Radiology - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 10 of 350
  • Item
    Thumbnail Image
    Toward transmural healing: Sonographic healing is associated with improved long-term outcomes in patients with Crohn's disease
    Vaughan, R ; Tjandra, D ; Patwardhan, A ; Mingos, N ; Gibson, R ; Boussioutas, A ; Ardalan, Z ; Al-Ani, A ; Gibson, PR ; Christensen, B (WILEY, 2022-03-28)
    BACKGROUND AND AIMS: Transmural healing has emerged as a treatment target in Crohn's disease (CD). We investigated whether transmural healing assessed with intestinal ultrasound (IUS) is associated with improved clinical outcomes in patients with CD in clinical remission. METHODS: Patients with CD in clinical remission at baseline (HBI <4) having IUS between August 2017 and June 2020 with at least 6-months' follow-up were retrospectively studied. Time to medication escalation, corticosteroid use and CD-related hospitalisation or surgery were compared by the presence or absence of sonographic healing, defined as bowel wall thickness ≤3 mm without hyperemia on color Doppler, inflammatory fat, or disrupted bowel wall stratification. Factors associated with survival were analyzed by Kaplan-Meier analysis using Cox proportional-hazard model. RESULTS: Of 202 consecutive patients (50% male), sonographic inflammation was present in 61%. During median follow-up of 19 (IQR 13-27) months, medication escalation occurred in 52%, corticosteroid use in 23%, hospitalisation in 21%, and CD-related surgery in 13%. Sonographic healing was significantly associated with a reduced risk of medication escalation (p = 0.0018), corticosteroid use (p = 0.0247), hospitalisation (p = 0.0102), and surgery (p = 0.083). On multivariable analysis, sonographic healing was significantly associated with an increased odds of medication escalation-free survival (hazard ratio [HR]:1.94; 95% CI 1.23-3.06; p = 0.004) and corticosteroid-free survival (HR:2.41; 95% CI 1.24-4.67; p = 0.009), but not with hospitalisation or surgery. CONCLUSION: In patients with CD in clinical remission, sonographic healing is associated with improved clinical outcomes. Further studies are needed to determine whether sonographic healing should be a treatment target.
  • Item
    Thumbnail Image
    F-18-FDG PET/CT features of immune-related adverse events and pitfalls following immunotherapy
    Cherk, MH ; Nadebaum, DP ; Barber, TW ; Beech, P ; Haydon, A ; Yap, KS (WILEY, 2022-02-22)
    18 F-FDG PET/CT scanning is routinely performed to stage and evaluate the treatment response in many malignancies. Immunotherapy is a rapidly growing treatment option for many cancers, and both clinicians and imaging specialists need to be familiar with 18 F-FDG PET/CT imaging characteristics unique to patients on this type of treatment. In particular, many immune-related adverse events (irAEs) can be detected on 18 F-FDG PET/CT and early accurate identification is critical to reduce treatment related morbidity and incorrect interpretation of malignant disease status. This pictorial essay reviews frequently encountered irAEs in clinical practice and their appearances on 18 F-FDG PET/CT along with a brief discussion on pseudoprogression and hyperprogression.
  • Item
    Thumbnail Image
    Prospective Associations of Susceptibility-Weighted Imaging Biomarkers with Fatigue Symptom Severity in Childhood Traumatic Brain Injury.
    Ryan, NP ; Catroppa, C ; Beauchamp, MH ; Beare, R ; Ditchfield, M ; Coleman, L ; Kean, M ; Crossley, L ; Hearps, SJC ; Anderson, V (Mary Ann Liebert Inc, 2022-08-22)
    Fatigue may be among the most profound and debilitating consequences of pediatric traumatic brain injury (TBI); however, neurostructural risk factors associated with post-injury fatigue remain elusive. This prospective study aimed to evaluate the independent value of susceptibility-weighted imaging (SWI) biomarkers, over-and-above known risk factors, to predict fatigue symptom severity in children with TBI. 42 children were examined with structural magnetic-resonance imaging (sMRI), including a SWI sequence, within 8-weeks post-injury. The PedsQL Multi-Dimensional Fatigue Scale (MFS) was administered 24-months post-injury. Compared to population expectations, the TBI group displayed significantly higher levels of general fatigue (Cohen's d = 0.44), cognitive fatigue (Cohen's d = 0.59), sleep/rest fatigue (Cohen's d = 0.37), and total fatigue (Cohen's d = 0.63). In multi-variate models adjusted for TBI severity, child demographic factors and depression, sub-acute volume of SWI lesions was independently associated with all fatigue symptom domains. The magnitude of the brain-behavior relationship varied by fatigue symptom domain, such that the strongest relationships were observed for the cognitive fatigue and total fatigue symptom scales. Overall, we found that total volume of SWI lesions explained up to 24% additional variance in multi-dimensional fatigue, over-and-above known risk factors. SWI has potential to improve prediction of post-injury fatigue in children with TBI. Our preliminary findings suggest that volume of SWI lesions may represent a novel, independent biomarker of post-injury fatigue scores, which could help to identify high-risk children who are likely to benefit from targeted psychoeducation and/or preventive strategies to minimize risk of persisting fatigue.
