Errors In Image Interpretation Research Articles

Tips and tricks for a correct interpretation of contrast-enhanced ultrasound.

Although contrast-enhanced ultrasound (CEUS) is a widespread and easily manageable technique, image interpretation errors can occur due to the operator's inexperience and/or lack of knowledge of the frequent pitfalls, which may cause uncertain diagnosis and misdiagnosis. Indeed, knowledge of the basic physical and technical principles of ultrasound is needed both to understand sonographic image findings and to evaluate the potential and limits of the method. Like the B-mode ultrasound, the quality of the CEUS examination is also subject not only to the adequate manual skill of the operator but also to his/her deep knowledge of the technique which improves the quality of the image helping avoid misleading artifacts. In this review, the main parameters influencing a CEUS examination will be described by taking into account the most common errors and pitfalls and their possible solutions.

Inclusion of a Visual Aid Improves Surgeon and Trainee Accuracy when Evaluating Images for Ankle Syndesmosis Repair

Category:Trauma; Ankle;OtherIntroduction/Purpose:Malreduction in ankle syndesmosis repair is associated with post-operative pain, instability, and revision. Although multiple surgical techniques are designed to minimize malreduction, little is understood regarding the multi-factorial sources of error these techniques aim to address. For example, image interpretation errors may be particularly problematic, as previous work indicates identifying subtle fibular displacements from imaging is challenging for experienced orthopaedic trauma surgeons. In this context, this study evaluates whether surgical experience and/or inclusion of a visual aid improves surgeon accuracy during an image interpretation task. The task originates from the center-center technique, which is designed to minimize syndesmosis malreduction by drilling through the aligned centers of the tibia and fibula on an internally-rotated, lateral ankle x-ray.Methods:Twenty-eight individuals participated in this IRB-approved study (10 orthopaedic surgery attendings, 8 orthopaedic surgery residents, 10 medical students). Each evaluated 90 lateral ankle images arranged in two equal sets. In each set, the fibula was displaced from perfectly centered (-40% posterior to +40% anterior in 10% increments; each increment repeated 5 times). The two sets were identical, except one was augmented with a visual aid (or crosshair) marking the center of the tibia. Image and set order were randomized to control for learning effects. For each image, participants classified the fibula as 'centered' or 'non- centered' while wearing eye-tracking glasses. The glasses recorded two physiological measures of cognitive burden: blinks per image and image interpretation time. Statistical analyses tested the hypotheses that surgical experience and addition of a visual aid improved interpretation accuracy and decreased cognitive burden. Statistical significance (p <= 0.05) was evaluated using ANOVA followed by paired t-tests.Results:All participants accurately identified images with large fibular displacements (>20%) and perfectly centered (0%) images; however, interpretation accuracy at small displacements (10%) approximated random chance (Fig. 1A). Inclusion of a visual aid significantly improved image interpretation accuracy for both the full image set (p = 0.015, Fig. 1B) and images with small displacements (p = 0.025, Fig. 1A 10% and 20%). Although surgical experience was not a significant predictor of interpretation accuracy, surgical experience did significantly influence physiological measures of cognitive burden. Interestingly, inclusion of a visual aid slightly increased cognitive burden as measured by blinks per image for trainees, but significantly decreased this metric for attendings (p = 0.014, Fig. 1C). Compared to attendings, time per image was significantly increased for residents (p = 0.007), but not medical students (Fig. 1D).Conclusion:This study demonstrates that a visual aid can improve image interpretation accuracy for both experienced surgeons and trainees. Interestingly, the inclusion of the visual aid decreased the physiologically measured cognitive burden of attendings, but not trainees. This suggests that additional visual information displayed on an x-ray image may be processed and used differently by experienced versus inexperienced surgeons. Thus, this study provides foundational evidence that augmenting images can improve surgical accuracy and motivates future work to characterize how image augmentation influences clinical and educational outcomes.

Describing the learning curve of novices for the diagnosis of paediatric distal forearm fractures using point-of-care ultrasound.

