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Sriwijaya Journal of Radiology and Imaging Research
Published by Phlox Institute: Indonesian Medical Research Organization
ISSN : 2986853X     EISSN : 2986853X     DOI : https://doi.org/10.59345/sjrir
Core Subject : Health, Science,
Dentistry Health Professions Medicine & Pharmacology Neuroscience Physics
Focus Sriwijaya Journal of Radiology and Imaging Research (SJRIR) focused on the development of medical sciences especially radiology & imaging research for human well-being. Scope Sriwijaya Journal of Radiology and Imaging Research (SJRIR) publishes articles which encompass all aspects of basic research/clinical studies related to the field of radiology & imaging research and allied science fields, especially all type of original articles, case reports, review articles, narrative review, meta-analysis, systematic review, mini-reviews and book review.
Arjuna Subject : Kedokteran - Kedokteran Radiologi Nuklir dan Imaging
Articles 35 Documents
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Panoramic X-ray Radiation Exposure Safety Test at ATRO Muhammadiyah Makassar Rusli, Muhammad
Sriwijaya Journal of Radiology and Imaging Research Vol. 1 No. 1 (2023): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v1i1.209

Abstract

Introduction: The radiation safety protocol is an effort made to create conditions so that the dose of ionizing radiation that affects humans and the environment does not exceed the specified limit value. This study aimed to measure exposure to X-ray radiation on panoramic X-rays at ATRO Muhammadiyah Mak assar. Methods: This research was conducted at the radiology department of ATRO Muhammadiyah Makassar in December 2022. The tools and materi als that will be used in this research are dental X-ray planes, survey meters, and perspex phantom, with a thickness of 10 mm, as a substitute for organs in humans. Measurement of the radiation dose exposure in dental X-ray examinations was carried out using an exposure factor of 70 kV, 8 mA at a distance of 1 meter, 2 meters, 3 meters, and 4 meters from various directions, namely fron t, left side, right side, and back with time. Different exposure on each object. Results: The highest dose intensity value was found at 0.25 seconds with a distance of 1 meter in the forward direction with a dosing accuracy of 138.4 (µSv/h). The lowest point is at 0.17 seconds with a distance of 3 meters behind wit h a dosing accuracy of 0.89 (µSv/h) for an officer who is in the radiation field during irradiation. Conclusion: The safe distance for a radiation officer and the general public who must be in the radiation field to assist patients during an examination is 4 meters from the radiation source.
A Review of Radiation Protection Standards for Workers in Hospital Radiology: A Narrative Literature Review Yoshandi, Mohammad; Annisa
Sriwijaya Journal of Radiology and Imaging Research Vol. 1 No. 1 (2023): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v1i1.210

Abstract

One of the goals of radiation protection is to prevent stochastic effects from occurring and to limit the chances of stochastic effects occurring to a limit value that is acceptable to soci ety. This literature review aims to describe radiation protection standards for workers in hospital radiology. To prevent non-stochastic effects, a limit of 0.5 Sv (50 rem) in 1 year was used for all tissues except the lens of the eye. For eyepieces, the recommended annual limit is 0.15 Sv (15 rem). This limit va lue is used either for radiation reception by a single tissue or for radiation rec eption by multiple organs. To limit stochastic effects, the annual effective equivalent dose (HE) limit for whole-body radiation reception is 50 mSv (5 re m). The radiation protection equipment that must be available at a radio diagnostic facility is a lead apron, thyroid shield, gonad protectors, gloves, Pb g oggles, and lead curtains. In conclusion, radiation protection equipment must be provided by radiology facility operators and used by radiation workers, especially radiologists and other competent doctors. Periodic inspection and st andardized maintenance of radiation shields must be carried out for the sake of public safety.
Brain Magnitude Resonance Imaging Examinati on Protocol in Epilepsy Patients: A Narrative Literature Review Istiqomah, Sarah Wilmar
Sriwijaya Journal of Radiology and Imaging Research Vol. 1 No. 1 (2023): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v1i1.211