  • Item
    Thumbnail Image
    Verbal notification of radiology results: are radiologists meeting expectations?
    Preece, E ; Whitchurch, M ; Sutherland, T (Wiley, 2022-08)
    BACKGROUND: Delayed communication of radiographic findings is associated with poor patient outcomes and significant medicolegal risk. Radiologists verbally contact referring practitioners with urgent findings, although practitioner's expectations regarding notification have rarely been examined. AIM: To assess differences in preferred practice between radiologists and referring practitioners in the verbal communication of urgent radiology findings. METHODS: For 33 clinical stems, respondents were asked if they would issue (radiologists) or expect to receive (referring practitioners) verbal notification of results or routine written communication only. Surveys were emailed to radiologists and referring practitioners of varying experience at a tertiary referral hospital in Melbourne, Victoria. RESULTS: A total of 97 survey responses was received. Eighty responses were from referring practitioners and 17 from radiologists. Referring practitioners were seen to slightly prefer verbal notification more often than issued by radiologists overall (61%; 95% confidence interval (CI) 57-66% verbal notification expected vs 58%; 95% CI 52-64% issued). More senior referring practitioners with greater than 10 years' experience expected verbal notification more often (67%; 95% CI 59-75%), and more senior radiologists issued verbal reports less often (54%; 95% CI 39-69%). More junior referring practitioners, for example, registrars or fellows, expected notification less often overall (59%; 95% CI 43-76%). Subgroup analysis demonstrated statistically significant differences in notification preferences for certain clinical scenarios. CONCLUSIONS: Overall results show fair correlation between referrer's expectations of verbal notification and the provision of verbal notification by radiologists. However, there were discrepancies in the practice and preferences of more junior and senior practitioners in certain clinical scenarios.
  • Item
    Thumbnail Image
    Macroscopic fat containing renal cell carcinoma
    Kirkinis, M ; Sutherland, T (WILEY, 2021-03-05)
    Renal masses containing macroscopic fat traditionally are pathognomonic for angiomyolipoma, a benign tumour. We describe two cases contrary to this axiom, the first being initially referred for angioembolisation, but subsequently biopsied when it was angiographically occult, whilst the second case showed a small macroscopic fat component and arterial enhancement prompting biopsy. Neither of these two cases demonstrated calcification which would usually suggest a more sinister lesion requiring further workup. The results demonstrated renal cell carcinoma for both lesions. Our multidisciplinary meeting approach to renal masses with a small amount of macroscopic fat and no calcifications has now changed.
  • Item
    No Preview Available
    Computer-aided Measurement System Using Image Processing for Measuring Cobb Angle in Scoliosis
    Moftian, N ; Soltani, TS ; Salahzadeh, Z ; Pourfeizi, HH ; Gheibi, Y ; Fazlollahi, A ; Rezaei-Hachesu, P (Briefland, 2022-01-01)
    Background: One of the spine deformities is scoliosis, and Cobb angle is generally used to assess it. Objectives: In this study, a computer-aided measurement system (CAMS) was presented as a new repeatable and reproducible approach to assess the Cobb angle in idiopathic scoliosis patients. Methods: Python libraries, including OpenCV and Numpy were used for image processing and design of the software. To assess the repeatability and reproducibility of the CAMS, a series of 98 anterior-posterior radiographs from patients with idiopathic scoliosis were used. Assessments were done by five independent observers. Each radiograph was assessed by each observer three times with a minimum break of two weeks among assessment. The single measure intraclass correlation coefficient (ICC), the mean absolute difference (MAD), and the standard error measurement (SEM) values were used for intra- and inter-observer reliability. Results: The inter-observer analysis indicated that the ICCs ranged from 0.94 - 0.99, and the MAD between manual and CAMS were less than 3°. For intra-observer measurements, the combined SEM between all observers for the manual and CAMS was 1.79° and 1.27°, respectively. An ICC value of 0.97 with 95% confidence interval (CI) was excellent in CAMS for inter-observer reliability. The MAD of CAMS was 2.18 ± 2.01 degrees. Conclusions: The CAMS is an effective and reliable approach for assessing scoliotic curvature in the standing radiographs of thoraco-lumbar. Moreover, CAMS can accelerate clinical visits, and its calculation results are reliable.