The learning curve of nurse practitioners (NPs) to accurately diagnose paediatric distal forearm fractures using point-of-care ultrasound (POCUS) was investigated. Each NP's learning curve was calculated as cumulative diagnostic accuracy against a number of scans performed. The curve's plateau represented the attainment of competency. Secondary outcomes were the comparisons before and after this cut-off of diagnostic accuracy, classification of diagnostic errors, pain scores, duration and preference. Five NPs performed 201 POCUS studies with diagnostic accuracy plateauing at 90%, providing a 'cut-off' point at scan 15. Accuracy of POCUS scanning before and after the fifteenth scan was 81% (95% CI 70%-89%) and 90% (95% CI 84%-94%), respectively, demonstrating 9% improvement (P = 0.07). There was a 10% reduction in image interpretation errors. After fifteen scans, POCUS became faster (mean difference (MD) 2.6 min [95% CI 2.0-3.3], P < 0.001), less painful (MD 0.61 points FPSR scale [95% CI 0.04-1.18], P = 0.04) and more preferred by NPs (63% vs 77%, P = 0.03). The learning curve of POCUS-novice NPs independently scanning paediatric distal forearm injuries plateaued with mean diagnostic accuracy of 90% after 15 scans, suggesting competency was attained at this cut-off, supported by higher accuracy, being faster, less painful and more preferred by NPs. Future training packages in forearm POCUS should further address image interpretation and provide ongoing expert feedback. The findings from this study suggest that competency in paediatric distal forearm POCUS can be attained by novices after a short training course and approximately 15 scans.

Pediatric Hepatoblastoma, Hepatocellular Carcinoma, and Other Hepatic Neoplasms: Consensus Imaging Recommendations from American College of Radiology Pediatric Liver Reporting and Data System (LI-RADS) Working Group.

Appropriate imaging is imperative in evaluating children with a primary hepatic malignancy such as hepatoblastoma or hepatocellular carcinoma. For use in the adult patient population, the American College of Radiology created the Liver Imaging Reporting and Data System (LI-RADS) to provide consistent terminology and to improve imaging interpretation. At present, no similar consensus exists to guide imaging and interpretation of pediatric patients at risk for developing a liver neoplasm or how best to evaluate a pediatric patient with a known liver neoplasm. Therefore, a new Pediatric Working Group within American College of Radiology LI-RADS was created to provide consensus for imaging recommendations and interpretation of pediatric liver neoplasms. The article was drafted based on the most up-to-date existing information as interpreted by imaging experts comprising the Pediatric LI-RADS Working Group. Guidance is provided regarding appropriate imaging modalities and protocols, as well as imaging interpretation and reporting, with the goals to improve imaging quality, to decrease image interpretation errors, to enhance communication with referrers, and to advance patient care. An expanded version of this document that includes broader background information on pediatric hepatocellular carcinoma and rationale for recommendations can be found in Appendix E1 (online).

Grayscale histogram analysis to study the echogenicity and echotexture of the walls of the common carotid arteries of horses and mules

ABSTRACT: Visual inspection of ultrasound examination for assessment of echogenicity and echotexture of blood vessel tissues is a technique routinely used in medical practice in humans. However, simple visual inspection can lead to poor quality diagnoses and errors. The use of grayscale histogram (GSH) analysis has proved to be an efficient technique to quantify the region of interest, allowing minimization of image interpretation errors. This study aimed to evaluate and compare the echogenicity and echotexture of the walls of the common carotid arteries of healthy female horses and mules using the GSH technique and correlate them with age, body mass, and vessel diameters. B-mode ultrasound examinations were performed in the left and right common carotid arteries in three regions (cranial, middle, and caudal) in 11 horses and 11 healthy mules. The GSH of the animals showed heterogeneous walls, but did not differentiate statistically between female horses and mules. The Mean variable of the middle right, middle left and caudal right sides showed differences, more significant in the mules. On the middle right side, the Min variable was different, higher in the mules. On the middle and caudal left side, the variables Max and Mode showed higher values in the mules. For the mules, the age factor presented negative correlation with the Mean, Mode,, Mode(Count), and Mode(Count)/Count(%) variables, and the body mass factor presented negative correlation with the Mode, Mean and Max variables. For the female horses, the body mass factor showed positive correlation with the Mean and Mode variables. Echogenicity of the carotid artery walls differed between female horses and mules, whereas echotexture was heterogeneous and statistically similar among the animals. The age and body mass factors inversely influenced the echogenicity of the mules, but were not significant in the female horses, in which only the body mass factor positively influenced echogenicity.