Abstract

MRI is becoming the choice for performing high-resolution structural imaging in epilepsy. Selection of brain MRI sequences with appropriate clinical epilepsy is very important to s how abnormalities clearly so that the diagnosis can be made. The epilepsy protocol includes T1 and T2 weights, as well as fluid-attenuated inversion recovery (FLAIR). This literature review aims to describe the protocol for brain MRI examination in epilepsy patients. There is one special sequence that is used as a parameter for brain MRI examination in cases of epilepsy, namely fast spin-echo inversion recovery (FSE-IR), which is a modification of conventional inversion recovery and is used to suppress signals from certain tissues a ssociated with T2 weighting. The coronal T2 propeller sequence is the sequence for showing pathology in the hippocampus. Coronal FSE-IR is useful for evaluating the hippocampus from the coronal side by eliminating the white signal to increase the contrast between white matter and gray matter. In conclu sion, each sequence in the MRI examination protocol has a specific goal, namely to reveal pathology on the MRI slice and establish a diagnosis.
Overview of Chest Radiology Images of Coron avirus Disease 2019 (COVID-19) Patients at Undata General Hospital, Palu, Indonesia Nurahalisa, Siti; Sulistiana, Ria
Sriwijaya Journal of Radiology and Imaging Research Vol. 1 No. 1 (2023): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v1i1.212

Abstract

Introduction: M aking a diagnosis of COVID-19 requires quite sophisticated technology and tools. To make a diagnosis of COVID-19, a technology and tool are needed that can identify the presence of the genetic material of the SARS-CoV-2 virus. How ever, the existence of PCR tools cannot be spread evenly in various regions of Indonesia because the tools are quite difficult to operate and require adequate laboratory facilities. The radiological image of the chest is a promising supporting examination to be developed as a supporting examination to diagnose COVID-19. This study aimed to obtain an overview of chest radiology image s of COVID-19 patients at Undata General Hospital, Palu, Indonesia. Methods: This study is a descriptive observational study. A total of 20 research su bjects participated in this study. Observations of chest radiological images are presented in a univariate manner in the form of the frequency distribution of data using SPSS software. Results: Study subjects with mild degree s of COVID-19 had normal chest X-rays. Meanwhile, research subjects with moderate degrees of COVID-19 generally have a chest X-ray photo in the form of an infiltrate. Study subjects with severe COVID-19 had a chest X-ray image in the form of consolidated-ground glass opacity. Conclusion: The more severe the degree of COVID-19 is in line with the higher the inflammation in the lung tissu e, so a radiological image of the thorax appears in the form of a consolidated-ground glass opacity image.
Overview of Radiological Images of Chest X-ray s of Patients with Tuberculosis at BARI General Hospital, Palembang, Indonesia Agustina, Dessy
Sriwijaya Journal of Radiology and Imaging Research Vol. 1 No. 1 (2023): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v1i1.213

Abstract

Introduction: Tuberculosis (TB) is a chronic and contagious infectious disease that can attack almost all organs of the human body, especially the lungs, caused by the bacterium Mycobacterium Tuberculosis. Chest X-ray is a fast imaging technique and one of the main tools that have high sensitivity for diagnosing pul monary TB. This study aimed to find out more about the overview of radiological images of chest X-rays of patients with tuberculosis at BARI General Hospital , Palembang, Indonesia. Methods: This study is a descriptive observational study. A total of 50 research subjects participated in this study. The radiological images of the chest X-rays are presented in the form of grouping, namel y the presence of infiltrates, consolidation, fibrosis, cavities, and effusions. In addition, observations were made on the location of the emergence of va rious abnormalities on the radiological image of the chest X-rays in a descriptive way. Results: This study showed that the majority of study subjects had to infiltrate radiological features, and the majority of study subjects had le sions at the apex of the superior lobe. Conclusion: The radiological images of the chest X-rays in TB patients show the presence of infiltrate, consoli dation, fibrosis, effusion, and cavity lesions, where the lesions are in line with the progressivity of TB.
Loculated Right-Sided Hydropneumothorax Mimicking Giant Pulmonary Bullae in a Post-Tuberculosis Patient: A Multimodality Imaging Diagnostic Challenge Sidik Teghar Sanyadi; Bernard Sujijanto Suwito; Gandhi Estrada Atmanto
Sriwijaya Journal of Radiology and Imaging Research Vol. 4 No. 1 (2026): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v4i1.245

