European Radiology最新文献

Importance: Misdiagnosis in breast imaging can have significant implications for patients, healthcare providers, and the healthcare system as a whole.

Observations: Some of the potential implications of misdiagnosis in breast imaging include delayed diagnosis or false reassurance, which can result in a delay in treatment and potentially a worse prognosis. Misdiagnosis can also lead to unnecessary procedures, which can cause physical discomfort, anxiety, and emotional distress for patients, as well as increased healthcare costs. All these events can erode patient trust in the healthcare system and in individual healthcare providers. This can have negative implications for patient compliance with screening and treatment recommendations, as well as overall health outcomes. Moreover, misdiagnosis can also result in legal consequences for healthcare providers, including medical malpractice lawsuits and disciplinary action by licensing boards.

Conclusion and relevance: To minimize the risk of misdiagnosis in breast imaging, it is important for healthcare providers to use appropriate imaging techniques and interpret images accurately and consistently. This requires ongoing training and education for radiologists and other healthcare providers, as well as collaboration and communication among healthcare providers to ensure that patients receive appropriate and timely care. If a misdiagnosis does occur, it is important for healthcare providers to communicate with patients and provide appropriate follow-up care to minimize the potential implications of the misdiagnosis. This may include repeat imaging, additional biopsies or other procedures, and referral to specialists for further evaluation and management.

Key points: Question What factors most contribute to and what implications stem from misdiagnosis in breast imaging? Findings Ongoing training and education for radiologists and other healthcare providers, as well as interdisciplinary collaboration and communication, is paramount. Clinical relevance Misdiagnosis in breast imaging can have significant implications for patients, healthcare providers, and the entire healthcare system.

Importance: Breast cancer is one of the leading causes of negligence claims in radiology. The objective of this document is to describe the specific main causes of errors in breast imaging and provide European Society of Breast Imaging (EUSOBI) recommendations to try to minimize these.

Observations: Technical failures represent 17% of all mammographic diagnostic negligence claims. Mammography quality control protocol and dedicated training for technologists and radiologists are essential. Lack of consideration of the clinical context is a second critical issue, as a clinical abnormality is found in 80% of malpractice claims. EUSOBI emphasizes the importance of communication and clinical examination before the diagnostic investigation. Detection errors or misapplications of the lexicon or Breast Imaging Reporting Data System (BI-RADS) score account for 5% of malpractice claims and should be reduced by limiting radiologists' distraction or fatigue, and being aware of satisfaction of search errors and the importance of a personal systematic review. Errors related to pathological concordance and MDT review can be limited by the use of markers after biopsy and the use of standardized reports, which can aid communication with other specialities. Finally, errors related to tumor or patient factors should be discussed, considering the use of contrast-enhanced mammography and magnetic resonance imaging.

Conclusion: Several factors are responsible for misdiagnosis in breast cancer, including errors in the practice of the technician and/or radiologist (technical failures, lack of consideration of the clinical context, incorrect application of the BI-RADS score, false reassurances), lack of communication with other specialists or with the patient, and the type of tumor and breast parenchyma.

Key points: Question What factors most contribute to and what implications stem from misdiagnosis in breast imaging? Findings Ongoing training and education for radiologists and other healthcare providers, as well as interdisciplinary collaboration and communication is paramount. Clinical relevance Misdiagnosis in breast imaging can have significant implications for patients, healthcare providers, and the entire healthcare system.

Background: Since radiology reports are primarily written for health professionals, patients may experience difficulties understanding jargon and terminology used, leading to anxiety and confusion.

Objectives: This review evaluates the impact of different radiology report formats on outcomes related to patient information processing, including perception, decision (behavioral intention), action (actual health behavior), and memory (recall of information).

Methods: PubMed, Web of Science, EMBASE, and PsycInfo were searched for relevant qualitative and quantitative articles describing or comparing ways of presenting diagnostic radiology reports to patients. Two reviewers independently screened for relevant articles and extracted data from those included. The quality of articles was assessed using the Mixed Methods Appraisal Tool.