Errores comunes en la interpretación oncológica

Errors in image interpretation are inevitable and generally multifactorial. They can be due to the radiologist's failure to interpret the findings correctly (including cognitive causes, perceptual errors, or ambiguity in reporting) or to problems related with the system (technical problems in image acquisition, incorrect clinical information, excessive workload, or inadequate working conditions). It is the radiologist's responsibility to know why errors occur and how to detect them to prevent them from occurring again. This article focuses on the problem of errors in diagnosing oncologic patients, both at the time of diagnosis and during follow-up as well as in the study of the response to treatment with new molecular therapies. To reduce possible errors, radiologists should ensure a systematic reading and an assessment of the oncologic response over time in the clinical context of the patient; they also need to have and apply knowledge of the new specific criteria for the response of each tumor type in the management of the patient.

A sparse representation and dictionary learning based algorithm for image restoration in the presence of Rician noise.

Rician noise removal for Magnetic Resonance Imaging (MRI) is very important because the MRI has been widely used in various clinical applications and the associated Rician noise deteriorates the image quality and causes errors in interpreting the images. Great efforts have recently been devoted to develop the corresponding noise-removal algorithms, particularly the development based on the newly-established Total Variation (TV) theorem. However, all the TV-based algorithms depend mainly on the gradient information and have been shown to produce the so called "blocky" artifact, which also deteriorates the image quality and causes image interpretation errors. In order to avoid producing the artifact, this paper presents a new de-noising model based on sparse representation and dictionary learning. The Split Bregman Iteration strategy is employed to implement the model. Furthermore, an appropriate dictionary is designed by the use of the Kernel Singular Value Decomposition method, resulting in a new Rician noise removal algorithm. Compared with other de-noising algorithms, the presented new algorithm can achieve superior performance, in terms of quantitative measures of the Structural Similarity Index and Peak Signal to Noise Ratio, by a series of experiments using different images in the presence of Rician noise.

Clinical Significance of US Artifacts.

Artifacts are frequently encountered at clinical US, and while some are unwanted, others may reveal valuable information related to the structure and composition of the underlying tissue. They are essential in making ultrasonography (US) a clinically useful imaging modality but also can lead to errors in image interpretation and can obscure diagnoses. Many of these artifacts can be understood as deviations from the assumptions made in generating the image. Therefore, understanding the physical basis of US image formation is critical to understanding US artifacts and thus proper image interpretation. This review is limited to gray-scale artifacts and is organized into discussions of beam- and resolution-related, location-related (ie, path and speed), and attenuation-related artifacts. Specifically, artifacts discussed include those related to physical mechanisms of spatial resolution, speckle, secondary lobes, reflection and reverberation, refraction, speed of sound, and attenuation. The underlying physical mechanisms and appearances are discussed, followed by real-world strategies to mitigate or accentuate these artifacts, depending on the clinical application. Relatively new US modes, such as spatial compounding, tissue harmonic imaging, and speckle reduction imaging, are now often standard in many imaging protocols; the effects of these modes on US artifacts are discussed. The ability of a radiologist to understand the fundamental physics of ultrasound, recognize common US artifacts, and provide recommendations for altering the imaging technique is essential for proper image interpretation, troubleshooting, and utilization of the full potential of this modality. ©RSNA, 2017.

Variações da reflectância e dos índices de vegetação em função dos parâmetros da modelagem topográfica no Parque Estadual do Turvo, Rio Grande do Sul, Brasil

