Objective: To evaluate a clinically applicable split-bolus computed tomography urography (CTU) protocol combined with renal computed tomography angiography (CTA) by comparing image quality, radiation dose, and contrast medium volume with conventional multiphasic CTU. Methods: Patients with suspected urinary tract disease were prospectively enrolled and allocated to a modified split-bolus CTU plus renal CTA protocol (group A) or conventional CTU (group B). Group A underwent unenhanced CT, bolus-triggered renal arterial-phase CT, and a delayed comprehensive phase after a second contrast injection. Group B underwent conventional 4-phase CTU. A retrospective cohort of renal CTAs (group C) was included to compare the image quality of renal arteries. Objective CT attenuation, subjective image quality, dose-length product (DLP), effective dose (ED), and contrast medium volume were analyzed. Results: Among 153 prospective participants (group A, n=77; group B, n=76), visualization of the urinary collecting system did not differ significantly between groups A and B in CT attenuation or subjective scores (all P >0.05). Arterial attenuation and renal artery image quality were significantly higher in group A than in group B (all P <0.001), whereas subjective renal artery scores did not differ significantly between groups A and C ( P =0.324). Compared with group B, group A reduced DLP and ED by 29.9% and contrast medium volume by 14.4% (all P <0.001). Conclusions: The split-bolus CTU protocol, combined with renal CTA, may provide a feasible imaging option for selected patients requiring both urinary tract and renal arterial assessment, with reduced radiation exposure and contrast medium use, without compromising urinary tract image quality.
As the volume and complexity of trauma torso Computed Tomography (CT) scans continue to rise, the risk of diagnostic error in the emergency department (ED) remains a significant challenge. While perceptual misses are common, in the high acuity and time-pressured environment of the ED, many errors are driven by ingrained mental shortcuts that can lead to misinterpretation, ie, cognitive biases. This educational review presents 16 cases from a level 1 trauma and tertiary care institution, emphasizing diagnostic errors and near-misses encountered during the interpretation of emergency torso CT. Cases are organized by organ systems and highlight missed or misinterpreted findings involving the cardiothoracic, gastrointestinal, genitourinary, and musculoskeletal systems. Each case illustrates a relevant cognitive bias, including framing bias, satisfaction of search, anchoring bias, premature closure, availability bias, zebra retreat bias, and blind spot bias. The pathophysiology of these commonly overlooked injuries will be reviewed with a focus on cognitive biases that lead to their omission and practical mitigation strategies to avoid them. This review emphasizes the importance of reviewing all available images independently with a systematic and consistent search pattern and only then integrating clinical information as a potential strategy to reduce cognitive biases. By recognizing these patterns of error and implementing mitigation strategies, radiologists may improve diagnostic accuracy and clinical outcomes.
Objective: To evaluate the clinical utility of a “One-stop” spectral CT combined with perfusion CT scan for preoperative assessment of lymphovascular invasion (LVI) and perineural invasion (PNI) in gastric cancer (GC) and to investigate whether spectral CT parameters can serve as reliable surrogates for perfusion CT biomarkers in risk stratification. Methods: In this prospective study, 87 patients with histologically confirmed gastric adenocarcinoma underwent preoperative contrast-enhanced “One-stop” spectral CT combined with perfusion CT scan at our institution. Patients were stratified into LVI/PNI-positive (n=65) and LVI/PNI-negative (n=22) groups based on postoperative pathology. Spectral parameters—including iodine concentration (IC), effective atomic number (Zeff), and water concentration (WC)—were measured in arterial (AP) and venous (VP) phases. Perfusion parameters included blood volume (BV), blood flow (BF), mean transit time (MTT), permeability-surface area product (PS), and time to peak (Tmax). Intergroup comparisons, diagnostic performance evaluation, and correlation analyses between spectral and perfusion parameters were performed. Results: Significant differences were observed between LVI/PNI-positive and -negative groups for Zeff (in both AP and VP), IC (in VP), BV, and MTT (all P <0.05). In contrast, no significant differences were found for WC, BF, PS, or Tmax. A combined diagnostic model integrating spectral and perfusion parameters (AP+VP+P) achieved the highest performance, with an area under the curve (AUC) of 0.862 and an F 1 score of 0.892. Notably, VP-IC demonstrated a strong positive correlation with BV (Spearman ρ =0.751, P <0.001), underscoring the potential of spectral CT to reflect tumor perfusion noninvasively. Conclusion: Spectral CT parameters, particularly VP-IC, show a strong correlation with the perfusion biomarker BV and offer comparable diagnostic accuracy for detecting LVI/PNI in GC. This supports the role of spectral CT as a viable surrogate for perfusion CT. The integrated “One-stop” protocol, enabling simultaneous acquisition of both data sets in a single scan, provides a streamlined and clinically practical approach to preoperative risk stratification.
Magnetic resonance imaging (MRI) is integral to modern clinical practice owing to its superior soft-tissue contrast. However, the complexity of MRI physics predisposes examinations to numerous artifacts that may mimic pathology, obscure disease, or lead to misinterpretation in routine clinical settings. Failure to recognize these artifacts can result in diagnostic error, unnecessary additional imaging, or inappropriate clinical management. This practical review categorizes commonly encountered MRI artifacts by underlying mechanisms and highlights their typical imaging appearances across routine clinical applications. Emphasis is placed on differentiating artifacts from true pathology and on providing actionable strategies for artifact recognition, troubleshooting, and prevention during image acquisition and interpretation. By integrating imaging examples with clinically relevant explanations of the underlying physics, this review aims to equip practicing radiologists and trainees with a structured approach to confidently identify misleading findings and improve diagnostic accuracy in everyday practice.