Abstract

Introduction: Post-tuberculosis lung disease remains a significant public health challenge affecting millions of individuals globally, representing a substantial health burden in tuberculosis-endemic regions and in developed countries with immigration from endemic areas. Loculated hydropneumothorax as a late complication of successfully treated pulmonary tuberculosis is a rare but diagnostically challenging entity, particularly when imaging findings suggest alternative pathology such as giant pulmonary bullae. This case illustrates the complexity of post-tuberculosis complications and the essential role of multimodality imaging. Case Presentation: A 63-year-old retired woman presented to the emergency department with three days of progressive dyspnea accompanied by productive cough with yellowish-white sputum. Physical examination revealed severe tachypnea (41 breaths per minute), clinically significant hypoxemia (SpO₂ 88 percent on room air), and diminished breath sounds over the right hemithorax with crackles in the right upper lobe. Chest radiography demonstrated a large thin-walled cavity (18 by 9.5 by 14 centimeters) with a horizontal air-fluid level in the right hemithorax, mediastinal leftward shift, and right costophrenic sinus obliteration. Thoracic point-of-care ultrasound revealed predominant gas throughout the right hemithorax with minimal pleural fluid in dependent zones and absence of identifiable lung tissue above the hemidiaphragm. Contrast-enhanced computed tomography definitively identified loculated right-sided hydropneumothorax with thin-walled pleural compartment, air-fluid level, compressive atelectasis of right lower and middle lobes, and post-tuberculosis fibrotic sequelae. Individual imaging modalities — radiography, ultrasound, and computed tomography — each contributed essential diagnostic information, demonstrating that none is sufficient in isolation. Conclusion: Loculated hydropneumothorax must be considered in the differential diagnosis of large cavitary lesions in post-tuberculosis patients. A multimodality imaging approach is essential for achieving diagnostic certainty and preventing unnecessary surgical intervention.
Diffusion Tensor Imaging and Resting-State Functional MRI Reveal Coupled Microstructural and Default-Mode Network Alterations in Mild Cognitive Impairment: A Diagnostic Accuracy Study Taryudi Suharyana; Akmal Hasan; Jason Willmare
Sriwijaya Journal of Radiology and Imaging Research Vol. 3 No. 2 (2025): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v3i2.285