Remote sensing techniques have been widely used in forestry studies as they allow evaluation and monitoring of large forested areas. The Parque Estadual do Turvo (pet) (17 491 ha) is the largest remaining tract of well-preserved subtropical deciduous forest in Southern Brazil, it constitutes the northern-most portion of the Misiones forest of Argentina (10 000 km2). The area is of great environmental importance and is suitable for conducting remote sensing studies using high or even coarse-to-moderate spatial resolution data and related vegetation indices. Both, reflectance values and vegetation indices are affected by external factors that modify the spectral response of surface elements. Among the factors that can induce errors in image interpretation are topographic effects that add spectral variability to satellite products. In addition, previous studies in subtropical forests have shown that the geometry of data acquisition also affects significantly the estimates of vegetation parameters derived from images acquired at off-nadir viewing or by sensors with large field-of-view (FOV).This study aimed to evaluate the magnitude of variations in bidirectional reflectance values and in vegetation indices derived from those, as a function of local topography, using high spatial resolution data acquired by the RapidEye satellite constellation.The method included the use of a digital elevation model (dem) from the Advanced Space-borne Thermal Emission and Reflection Radiometer – Global Digital Elevation Map version 2 (aster gdem v2) and two RapidEye scenes. From the dem, topographical parameters including slope aspect (eight classes), elevation (nine classes with 120-m spacing interval) and shaded relief (shaded, intermediate and sunlit surfaces) were derived. These data provide information on areas with or without direct exposure to solar radiation, depending on topographic features. RapidEye data were acquired on June 28, 2012 and October 17, 2012, corresponding to dates when the forest shows low or high leaf area index (lai), respectively. Both scenes were acquired with a view angle close to nadir. Solar elevation angles for the June and October images were 37.93° and 71.25°, respectively. The RapidEye data were corrected for atmospheric effects using the Fast Line-of-sight Atmospheric Analysis of Hypercubes (flaash®). The next step was to perform topographic modeling in order to extract slope, aspect and elevation data. From the topographic variables and the RapidEye metadata, shaded relief was calculated for both scenes. After segmenting the scenes based on the topographic variables, we evaluated the spectral reflectance and vegetation indices, as measured by RapidEye, as a function of topographic parameters. For this purpose, we randomly sampled 1000 pixels from each topographic class. The Normalized Difference Vegetation Index (ndvi) and Enhanced Vegetation Index (evi) were calculated from the RapidEye data. The samples were averaged and analyzed using graphics and descriptive statistics. Select transects were analyzed in more detail to evaluate the effects of local topographic parameters on the remote sensing products. In addition, we conducted forest surveys in 14 plots (20x50m) to produce a floristic-structural characterization of the deciduous forest.The field inventories identified a total of 74 plant species (in 31 families) distributed in three strata and showed the presence of discontinuities within the forest. The results showed that, in addition to seasonal phenological variations, local illumination conditions caused by the relief in the pet contributed to explain the forest spectral response. The topographic variable that most importantly affected the pet spectral response, as measured by RapidEye, was slope aspect. Despite being affected by varying illumination conditions in the two dates, the reflectance and vegetation indices of the June image were most impacted by the shaded relief caused by the low solar elevation and large amount of shadows in the scene. The illumination effects were compounded by the seasonal leaf shedding in the deciduous forests, especially in the upper canopy layer. The winter time (June) scene showed more shaded relief and lower lai values. In the October scene the shade fraction was substantially reduced and leaf shedding reduced the forest canopy anisotropy. A per band analysis showed that the red and near infrared bands were the ones with the highest dependence on aspect and shaded relief. Increases in elevation caused a positive change in near infrared reflectance and a lower reflectance in the visible bands. The ndvi showed lower dependence on topographical conditions than the evi. The evi showed higher sensitivity to illumination conditions, shade and seasonal lai variations.We concluded that the analysis of remote sensing data (reflectance values or vegetation indices such as ndvi and evi) should take into account local topographic effects. In general, the spectral anisotropy in the June scene was higher than in the October scene due the combined effect of deciduousness (leaf shedding), the lower solar elevation and larger amount of shadows.

Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.

Lung cancer is the leading cause of cancer-related deaths in the world, and its main manifestation is pulmonary nodules. Detection and classification of pulmonary nodules are challenging tasks that must be done by qualified specialists, but image interpretation errors make those tasks difficult. In order to aid radiologists on those hard tasks, it is important to integrate the computer-based tools with the lesion detection, pathology diagnosis, and image interpretation processes. However, computer-aided diagnosis research faces the problem of not having enough shared medical reference data for the development, testing, and evaluation of computational methods for diagnosis. In order to minimize this problem, this paper presents a public nonrelational document-oriented cloud-based database of pulmonary nodules characterized by 3D texture attributes, identified by experienced radiologists and classified in nine different subjective characteristics by the same specialists. Our goal with the development of this database is to improve computer-aided lung cancer diagnosis and pulmonary nodule detection and classification research through the deployment of this database in a cloud Database as a Service framework. Pulmonary nodule data was provided by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), image descriptors were acquired by a volumetric texture analysis, and database schema was developed using a document-oriented Not only Structured Query Language (NoSQL) approach. The proposed database is now with 379 exams, 838 nodules, and 8237 images, 4029 of them are CT scans and 4208 manually segmented nodules, and it is allocated in a MongoDB instance on a cloud infrastructure.

