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Open research questions in Radiology practices and education

61 unresolved questions extracted from the limitations and future-work sections of 341 Radiology practices and education papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Legislators, mostly without medical training, enacting laws mandating certain medical procedures undercuts the principle that every patient is unique and requires an individualized approach to treatment.

    Modality matters · 2026 · DOI

  • The implementation of coordinated care requires new forms of control and data analysis. There is a need for robust privacy and security measures to protect patient data.

    The use of medical imaging and modern technologies in coordinated patient care · 2026 · DOI

  • Accurate diagnosis of LBP is challenging due to the complexity of the condition and the limited availability of diagnostic tools in resource-limited settings. The study highlights the challenge of developing effective and efficient diagnostic tools for LBP.

    Diagnostic accuracy of plain radiography compared with MRI in adults with non-traumatic low back pain · 2026 · DOI

  • The problem of hallucinations in large language models is a significant challenge. There is a need for further research into mitigating hallucinations in large language models.

    Patterns of Errors and Hallucinations Among ChatGPT, Perplexity, Qwen, and Copilot in Answering ACR DXIT Radiology Questions · 2026 · DOI

  • The study identifies a gap in evaluating the reference accuracy of large language models in radiology

    Reply: Evaluating the reference accuracy of large language models in radiology: a comparative study across subspecialties · 2026 · DOI

  • The study only included radiology residents and did not evaluate the performance of more experienced radiologists. The study used a limited number of scanners and imaging protocols.

    Commercial artificial intelligence–assisted performance and interpretation time of first-on-call radiology residents using computed tomography pulmonary angiography to detect pulmonary embolism: a multireader, multicenter study · 2026 · DOI

  • Further studies are needed to evaluate the effect of AI support on the performance of more experienced radiologists. The use of AI assistance in other medical imaging tasks should be investigated.

    Commercial artificial intelligence–assisted performance and interpretation time of first-on-call radiology residents using computed tomography pulmonary angiography to detect pulmonary embolism: a multireader, multicenter study · 2026 · DOI

  • The study identifies a challenge in the training of radiology residents in CT brain perfusion. The study highlights the need for dedicated teaching on stroke imaging for radiology residents. The study suggests that the lack of confidence among radiology residents in reporting CT brain perfusion may be a challenge in clinical practice.

    RSSA Conference: Radiology Residents Experience with CT Brain Perfusion: Regional Cross-sectional Study in Saudi Arabia · 2026 · DOI

  • Further research is needed to investigate the factors affecting residents' confidence in reporting CT brain perfusion. Studies should be conducted to evaluate the effectiveness of dedicated teaching on stroke imaging for radiology residents. Research should be done to develop training programs that address the needs of radiology residents in CT brain perfusion.

    RSSA Conference: Radiology Residents Experience with CT Brain Perfusion: Regional Cross-sectional Study in Saudi Arabia · 2026 · DOI

  • The study uses simulated audio recordings, which may not reflect real-world scenarios. The study is limited to a specific multilingual setting (Chinese-English).

    Automatic Speech Recognition and Large Language Models for Multilingual Pathology Report Generation: Proof-of-Concept Study · 2026 · DOI

  • Future research should investigate the use of Whisper-based ASR and LLMs in real-world scenarios. Future research should explore the application of this approach to other multilingual settings.

    Automatic Speech Recognition and Large Language Models for Multilingual Pathology Report Generation: Proof-of-Concept Study · 2026 · DOI

  • Medical interns may have limited experience in interpreting chest X-rays. Medical interns may have varying levels of competence in identifying critical findings on chest X-rays. The study's findings may be limited by the sample size and population.

    Medical Interns' Skill Levels in Emergency Chest X-ray Interpretation · 2026 · DOI

  • There is a gap in the literature regarding the evaluation of medical interns' proficiency in identifying critical findings on chest X-rays. The study aims to address this gap by evaluating the proficiency of medical interns in identifying critical findings on chest X-rays.