Results: Eighteen studies, two qualitative and sixteen quantitative, were included. Sixteen studies compared multiple presentation formats, most frequently traditional unmodified reports (n = 15), or reports with anatomic illustrations (n = 8), lay summaries (n = 6) or glossaries (n = 6). Glossaries, illustrations, lay summaries, lay reports or lay conclusions all significantly improved participants' cognitive perception and perception of communication of radiology reports, compared to traditional reports. Furthermore, these formats increased affective perception (e.g., reduced anxiety and worry), although only significant for lay reports and conclusions.

Conclusion: Modifying traditional radiology reports with glossaries, illustrations or lay language enhances patient information processing.

Key points: Question Identifying the impact of different radiology report formats on outcomes related to patient information processing to enhance patient engagement through online access to radiology reports. Findings Lay language summaries, glossaries with patient-oriented definitions, and anatomic illustrations increase patients' satisfaction with and understanding of their radiology reports. Clinical relevance To increase patients' satisfaction, perceived usefulness and understanding with radiology reports, the use of lay language summaries, glossaries with patient-oriented definitions, and anatomic illustrations is recommended. These modifications decrease patients' unnecessary insecurity, confusion, anxiety and physician consultations after viewing reports.

Objectives: To develop a nomogram based on clinical features and spectral quantitative parameters to preoperatively predict the Lauren classification for locally advanced gastric cancer (LAGC).

Methods: Patients diagnosed with LAGC by postoperative pathology who underwent abdominal triple-phase enhanced spectral computed tomography (CT) were prospectively enrolled in this study between June 2023 and December 2023. All the patients were categorized into intestinal- and diffuse-type groups according to the Lauren classification. Traditional characteristics, including demographic information, serum tumor markers, gastroscopic pathology, and image semantic features, were collected. Spectral quantitative parameters, including iodine concentration (IC), effective atomic number (Zeff), and slope of the energy spectrum curve from 40 keV to 70 keV (λ), were measured three times for each patient by two blinded radiologists in arterial/venous/delayed phases (AP/VP/DP). Differences in traditional features and spectral quantitative parameters between the two groups were compared using univariable analysis. Independent predictors of the Lauren classification of LAGC were screened using multivariable logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminating capability. Ultimately, the nomogram, including clinical features and spectral CT quantitative parameters, was developed.

Results: Gender, nIC in AP (APnIC), and λ in DP (λd) were independent predictors for Lauren classification. The nomogram based on these indicators produced the best performance with an area under the curve of 0.841 (95% confidence interval: 0.749-0.932), specificity of 85.3%, accuracy of 76.4%, and sensitivity of 68.4%.

Conclusion: The nomogram based on clinical features and spectral CT quantitative parameters exhibits great potential in the preoperative and non-invasive assessment of Lauren classification for LAGC.

Key points: Question Can the proposed nomogram, integrating clinical features and spectral quantitative parameters, preoperatively predict the Lauren classification in locally advanced gastric cancer (LAGC)? Findings The nomogram, based on gender, arterial phase normalized iodine concentration, and slope of the energy spectrum curve in the delayed phase showed satisfactory predictive ability. Clinical relevance The established nomogram could contribute to guiding individualized treatment strategies and risk stratification in patients by predicting the Lauren classification for LAGC before surgery.

Objectives: This study aimed to develop nomograms for predicting post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC), using deep learning analysis of Gadoxetic acid-enhanced hepatobiliary (HBP) MRI.

Methods: This retrospective study analyzed patients who underwent gadoxetic acid-enhanced MRI and hepatectomy for HCC between 2016 and 2020 at two referral centers. Using a deep learning algorithm, volumes and signal intensities of whole non-tumor liver, expected remnant liver, and spleen were measured on HBP images. Two multivariable logistic regression models were formulated to predict PHLF, defined and graded by the International Study Group of Liver Surgery: one based on whole non-tumor liver measurements (whole liver model) and the other on expected remnant liver measurements (remnant liver model). The models were presented as nomograms and a web-based calculator. Discrimination performance was evaluated using the area under the receiver operating curve (AUC), with internal validation through 1000-fold bootstrapping.