Understanding and Confronting Our Mistakes: The Epidemiology of Error in Radiology and Strategies for Error Reduction.

Arriving at a medical diagnosis is a highly complex process that is extremely error prone. Missed or delayed diagnoses often lead to patient harm and missed opportunities for treatment. Since medical imaging is a major contributor to the overall diagnostic process, it is also a major potential source of diagnostic error. Although some diagnoses may be missed because of the technical or physical limitations of the imaging modality, including image resolution, intrinsic or extrinsic contrast, and signal-to-noise ratio, most missed radiologic diagnoses are attributable to image interpretation errors by radiologists. Radiologic interpretation cannot be mechanized or automated; it is a human enterprise based on complex psychophysiologic and cognitive processes and is itself subject to a wide variety of error types, including perceptual errors (those in which an important abnormality is simply not seen on the images) and cognitive errors (those in which the abnormality is visually detected but the meaning or importance of the finding is not correctly understood or appreciated). The overall prevalence of radiologists' errors in practice does not appear to have changed since it was first estimated in the 1960s. The authors review the epidemiology of errors in diagnostic radiology, including a recently proposed taxonomy of radiologists' errors, as well as research findings, in an attempt to elucidate possible underlying causes of these errors. The authors also propose strategies for error reduction in radiology. On the basis of current understanding, specific suggestions are offered as to how radiologists can improve their performance in practice.

Reducing Interruptions in the Reading Room: Standardized CT/MRI Contrast Orders

THE PROBLEM One major source of interruptions in workflow that we identified in our academic practice was phone calls to the radiology reading room from technologists and nursing staff members requesting written prescription orders for oral and intravenous contrast and prescription of protocols to be entered into our computerized protocoling system. Technologists would routinely call for protocols and nurses would call for contrast media, with potentially a minimum of two phone calls per patient examination. Although prescribing imaging protocols and contrast orders are essential tasks for quality patient care, this pattern of workflow in our department was problematic, inevitability leading to delays and interruptions of patient care at multiple levels. For patients, wait times were potentially prolonged because orders were not in place in advance of patients’ arrival to the department. For technologists and nurses, the time spent trying to contact physicians negatively affected throughput and could potentially lead to errors due to interruptions in their workflow. For radiologists, interruptions in the reading room lead to prolonged turnaround times, foreshortened consultations with referring clinicians and readout sessions with trainees and potential errors in image interpretation or reports. Error rates in interpretations rendered by radiologists range from

Reducing image interpretation errors – Do communication strategies undermine this?

IntroductionErrors in the interpretation of diagnostic images in the emergency department are a persistent problem internationally. To address this issue, a number of risk reduction strategies have been suggested but only radiographer abnormality detection schemes (RADS) have been widely implemented in the UK. This study considers the variation in RADS operation and communication in light of technological advances and changes in service operation. MethodsA postal survey of all NHS hospitals operating either an Emergency Department or Minor Injury Unit and a diagnostic imaging (radiology) department (n = 510) was undertaken between July and August 2011. The questionnaire was designed to elicit information on emergency service provision and details of RADS. Results325 questionnaires were returned (n = 325/510; 63.7%). The majority of sites (n = 288/325; 88.6%) operated a RADS with the majority (n = 227/288; 78.8%) employing a visual ‘flagging’ system as the only method of communication although symbols used were inconsistent and contradictory across sites. 61 sites communicated radiographer findings through a written proforma (paper or electronic) but this was run in conjunction with a flagging system at 50 sites. The majority of sites did not have guidance on the scope or operation of the ‘flagging’ or written communication system in use. ConclusionsRADS is an established clinical intervention to reduce errors in diagnostic image interpretation within the emergency setting. The lack of standardisation in communication processes and practices alongside the rapid adoption of technology has increased the potential for error and miscommunication.