  • Item
    No Preview Available
    Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy
    Park, B-Y ; Lariviere, S ; Rodriguez-Cruces, R ; Royer, J ; Tavakol, S ; Wang, Y ; Caciagli, L ; Caligiuri, ME ; Gambardella, A ; Concha, L ; Keller, SS ; Cendes, F ; Alvim, MKM ; Yasuda, C ; Bonilha, L ; Gleichgerrcht, E ; Focke, NK ; Kreilkamp, BAK ; Domin, M ; von Podewils, F ; Langner, S ; Rummel, C ; Rebsamen, M ; Wiest, R ; Martin, P ; Kotikalapudi, R ; Bender, B ; O'Brien, TJ ; Law, M ; Sinclair, B ; Vivash, L ; Kwan, P ; Desmond, PM ; Malpas, CB ; Lui, E ; Alhusaini, S ; Doherty, CP ; Cavalleri, GL ; Delanty, N ; Kalviainen, R ; Jackson, GD ; Kowalczyk, M ; Mascalchi, M ; Semmelroch, M ; Thomas, RH ; Soltanian-Zadeh, H ; Davoodi-Bojd, E ; Zhang, J ; Lenge, M ; Guerrini, R ; Bartolini, E ; Hamandi, K ; Foley, S ; Weber, B ; Depondt, C ; Absil, J ; Carr, SJA ; Abela, E ; Richardson, MP ; Devinsky, O ; Severino, M ; Striano, P ; Parodi, C ; Tortora, D ; Hatton, SN ; Vos, SB ; Duncan, JS ; Galovic, M ; Whelan, CD ; Bargallo, N ; Pariente, J ; Conde-Blanco, E ; Vaudano, AE ; Tondelli, M ; Meletti, S ; Kong, X-Z ; Francks, C ; Fisher, SE ; Caldairou, B ; Ryten, M ; Labate, A ; Sisodiya, SM ; Thompson, PM ; McDonald, CR ; Bernasconi, A ; Bernasconi, N ; Bernhardt, BC (OXFORD UNIV PRESS, 2022-03-25)
    Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.
  • Item
  • Item
    No Preview Available
    Healthy Life-Year Costs of Treatment Speed From Arrival to Endovascular Thrombectomy in Patients With Ischemic Stroke A Meta-analysis of Individual Patient Data From 7 Randomized Clinical Trials
    Almekhlafi, MA ; Goyal, M ; Dippel, DWJ ; Majoie, CBLM ; Campbell, BCV ; Muir, KW ; Demchuk, AM ; Bracard, S ; Guillemin, F ; Jovin, TG ; Mitchell, P ; White, P ; Hill, MD ; Brown, S ; Saver, JL (AMER MEDICAL ASSOC, 2021-05-03)
    Importance: The benefits of endovascular thrombectomy (EVT) are time dependent. Prior studies may have underestimated the time-benefit association because time of onset is imprecisely known. Objective: To assess the lifetime outcomes associated with speed of endovascular thrombectomy in patients with acute ischemic stroke due to large-vessel occlusion (LVO). Data Sources: PubMed was searched for randomized clinical trials of stent retriever thrombectomy devices vs medical therapy in patients with anterior circulation LVO within 12 hours of last known well time, and for which a peer-reviewed, complete primary results article was published by August 1, 2020. Study Selection: All randomized clinical trials of stent retriever thrombectomy devices vs medical therapy in patients with anterior circulation LVO within 12 hours of last known well time were included. Data Extraction/Synthesis: Patient-level data regarding presenting clinical and imaging features and functional outcomes were pooled from the 7 retrieved randomized clinical trials of stent retriever thrombectomy devices (entirely or predominantly) vs medical therapy. All 7 identified trials published in a peer-reviewed journal (by August 1, 2020) contributed data. Detailed time metrics were collected including last known well-to-door (LKWTD) time; last known well/onset-to-puncture (LKWTP) time; last known well-to-reperfusion (LKWR) time; door-to-puncture (DTP) time; and door-to-reperfusion (DTR) time. Main Outcomes and Measures: Change in healthy life-years measured as disability-adjusted life-years (DALYs). DALYs were calculated as the sum of years of life lost (YLL) owing to premature mortality and years of healthy life lost because of disability (YLD). Disability weights were assigned using the utility-weighted modified Rankin Scale. Age-specific life expectancies without stroke were calculated from 2017 US National Vital Statistics. Results: Among the 781 EVT-treated patients, 406 (52.0%) were early-treated (LKWTP ≤4 hours) and 375 (48.0%) were late-treated (LKWTP >4-12 hours). In early-treated patients, LKWTD was 188 minutes (interquartile range, 151.3-214.8 minutes) and