients who were severely injured at baseline. Dichotomous outcomes were analysed using relative risks (RR) or hazard ratios (HR), and continuous outcomes using a linear mixed model.
RESULTS: 1767 patients were included in this substudy. One-third of the patients had a baseline GCS (Glasgow Coma Score) of 3 (n=579) and 24% had unilateral or bilateral unreactive pupils. 46% of patients were scanned pre-randomisation and post-randomisation (n=812/1767), 19% were scanned only pre-randomisation (n=341/1767) and 35% were scanned only post-randomisation (n=614/1767). In all patients, there was no evidence that TXA prevents intraparenchymal haemorrhage expansion (estimate=1.09, 95% CI 0.81 to 1.45) or intracranial haemorrhage expansion in patients who underwent neurosurgical haemorrhage evacuation (n=363) (estimate=0.79, 95% CI 0.57 to 1.11). In patients scanned pre-randomisation and post-randomisation (n=812), there was no evidence that TXA reduces progressive haemorrhage (adjusted RR=0.91, 95% CI 0.74 to 1.13) and new haemorrhage (adjusted RR=0.85, 95% CI 0.72 to 1.01). When patients with unreactive pupils at baseline were excluded, there was evidence that TXA prevents new haemorrhage (adjusted RR=0.80, 95% CI 0.66 to 0.98). In patients scanned post-randomisation (n=1431), there was no evidence of an increase in infarction with TXA (adjusted HR=1.28, 95% CI 0.93 to 1.76). A larger proportion of patients without (vs with) a post-randomisation scan died from head injury (38% vs 19%: RR=1.97, 95% CI 1.66 to 2.34, p<0.0001).
CONCLUSION: TXA may prevent new haemorrhage in patients with reactive pupils at baseline. This is consistent with the results of the CRASH-3 trial which found that TXA reduced head injury death in patients with at least one reactive pupil at baseline. However, the large number of patients without post-randomisation scans and the possibility that the availability of scan data depends on whether a patient received TXA, challenges the validity of inferences made using routinely collected scan data. This study highlights the limitations of using routinely collected scan data to examine the effects of TBI treatments.
TRIAL REGISTRATION NUMBER: ISRCTN15088122.