Abstract

Introduction: Early-stage neurodegeneration — clinically expressed as mild cognitive impairment (MCI) — lacks accessible imaging biomarkers that link microstructural white-matter injury to functional network disruption. We evaluated whether integrating diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI) at 3.0-Tesla improves detection of MCI and substantiates a structural-to-functional disconnection mechanism. Methods: In this STARD-2015-compliant, prospective cross-sectional diagnostic accuracy study at a tertiary hospital in Palembang, Indonesia, 85 participants (45 MCI, 40 age-, sex- and education-matched controls) underwent single-scanner 3.0-T MRI. DTI metrics (fractional anisotropy [FA], mean diffusivity [MD]) were derived by tract-based spatial statistics and posterior-cingulate-seeded Default Mode Network (DMN) connectivity by CONN. Consensus clinical diagnosis (Petersen criteria) was the blinded reference standard. Diagnostic accuracy used ROC/DeLong AUC, Wilson 95% confidence intervals (CIs), Cohen κ, and multivariable logistic regression. Results: Posterior-cingulum FA was lower (0.399 ± 0.058 vs 0.489 ± 0.052, p<0.001) and MD higher in MCI; PCC–mPFC connectivity was reduced (0.392 ± 0.124 vs 0.586 ± 0.136, p<0.001). FA discriminated MCI with AUC 0.903 (95% CI 0.831–0.974; sensitivity 82.2%, specificity 90.0%); a combined FA+FC model reached AUC 0.901 with sensitivity 95.6% and NPV 93.8% but did not exceed FA alone (DeLong p=0.90). FA and connectivity were strongly correlated (r=0.79, 95% CI 0.69–0.86, p<0.001). Inter-reader agreement was substantial (κ=0.74 and 0.67). Conclusion: Multimodal 3.0-T DTI and rs-fMRI provides an accurate, radiation-free signature of early-stage neurodegeneration; the coupling between cingulum microstructure and DMN connectivity is consistent with structural disconnection being associated with functional decoupling and offers a deployable tool for tertiary referral centres.
Deep Learning-Based Image Enhancement of Low-Field Brain MRI: A Multicenter Validation of Diagnostic Image Quality and Lesion Detection Rachmat Hidayat; Linda Purnama
Sriwijaya Journal of Radiology and Imaging Research Vol. 3 No. 2 (2025): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v3i2.288

Abstract

Introduction: Low-field MRI (LF-MRI) widens neuroimaging access in resource-limited settings but suffers low signal-to-noise ratio (SNR), reduced resolution and artefacts. We developed and validated a deep-learning framework for image normalisation and noise reduction to elevate 0.35T brain MRI toward high-field quality, and tested whether it improves clinically significant lesion detection. Methods: In a multicentre retrospective diagnostic-accuracy study (STARD 2015), 450 adults underwent non-contrast 0.35T brain MRI (T1W, T2W, FLAIR) across three private tertiary centres in Palembang, Indonesia. Images were enhanced with a CycleGAN incorporating Vision-Transformer blocks. Three blinded neuroradiologists scored a 5-point Likert scale and recorded lesion presence; paired 1.5T MRI was the reference standard. Sensitivity, specificity, AUC and likelihood ratios were computed with 95% CIs; tests compared by McNemar and DeLong; agreement by Fleiss kappa. Results: AI enhancement improved all quality metrics (e.g., T1W PSNR 22.15 to 28.45 dB; SSIM 0.71 to 0.89; all p<0.001). For lesion detection, AI-enhanced LF-MRI achieved sensitivity 93.9% (95% CI 89.4–96.6), specificity 91.1% (87.1–94.0) and AUC 0.94 (0.91–0.97) versus 78.3%, 81.1% and 0.81 for original images (DeLong p<0.001; McNemar p<0.001). LR+ rose to 10.56 and LR− fell to 0.067. Inter-reader agreement was almost perfect (Fleiss kappa 0.78–0.85). Conclusion: A CycleGAN-with-transformer framework substantially improved objective quality and diagnostic performance of 0.35T brain MRI toward high-field standards with almost-perfect reader agreement. Pending prospective and external validation, AI enhancement is a low-cost route to more equitable neuroimaging.
Deep-Learning Pharmacokinetic Modelling for Personalised Low-Dose Gadolinium in Oncological 3.0-T MRI: A Diagnostic-Accuracy Study Oliva Azalia Putri; Sony Sanjaya
Sriwijaya Journal of Radiology and Imaging Research Vol. 3 No. 2 (2025): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v3i2.290