    Medical Interns' Skill Levels in Emergency Chest X-ray Interpretation · 2026 · DOI

  • Future studies could evaluate the performance of LLMs on other specialized medical board examinations. Future studies could also investigate the use of LLMs in medical education and practice.

    Performance of large language models on the radiation and cancer biology practice exam · 2026 · DOI

  • There is a need to evaluate the performance of LLMs on specialized medical board examinations. The study addresses this gap by evaluating the performance of three widely used LLMs on a domain-specific radiation and cancer biology examination.

    Performance of large language models on the radiation and cancer biology practice exam · 2026 · DOI

  • The study has a small sample size of 36 RT students. The study is limited to a single university hospital in Thailand. The VR module is not publicly accessible due to proprietary 3D assets and identifiable individuals.

    Virtual Reality–Based Training in Radiologic Technology for Contrast-Enhanced Computed Tomography Brain Imaging: Randomized Controlled Trial · 2026 · DOI

  • Future studies can evaluate the effectiveness of the RTVR framework in other radiologic technology procedures. Future studies can assess the long-term effects of VR-based training on declarative knowledge gain and technology acceptance.

    Virtual Reality–Based Training in Radiologic Technology for Contrast-Enhanced Computed Tomography Brain Imaging: Randomized Controlled Trial · 2026 · DOI

  • The current state of radiology departments often leads to diagnostic errors and radiologist frustration, impacting the quality of care and patient experience. There is a need for a multilevel approach to department design to optimize workflow and improve service quality.

    Optimizing Radiology Workflow: A Multilevel Approach From Department Design to Workstation Ergonomics · 2026 · DOI

  • The traditional mentoring approach often fails to meet the diverse and evolving needs of learners in radiology. There is a shortage of qualified faculty in radiology.

    Cascade mentoring: a proposal for transforming radiology education in line with the European training curriculum · 2026 · DOI

  • The study had a limited sample size of 478 patients. The study only included patients with febrile or respiratory symptoms, which may not be representative of all patients undergoing CXR. The study did not evaluate the performance of the VLMs in real-world clinical settings.

    Comparative evaluation of generative AI models for chest radiograph report generation in the emergency department · 2026 · DOI

  • Further evaluation of VLMs in real-world clinical settings is needed. The study suggests that future research should focus on improving the performance of VLMs in terms of diagnostic agreement and clinical acceptability. The study highlights the need for larger, more diverse datasets to train and evaluate VLMs.

    Comparative evaluation of generative AI models for chest radiograph report generation in the emergency department · 2026 · DOI

  • No study was prospective. Methodological details were typically not sufficiently reported to allow reproducibility. Reference standard construction was highly heterogeneous. External testing was performed in only 2 of 10 studies.

    AI-Based Post-processing for Artefact Mitigation in Radiography: A Systematic Review · 2026 · DOI

  • The current evidence base is insufficient to support clinical adoption. There is a need for more research on AI-based post-processing methods for artefact mitigation in radiography.

    AI-Based Post-processing for Artefact Mitigation in Radiography: A Systematic Review · 2026 · DOI

  • Evaluating the performance of MLLMs in other medical imaging tasks. Assessing the potential applications of MLLMs in routine clinical practice. Developing more accurate and reliable MLLMs for medical imaging tasks.

    Diagnostic Performance of Multimodal Large Language Models in Assigning Bone-RADS Categories on CT · 2026 · DOI

  • The lack of studies assessing the performance of MLLMs in Bone-RADS classification. The need to evaluate the accuracy of MLLMs in medical imaging tasks.

    Diagnostic Performance of Multimodal Large Language Models in Assigning Bone-RADS Categories on CT · 2026 · DOI

Most-cited papers in Radiology practices and education

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61 open questions have been extracted from the limitations and future-work passages of 341 Radiology practices and education papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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