Avoiding never events: Improving nasogastric intubation practice and standards

To identify and rectify weaknesses in nasogastric (NG) intubation practice in the North Bristol NHS Trust that resulted in the occurrence of a National patient Safety Agency defined "never event". Root-cause analysis identified that a change in culture was required. Recommendations divided into four categories: documentation, intubation, interpretation training, and radiology. A 6 month prospective audit covering all aspects of NG intubation practice preceded implementation of the recommendations. All patients whose tubes were mis-sited formed the cohort of the study. A re-audit was undertaken 12 months after the implementation of the recommended changes. Re-audit suggested significant improvements had occurred in all categories, particularly junior doctor check image interpretation errors, which in the study group were reduced from seven to one, and documentation, which has so far improved by 22%. Protocols and guidelines associated with NG tube check imaging have now been developed for radiologists and radiographers with check imaging and image interpretation being made a priority and respiratory tract intubation treated as an emergency. The service is still not perfect, but there is a focal awareness of patient safety associated with intubation practice, and image interpretation by junior doctors significantly improved with the introduction of the e-learning package. However, it is considered that the responsibility for developing safe practice with respect to NG tube check image interpretation ultimately lies with the department of radiology, which should take the lead on reducing the risk of never events being caused by the misinterpretation of these images.

Understanding errors in diagnostic radiology: proposal of a classification scheme and application to emergency radiology

Errors in image interpretation are a common problem in diagnostic radiology. Although many published articles provide trainees with the means to correctly interpret imaging studies, they do not provide a framework for understanding why and how errors occur. In this article, we propose a classification system that allows categorization of errors, which we hope can serve as a basis for peer review, self-education, and quality improvement programs. Our scheme incorporates elements of a classification system proposed by previous authors but also includes novel categories. In this article, we show the usefulness of our scheme by applying it to a specific, and particularly problematic, diagnosis in emergency radiology, namely that of dural sinus thrombosis.

Nonrigid Versus Rigid Registration of Thoracic 18F-FDG PET and CT in Patients with Lung Cancer: An Intraindividual Comparison of Different Breathing Maneuvers

In lung cancer, (18)F-FDG PET, CT, and (18)F-FDG PET/CT are used for noninvasive staging and therapy planning. Even with improved image registration techniques-especially in the modern hybrid PET/CT scanners-inaccuracies in the fusion process may occur, leading to errors in image interpretation. The aim of this study was to investigate by an intraindividual analysis whether, in comparison with a rigid algorithm, a nonrigid registration algorithm improves the quality of fusion between (18)F-FDG PET and CT. Sixteen patients with histologically proven non-small cell lung cancer underwent a thoracic (18)F-FDG PET acquisition in radiotherapy treatment position and 3 CT acquisitions (expiration, inspiration, and mid breath-hold) on the same day. All scans were registered with rigid and nonrigid procedures, resulting in 6 fused datasets: rigid inspiration, rigid expiration, rigid mid breath-hold, nonrigid inspiration, nonrigid expiration, and nonrigid mid breath-hold. The quality of alignment was assessed by 3 experienced readers at 8 anatomic landmarks: lung apices, aortic arch, heart, spine, sternum, carina, diaphragm, and tumor using an alignment score ranging from 1 (no alignment) to 5 (exact alignment). Nonrigid PET/CT showed better alignment than rigid PET/CT (3.5 +/- 0.7 vs. 3.3 +/- 0.7, P < 0.001). Regarding the breathing maneuver, no difference between nonrigid mid breath-hold and rigid mid breath-hold was observed. In contrast, the alignment quality significantly improved from rigid expiration to nonrigid expiration (3.4 +/- 0.7 vs. 3.6 +/- 0.7, P < 0.001) and from rigid inspiration to nonrigid inspiration (3.1 +/- 0.7 vs. 3.3 +/- 0.7, P < 0.001). With regard to individual landmarks, an improvement in fusion quality through the use of nonrigid registration was obvious at the lung apices, carina, and aortic arch. The alignment quality of thoracic (18)F-FDG PET/CT exhibits a marked dependence on the breathing maneuver performed during the CT acquisition, as demonstrated in an intraindividual comparison. Nonrigid registration is a significant improvement over rigid registration if the CT is performed during full inspiration or full expiration. The best fusion results are obtained with the CT performed at mid breath-hold using rigid registration, without an improvement using nonrigid algorithms.