Abstract

Introduction: Weight-based dosing of gadolinium-based contrast agents (GBCA; 0.1 mmol/kg) in oncological MRI disregards individual haemodynamics and tumour microvascularity, contributing to avoidable cumulative exposure and tissue-retention risk. We evaluated an artificial-intelligence (AI)-assisted pharmacokinetic-modelling approach to personalise and reduce GBCA dose while preserving diagnostic performance. Methods: In this prospective, paired diagnostic-accuracy study reported per STARD 2015 at a tertiary hospital in Palembang, Indonesia, 152 adults (198 lesions) with histologically confirmed solid primary malignancies underwent 3.0-T contrast-enhanced MRI. A convolutional-neural-network extended-Tofts model derived each patient’s minimum effective gadobutrol dose, compared against the standard 0.1 mmol/kg protocol. Two radiologists, blinded to clinical data and to a composite reference standard (histopathology and ≥6-month imaging follow-up), assessed signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), 5-point diagnostic confidence and lesion characterisation. Sensitivity, specificity, AUC (DeLong), likelihood ratios, Cohen’s κ and McNemar testing were computed with 95% confidence intervals. Results: The AI protocol reduced GBCA dose by 38.4% (4.6 vs 7.5 mL; p<0.001). Sensitivity was 95.2% (95% CI 90.9–97.6), specificity 83.3% (66.4–92.7) and AUC 0.94 (0.90–0.97) versus 0.95 (0.91–0.98) for standard dose (DeLong p=0.620; McNemar p=0.773). SNR and CNR were non-inferior (all p>0.05). Inter-reader agreement was substantial-to-almost-perfect (characterisation κ 0.83; confidence κ 0.88). Diagnostic adequacy was maintained in 149/152 cases (98%). Conclusion: AI-assisted pharmacokinetic modelling enabled a 38% gadolinium-dose reduction without loss of diagnostic accuracy or image quality, supporting personalised contrast administration and lower cumulative exposure in oncological MRI.
Radiomics-Based Machine Learning for Automated Detection and Rupture-Risk Stratification of Cerebral Vascular Malformations: A Retrospective Cohort Study Hesti Putri; Nur Diana; Paula Magna Pablo-Rodriguez; Nadia Khoirina
Sriwijaya Journal of Radiology and Imaging Research Vol. 3 No. 2 (2025): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v3i2.291

Abstract

Introduction: Cerebral vascular malformations (CVMs) are the leading cause of spontaneous intracranial haemorrhage, yet their detection on CT/MR angiography is operator-dependent and existing machine-learning models derive almost exclusively from Caucasian or East Asian cohorts. We developed and internally validated a population-specific radiomics pipeline for CVM detection and rupture-risk stratification in a Southeast Asian population. Methods: In this retrospective diagnostic-and-prognostic cohort (STARD 2015; CLAIM) at a tertiary hospital in Palembang, Indonesia (2020–2025), 486 adults with diagnostic-quality CTA or TOF-MRA were analysed. After resampling and normalisation, 1,218 PyRadiomics features were reduced by LASSO and used to train Random Forest, SVM and XGBoost models (70/30 split). The reference standard was blinded consensus segmentation by two consultant neuroradiologists. Diagnostic accuracy (Wilson CI), AUC (DeLong), likelihood ratios, Cohen κ, McNemar test and a multivariable rupture model were computed. Results: CVM prevalence was 42.8% (208/486). XGBoost was the best detector (AUC 0.963 (95% CI 0.950–0.977); sensitivity 88.5 (95% CI 83.4–92.1)%; specificity 92.4 (95% CI 88.7–95.0)%; LR+ 11.71 (95% CI 7.74–17.72)), outperforming a single radiologist (ΔAUC 0.128, p<0.001; McNemar χ2=9.72, p=0.002 (discordant pairs b=73, c=39)). Inter-reader agreement was almost perfect (κ 0.845 (95% CI 0.797–0.893)). A radiomics-clinical model stratified rupture (AUC 0.846 (95% CI 0.792–0.901)), with lesion size (OR 4.26 (95% CI 2.60–6.98)) and hypertension (OR 2.46 (95% CI 1.18–5.14)) dominant and good calibration (χ2=14.87, df=8, p=0.062). Conclusion: A population-specific radiomics machine-learning pipeline achieved high diagnostic accuracy for CVM detection and clinically useful rupture-risk stratification, supporting operator-independent neurovascular triage in Southeast Asian settings. External validation is warranted.

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