MATERIALS AND METHODS: This was a retrospective study using computed tomography (CT) scans from 3 hospitals. Inclusion criteria were scans with 1-5 nodules of diameter ≥5 mm; exclusion criteria were poor-quality scans or those with nodules measuring <5mm in diameter. In the lesion detection phase, 2,147 nodules from 219 scans were used to develop and train the deep learning 3D-CNN to detect lesions. The 3D-CNN was validated with 235 scans (354 lesions) for sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) analysis. In the path planning phase, Bayesian optimization was used to propose possible needle trajectories for lesion biopsy while avoiding vital structures. Software-proposed needle trajectories were compared with actual biopsy path trajectories from intraprocedural CT scans in 150 patients, with a match defined as an angular deviation of <5° between the 2 trajectories.
RESULTS: The model achieved an overall AUC of 97.4% (95% CI, 96.3%-98.2%) for lesion detection, with mean sensitivity of 93.5% and mean specificity of 93.2%. Among the software-proposed needle trajectories, 85.3% were feasible, with 82% matching actual paths and similar performance between supine and prone/oblique patient orientations (P = .311). The mean angular deviation between matching trajectories was 2.30° (SD ± 1.22); the mean path deviation was 2.94 mm (SD ± 1.60).
CONCLUSIONS: Segmentation, lesion detection, and path planning for CT-guided lung biopsy using an AI-guided software showed promising results. Future integration with automated robotic systems may pave the way toward fully automated biopsy procedures.
APPROACH: In this paper, we propose a novel model called radiomics-reporting network (Radioport), which incorporates text attention. This model aims to improve the interpretability of deep learning radiomics in mammographic calcification diagnosis. Firstly, it employs convolutional neural networks (CNN) to extract visual features as radiomics for multi-category classification based on Breast Imaging Reporting and Data System (BI-RADS). Then, it builds a mapping between these visual features and textual features to generate diagnostic reports, incorporating an attention module for improved clarity.
MAIN RESULTS: To demonstrate the effectiveness of our proposed model, we conducted experiments on a breast calcification dataset comprising mammograms and diagnostic reports. The results demonstrate that our model can: (i) semantically enhance the interpretability of deep learning radiomics; and, (ii) improve the readability of generated medical reports.
SIGNIFICANCE: Our interpretable textual model can explicitly simulate the mammographic calcification diagnosis process.
METHODS: A total of 224 patients were recruited. An optimised CT protocol was applied using 100 kV and 1 mL/kg of contrast media dosing. The image quality and radiation dose exposure of this CT protocol were compared to those of a standard 120 kV, 80 mL fixed volume protocol. The radiation dose information and CT Hounsfield units were recorded. The signal-to-noise ratio, contrast-to-noise ratio (CNR) and figure of merit (FOM) were used as comparison metrics. The images were assessed for contrast opacification and visual quality by two radiologists. The renal function, contrast media volume and cost were also evaluated.
RESULTS: The median effective dose was lowered by 16% in the optimised protocol, while the arterial phase images achieved significantly higher CNR and FOM. The radiologists' evaluation showed more than 97% absolute agreement with no significant differences in image quality. No significant differences were found in the pre- and post-CT estimated glomerular filtration rate. However, contrast media usage was significantly reduced by 1,680 mL, with an overall cost savings of USD 421 in the optimised protocol.
CONCLUSION: The optimised weight-based protocol is cost-efficient and lowers radiation dose while maintaining overall contrast enhancement and image quality.
METHODS: This cross-sectional study of women who underwent DBT and ABUS from December 2019 to March 2022 included opportunistic and targeted screening cases, as well as symptomatic women. Breast density, Breast Imaging Reporting and Data System categories and histopathology reports were collected and compared. The PPV3 (proportion of examinations with abnormal findings that resulted in a tissue diagnosis of cancer), biopsy rate (percentage of biopsies performed) and cancer detection yield (number of malignancies found by the diagnostic test given to the study sample) were calculated.
RESULTS: A total of 1089 ABUS examinations were performed (age range: 29-85 y, mean: 51.9 y). Among these were 909 screening (83.5%) and 180 diagnostic (16.5%) examinations. A total of 579 biopsies were performed on 407 patients, with a biopsy rate of 53.2%. There were 100 (9.2%) malignant lesions, 30 (5.2%) atypical/B3 lesions and 414 (71.5%) benign cases. In 9 cases (0.08%), ABUS alone detected malignancies, and in 19 cases (1.7%), DBT alone detected malignancies. The PPV3 in the screening group was 14.6%.