Accuracy of real-time ultrasound measurements of total tissue, fat, and muscle depths at different measuring sites in lamb1

Accuracy of live ultrasound measurements to evaluate the total tissue depth (GR), as well as fat and LM depths at different scanning sites, was studied in 96 purebred Suffolk and Dorset lambs of both sexes slaughtered between 36 and 54 kg of BW. Before slaughter, 7 real-time ultrasound measurements were taken on lambs: fat and LM depths between the 12th and 13th ribs (transverse) and between the 3rd and 4th lumbar vertebrae (transverse and longitudinal), and GR. After slaughter, the measurements equivalent to ultrasound measurements were taken on digitized images of the cuts on the left half carcass of each lamb. Ultrasound GR and fat depth measurements were closely correlated with the corresponding carcass measurements (0.76 < or = r < or = 0.81). Ultrasound GR measurement exhibited a large error of central tendency, but the level of error due to the disturbance (ED) was comparable with fat depth measurements (ED = 8.5%; residual SD = 2.24 mm; CV of residuals = 9.5%). Ultrasound fat depth measurements were more accurate between the 12th and 13th ribs (error due to regression = 1.20; ED = 0.82) than between the 3rd and 4th lumbar vertebrae (error due to regression = 5.58 and 5.4; ED = 1.10 and 0.93, transverse and longitudinal, respectively), mainly due to image interpretation errors in the lumbar region. Measurements of LM depth demonstrated low variability in the population under study (SD = 2.6 mm), and these ultrasound measurements showed low correlation with the corresponding carcass measurements (0.34 < or = r < or = 0.43). The results of this study demonstrated that ultrasound measurements were more accurate for evaluating fat depth and the GR measurements than for estimating LM depths. Ultrasound GR measurement is a promising measurement, especially where carcass grading systems are based on this carcass measurement.

Pitfalls in Renal Mass Evaluation and How to Avoid Them

Characterization of renal masses with computed tomography (CT) and magnetic resonance (MR) imaging is usually clear-cut and accurate. However, potential pitfalls exist in diagnosis of renal masses, and it is necessary to understand these pitfalls to avoid misdiagnosis and possibly unnecessary surgery. Although some of the pitfalls are related to technical factors of the CT and MR imaging equipment, others are related to errors in image interpretation. To maximize detection and characterization of renal masses, the study should include images obtained before and after administration of intravenous contrast material, including images obtained during the nephrographic phase of enhancement. One should be aware of the potential unreliability of absolute Hounsfield unit measurements and of the existence of possible CT pseudoenhancement. When CT results are indeterminate, MR imaging may be helpful in demonstrating enhancement in renal masses. Before diagnosing a renal mass as a malignant neoplasm or suggesting surgery for a renal mass, one should consider alternative benign diagnoses; when appropriate, previous images or a supporting history should be obtained.

Turf wars in radiology: The quality of interpretations of imaging studies by nonradiologist physicians—a patient safety issue?

Previous publications have demonstrated that in side-by-side testing, radiologists clearly outperform nonradiologist physicians at interpreting plain radiographs. Other articles, mostly in the nonradiologic literature, have shown that in actual practice settings, nonradiologist physicians make frequent errors in image interpretation. On the other hand, several other studies have concluded that such errors are infrequent and generally do not affect patient outcomes. However, most of the latter studies have had methodologic flaws. Radiologists need to be aware of the evidence that exists in the medical literature on errors made by nonradiologists in image interpretation and to bring it to the attention of hospital authorities or medical policy-making groups that are charged with improving patient safety.

Magnetic resonance imaging of soft tissue expanders used in the management of musculoskeletal sarcomas.

A soft tissue expander is surgically inserted into the body to displace radiosensitive organs from the treatment field in a small number of patients receiving radiotherapy for musculoskeletal sarcoma. MRI is routinely used to monitor the response to the radiotherapy, local recurrence and complications of treatment. This study retrospectively reviews MRI of soft tissue expanders in seven patients with musculoskeletal sarcomas; six arising in the pelvis and one in the retroperitoneum. In the absence of an appropriate clinical history, the soft tissue expander may be mistaken for a pathological fluid collection such as abscess, post-operative seroma or even recurrent tumour. MRI of the soft tissue expanders and potential errors in image interpretation are illustrated.