Results: The study included 1760 patients (1395 male; mean age ± standard deviation, 60 ± 10 years), with 137 (7.8%) developing PHLF. Nomogram predictors included sex, gamma-glutamyl transpeptidase, prothrombin time international normalized ratio, platelets, extent of liver resection, and MRI variables derived from the liver volume, liver-to-spleen signal intensity ratio, and spleen volume. The whole liver and the remnant liver nomograms demonstrated strong predictive performance for PHLF (optimism-corrected AUC of 0.78 and 0.81, respectively) and symptomatic (grades B and C) PHLF (optimism-corrected AUC of 0.81 and 0.84, respectively).

Conclusion: Nomograms based on deep learning analysis of gadoxetic acid-enhanced HBP images accurately stratify the risk of PHLF.

Key points: Question Can PHLF be predicted by integrating clinical and MRI-derived volume and functional variables through deep learning analysis of gadoxetic acid-enhanced MRI? Findings Whole liver and remnant liver nomograms demonstrated strong predictive performance for PHLF with the optimism-corrected area under the curve of 0.78 and 0.81, respectively. Clinical relevance These nomograms can effectively stratify the risk of PHLF, providing a valuable tool for treatment decisions regarding hepatectomy for HCC.

Objective: To evaluate gadoxetic acid-enhanced (Gd-EOB-DTPA) MRI features of newly detected benign focal hepatic observations after chemotherapy.

Methods: In this retrospective single-center case-control study, we enrolled a cohort of 43 cancer patients with 93 newly detected benign focal hepatic observations after chemotherapy between January 2010 and December 2020. We evaluated several parameters including the delay of occurrence after chemotherapy, imaging features, and imaging follow-up. These parameters were compared with those observed in a control group comprising 34 patients with 93 hepatic metastases.

Results: For focal hepatic observations occurring at early-term follow-up (delay of occurrence after chemotherapy, median 3 months, range 1-6 months) with 22 patients encompassing 45 lesions, most lesions exhibited an ill-defined margin on HBP images (64.4%), negative on diffusion-weighted images (84.4%), mottled hypo-intensity on hepatobiliary phase images (88.9%), and undistorted vessels traversing the lesions (80.0%). Follow-up imaging indicated that 91.9% of these lesions resolved within 4-20 months. For focal hepatic observations occurring at late-term follow-up (delay of occurrence after chemotherapy, median 34 months, range 12-60 months) with 21 patients encompassing 48 lesions, which were diagnosed as focal nodular hyperplasia (FNH)-like lesions based on MRI features. A hepatobiliary ring enhancement was observed in 56.3% of lesions, and 66.7% of patients showed an increase in lesion size and/or number during follow-up imaging.

Conclusion: Focal hepatic observations occurring at early-term and late-term follow-ups after chemotherapy have distinctive imaging features at Gd-EOB-DTPA-MRI. Early-term focal observations tend to resolve spontaneously, whereas FNH-like lesions can increase in size and number during follow-up.

Key points: Question Focal benign liver lesions related to chemotherapy-induced hepatic injury were reported in recent years, often leading to confusion with metastasis and resulting in misdiagnosis. Findings Chemotherapy-induced focal hepatic observations identified during early- and late-term follow-up exhibit distinct imaging characteristics on Gd-EOB-DTPA-MRI and demonstrate varying temporal changes. Clinical relevance Chemotherapy-induced hepatic observations can be differentiated from metastasis based on Gd-EOB-DTPA MRI findings and their temporal changes. A deeper understanding of their findings can avoid unnecessary biopsies or surgical resections.