CONCLUSION: ABUS is useful as an adjunct to DBT in the opportunistic screening and diagnostic setting.
METHODS: This qualitative study used in-depth interviews and focus group discussions to obtain information from patients with gout under follow-up in primary care and doctors who cared for them. Patients and doctors shared their gout management experiences and views on implementing HLA-B*58:01 screening in primary care. Data were coded and analysed using thematic analysis.
RESULTS: 18 patients and 18 doctors from three different healthcare settings (university hospital, public health clinics, private general practitioner clinics) participated. The acceptability to HLA-B*58:01 screening was good among the doctors and patients. We discovered inadequate disclosure of severe side effects of allopurinol by doctors due to concerns about medication refusal by patients, which could potentially be improved by introducing HLA-B*58:01 testing. Barriers to implementation included out-of-pocket costs for patients, the cost-effectiveness of this implementation, lack of established alternative treatment pathway besides allopurinol, counselling burden and concern about genetic data security. Our participants preferred targeted screening for high-risk populations instead of universal screening.
CONCLUSION: Implementing HLA-B*58:01 testing in primary care is potentially feasible if a cost-effective, targeted screening policy on high-risk groups can be developed. A clear treatment pathway for patients who test positive should be made available.
METHODS: A pilot cluster randomized controlled trial (cRCT) with qualitative interviews was conducted. Each primary care doctor was considered a cluster and randomized to either the control (usual practice) or intervention (DeSSBack) group. Patient outcomes including Roland-Morris Disability Questionnaire (RMDQ), Hospital Anxiety and Depression Scale, and a 10-point pain rating scale were measured at baseline and 2-month postintervention. The doctors in the intervention group were interviewed to explore feasibility and acceptability of using DeSSBack.
RESULTS: Thirty-six patients with nonspecific LBP participated in this study (intervention n = 23; control n = 13). Fidelity was poor among patients but good among doctors. The RMDQ and anxiety score had medium effect sizes of 0.718 and 0.480, respectively. The effect sizes for pain score (0.070) and depression score were small (0.087). There was appreciable acceptability and satisfaction with use of DeSSBack, as it was helpful in facilitating thorough and standardized management, providing appropriate treatment plans based on risk stratification, improving consultation time, empowering patient-centred care, and easy to use.
CONCLUSIONS: A future cRCT to evaluate the effectiveness of DeSSBack is feasible to be conducted in a primary care setting with minor modifications. DeSSBack was found useful by doctors and can be improved to enhance efficiency.
TRIAL REGISTRATION: The protocol of the cluster randomized controlled trial was registered at ClinicalTrials.gov (NCT04959669).
METHODOLOGY: Records of patients diagnosed with tuberculosis from 1st January 2018 to 30th September 2019 were retrieved. Sociodemographic and clinical data were extracted. Treatment outcomes and all-cause mortality were recorded at 1 year after diagnosis. Univariate, multivariate, and stepwise regression were used to determine the factors associated with all-cause mortality.
RESULTS: Four-hundred and seventy-one patients were reviewed. The mean age was 46.6 ± 19.7 years. The all-cause mortality rate at one year of diagnosis was 15.3%. Factors identified were age [aOR 1.026 (95% CI: 1.004-1.049)], chronic kidney disease [aOR 3.269 (1.508-7.088)], HIV positive status [aOR 4.743 (1.505-14.953)], active cancer [aOR 5.758 (1.605-20.652)], liver disease [aOR 6.220 (1.028-37.621)], and moderate to advanced chest X-ray findings [aOR 3.851 (1.033-14.354)].
CONCLUSIONS: On average, one in seven patients diagnosed with TB died within a year in a Malaysian tertiary hospital. Identification of this vulnerable group using the associated factors found in this study may help to reduce the risk of mortality through early intervention strategies.
METHODS: A retrospective follow up study on all patients newly diagnosed with smear positive pulmonary tuberculosis from 2017 to 2019 was conducted at three government health clinics in Sabah, utilizing data from a national electronic tuberculosis database and medical records. Descriptive statistics and binary logistic regression were applied for data analysis. The outcome of the study was the sputum conversion status at the end of the two-month intensive treatment phase with either successful conversion to smear negative or non-conversion.