DTP 105 minutes (interquartile range, 76-135 minutes). Among the 298 of 380 (78.4%) patients with substantial reperfusion, median DTR time was 145.0 minutes (interquartile range, 111.5-185.5 minutes). Care process delays were associated with worse clinical outcomes in LKW-to-intervention intervals in early-treated patients and in door-to-intervention intervals in early-treated and late-treated patients, and not associated with LKWTD intervals, eg, in early-treated patients, for each 10-minute delay, healthy life-years lost were DTP 1.8 months vs LKWTD 0.0 months; P < .001. Considering granular time increments, the amount of healthy life-time lost associated with each 1 second of delay was DTP 2.2 hours and DTR 2.4 hours. Conclusions and Relevance: In this study, care delays were associated with loss of healthy life-years in patients with acute ischemic stroke treated with EVT, particularly in the postarrival time period. The finding that every 1 second of delay was associated with loss of 2.2 hours of healthy life may encourage continuous quality improvement in door-to-treatment times.
  • Item
    Thumbnail Image
    Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.
    Seah, JCY ; Tang, CHM ; Buchlak, QD ; Holt, XG ; Wardman, JB ; Aimoldin, A ; Esmaili, N ; Ahmad, H ; Pham, H ; Lambert, JF ; Hachey, B ; Hogg, SJF ; Johnston, BP ; Bennett, C ; Oakden-Rayner, L ; Brotchie, P ; Jones, CM (Elsevier BV, 2021-08)
    BACKGROUND: Chest x-rays are widely used in clinical practice; however, interpretation can be hindered by human error and a lack of experienced thoracic radiologists. Deep learning has the potential to improve the accuracy of chest x-ray interpretation. We therefore aimed to assess the accuracy of radiologists with and without the assistance of a deep-learning model. METHODS: In this retrospective study, a deep-learning model was trained on 821 681 images (284 649 patients) from five data sets from Australia, Europe, and the USA. 2568 enriched chest x-ray cases from adult patients (≥16 years) who had at least one frontal chest x-ray were included in the test dataset; cases were representative of inpatient, outpatient, and emergency settings. 20 radiologists reviewed cases with and without the assistance of the deep-learning model with a 3-month washout period. We assessed the change in accuracy of chest x-ray interpretation across 127 clinical findings when the deep-learning model was used as a decision support by calculating area under the receiver operating characteristic curve (AUC) for each radiologist with and without the deep-learning model. We also compared AUCs for the model alone with those of unassisted radiologists. If the lower bound of the adjusted 95% CI of the difference in AUC between the model and the unassisted radiologists was more than -0·05, the model was considered to be non-inferior for that finding. If the lower bound exceeded 0, the model was considered to be superior. FINDINGS: Unassisted radiologists had a macroaveraged AUC of 0·713 (95% CI 0·645-0·785) across the 127 clinical findings, compared with 0·808 (0·763-0·839) when assisted by the model. The deep-learning model statistically significantly improved the classification accuracy of radiologists for 102 (80%) of 127 clinical findings, was statistically non-inferior for 19 (15%) findings, and no findings showed a decrease in accuracy when radiologists used the deep-learning model. Unassisted radiologists had a macroaveraged mean AUC of 0·713 (0·645-0·785) across all findings, compared with 0·957 (0·954-0·959) for the model alone. Model classification alone was significantly more accurate than unassisted radiologists for 117 (94%) of 124 clinical findings predicted by the model and was non-inferior to unassisted radiologists for all other clinical findings. INTERPRETATION: This study shows the potential of a comprehensive deep-learning model to improve chest x-ray interpretation across a large breadth of clinical practice. FUNDING: Annalise.ai.