RESULTS: 374 patients were included in the analysis. Our patients were generally younger than 60 years old with no medical illness and varying proportions of tuberculosis severity as judged by radiographic appearance and sputum bacillary load upon diagnosis. Foreigners constituted 27.8% of our sample. 8.8% (confidence interval: 6.2-12.2) did not convert to smear negative at the end of the intensive phase. Binary logistic regression showed that older patients ≥60 years old (adjusted odds ratio, AOR = 4.303), foreigners (AOR = 3.184) and patients with higher sputum bacillary load at diagnosis [2+ (AOR = 5.061) and 3+ (AOR = 4.992)] were more likely to have delayed sputum smear conversion.
CONCLUSION: The prevalence of delayed sputum conversion in our study was considerably low at 8.8% with age ≥60 years old, foreigners and higher pre-treatment sputum bacillary load associated with delayed conversion. Healthcare providers should take note of these factors and ensure the patients receive proper follow up treatment.
MATERIALS AND METHODS: Breast lesions and axillae of 107 patients were assessed using B-mode ultrasound and SWE. Histopathology was the diagnostic gold standard.
RESULTS: In metastatic axillary lymph nodes, qualitative SWE using color patterns had the highest area under curve (AUC) value, followed by B-mode Ultrasound (cortical thickening >3 mm) and quantitative SWE using Emax of 15.2 kPa (AUC of 81.3%, 70.1%, and 61.2%, respectively). Qualitative SWE exhibited better diagnostic performance than the other two parameters, with sensitivity of 96.0% and specificity of 56.1%. Combination of B-mode Ultrasound (using cortical thickness of >3 mm as cut-off point) and qualitative SWE (Color patterns of 2 to 4) showed sensitivity of 71.6%, specificity of 95%, PPV of 96%, NPV of 66.7%, and accuracy of 80.4%.
CONCLUSION: Qualitative SWE assessment exhibited higher accuracy compared to quantitative values. Qualitative SWE as an adjunct to B-mode ultrasound can further improve the diagnostic accuracy of metastatic ALN in breast cancer.
OBJECTIVES: This study aimed to evaluate the feasibility of a COVID-19 symptom monitoring system (CoSMoS) by exploring its utility and usability with end-users.
METHODS: This was a qualitative study using in-depth interviews. Patients with suspected COVID-19 infection who used CoSMoS Telegram bot to monitor their COVID-19 symptoms and doctors who conducted the telemonitoring via CoSMoS dashboard were recruited. Universal sampling was used in this study. We stopped the recruitment when data saturation was reached. Patients and doctors shared their experiences using CoSMoS, its utility and usability for COVID-19 symptoms monitoring. Data were coded and analysed using thematic analysis.
RESULTS: A total of 11 patients and 4 doctors were recruited into this study. For utility, CoSMoS was useful in providing close monitoring and continuity of care, supporting patients' decision making, ensuring adherence to reporting, and reducing healthcare workers' burden during the pandemic. In terms of usability, patients expressed that CoSMoS was convenient and easy to use. The use of the existing social media application for symptom monitoring was acceptable for the patients. The content in the Telegram bot was easy to understand, although revision was needed to keep the content updated. Doctors preferred to integrate CoSMoS into the electronic medical record.
CONCLUSION: CoSMoS is feasible and useful to patients and doctors in providing remote monitoring and teleconsultation during the COVID-19 pandemic. The utility and usability evaluation enables the refinement of CoSMoS to be a patient-centred monitoring system.
METHODS: All publications related to hepatitis B reactivation with the use of immunosuppressive therapy since 1975 were reviewed. Advice from key opinion leaders in member countries/administrative regions of Asian-Pacific Association for the study of the liver was collected and synchronized. Immunosuppressive therapy was risk-stratified according to its reported rate of hepatitis B reactivation.
RECOMMENDATIONS: We recommend the necessity to screen all patients for hepatitis B prior to the initiation of immunosuppressive therapy and to administer pre-emptive nucleos(t)ide analogues to those patients with a substantial risk of hepatitis and acute-on-chronic liver failure due to hepatitis B reactivation.
METHODS: 220 patients underwent CT of the chest, abdomen and pelvis (CAP) using a standard FV protocol, and subsequently, a customised 1.0 mL/kg WBV protocol within one year. Both image sets were assessed for contrast enhancement using CT attenuation at selected regions-of-interest (ROIs). The visual image quality was evaluated by three radiologists using a 4-point Likert scale. Quantitative CT attenuation was correlated with the visual quality assessment to determine the HU's enhancement indicative of the image quality grades. Contrast media usage was calculated to estimate cost-savings from both protocols.
RESULTS: Mean patient age was 61 ± 14 years, and weight was 56.1 ± 8.7 kg. FV protocol produced higher contrast enhancement than WBV, p