Use of a Dedicated Server to Perform Coronal and Sagittal Reformations in Trauma Examinations

The purpose of this study was to evaluate the impact of implementing an automated process for generating coronal and sagittal reformatted images on radiologist workflow. When performing trauma-related CT examinations of the cervical, thoracic, and lumbar spine at our institution, technologists manually generate coronal and sagittal reconstructions at the scanner console and send these images to a picture archiving and communication system (PACS) for interpretation by radiologists and clinical viewing. Although certain PACS, thin-client three-dimensional systems, and CT scanners are capable of automatically generating reconstructed or reformatted images, the systems at our institution do not support this functionality. We have recently integrated a dedicated server that is capable of automatically generating multiplanar reformatted (MPR) images from source thin-section axial images and sending these images to PACS without requiring technologist input. This dedicated server was used to generate coronal and sagittal MPRs for trauma-related spine studies in parallel with technologist-generated coronal and sagittal reconstructions. When comparing the two methods, using the dedicated server to automatically generate reformations resulted in substantial time savings for the radiologist compared to technologist-generated reconstructions. Additionally, a survey of interpreting radiologists indicated that a significant majority preferred to view the automatically generated MPRs on PACS compared to the thin-client system, considered the image quality to be good or excellent, and believed that viewing MPRs increased diagnostic accuracy and confidence. It is expected that this automated process will significantly improve radiologist workflow with respect to image interpretation time and report turnaround time.     

Analyzing PACS Usage Patterns by Means of Process Mining: Steps Toward a More Detailed Workflow Analysis in Radiology

In this paper, statistical analysis and techniques from process mining are employed to analyze interaction patterns originating from radiologists reading medical images in a picture archiving and communication system (PACS). Event logs from 1 week of data, corresponding to 567 cases of single-view chest radiographs read by 14 radiologists, were analyzed. Statistical analysis showed that the numbers of commands and command types used by the radiologists per case only have a slightly positive correlation with the time to read a case (0.31 and 0.55, respectively). Further, one way ANOVA showed that the factors time of day, radiologist and specialty were significant for the number of commands per case, whereas radiologist was also significant for the number of command types, but with no significance of any of the factors on time to read. Applying process mining to the event logs of all users showed that a seemingly “simple” examination (single-view chest radiographs) can be associated with a highly complex interaction process. However, repeating the process discovery on each individual radiologist revealed that the initially discovered complex interaction process consists of one group of radiologists with individually well-structured interaction processes and a second smaller group of users with progressively more complex usage patterns. Future research will focus on metrics to describe derived interaction processes in order to investigate if one set of interaction patterns can be considered as more efficient than another set when reading radiological images in a PACS.     

The iPad Tablet Computer for Mobile On-Call Radiology Diagnosis? Auditing Discrepancy in CT and MRI Reporting

Tablet computers such as the iPad, which have a large format, improved graphic display resolution and a touch screen interface, may have an advantage compared to existing mobile devices such as smartphones and laptops for viewing radiological images. We assessed their potential for emergency radiology teleconsultation by reviewing multi-image CT and MRI studies on iPad tablet computers compared to Picture Archival and Communication Systems (PACS) workstations. Annonymised DICOM images of 79 CT and nine MRI studies comprising a range of common on-call conditions, reported on full-featured diagnostic PACS workstation by one Reporting Radiologist, were transferred from PACS to three iPad tablet computers running OsiriX HD v 2.02 DICOM software and viewed independently by three reviewing radiologists. Structured documentation was made of major findings (primary diagnosis or other clinically important findings), minor findings (incidental findings), and user feedback. Two hundred and sixty four readings (88 studies read by three reviewing radiologists) were compared, with 3.4 % (nine of 264) major discrepancies and 5.6 % (15 of 264) minor discrepancies. All reviewing radiologists reported favorable user experience but noted issues with software stability and limitations of image manipulation tools. Our results suggest that emergency conditions commonly encountered on CT and MRI can be diagnosed using tablet computers with good agreement with dedicated PACS workstations. Shortcomings in software and application design should be addressed if the potential of tablet computers for mobile teleradiology is to be fully realized.     

Factors Affecting Radiologist’s PACS Usage

The purpose of this study was to determine if any of the factors radiologist, examination category, time of week, and week effect PACS usage, with PACS usage defined as the sequential order of computer commands issued by a radiologist in a PACS during interpretation and dictation. We initially hypothesized that only radiologist and examination category would have significant effects on PACS usage. Command logs covering 8 weeks of PACS usage were analyzed. For each command trace (describing performed activities of an attending radiologist interpreting a single examination), the PACS usage variables number of commands, number of command classes, bigram repetitiveness, and time to read were extracted. Generalized linear models were used to determine the significance of the factors on the PACS usage variables. The statistical results confirmed the initial hypothesis that radiologist and examination category affect PACS usage and that the factors week and time of week to a large extent have no significant effect. As such, this work provides direction for continued efforts to analyze system data to better understand PACS utilization, which in turn can provide input to enable optimal utilization and configuration of corresponding systems. These continued efforts were, in this work, exemplified by a more detailed analysis using PACS usage profiles, which revealed insights directly applicable to improve PACS utilization through modified system configuration.     

Radiologists’ Variation of Time to Read Across Different Procedure Types

The workload of US radiologists has increased over the past two decades as measured through total annual relative value units (RVUs). This increase in RVUs generated suggests that radiologists’ productivity has increased. However, true productivity (output unit per input unit; RVU per time) is at large unknown since actual time required to interpret and report a case is rarely recorded. In this study, we analyzed how the time to read a case varies between radiologists over a set of different procedure types by retrospectively extracting reading times from PACS usage logs. Specifically, we tested two hypotheses that; i) relative variation in time to read per procedure type increases as the median time to read a procedure type increases, and ii) relative rankings in terms of median reading speed for individual radiologists are consistent across different procedure types. The results that, i) a correlation of -0.25 between the coefficient of variation and median time to read and ii) that only 12 out of 46 radiologists had consistent rankings in terms of time to read across different procedure types, show both hypotheses to be without support. The results show that workload distribution will not follow any general rule for a radiologist across all procedures or a general rule for a specific procedure across many readers. Rather the findings suggest that improved overall practice efficiency can be achieved only by taking into account radiologists’ individual productivity per procedure type when distributing unread cases.     

Soft Copy Display Requirements for Digital Mammography

One of the advantages of digital mammography is to display mammograms on softcopy (electronic displays). Softcopy display of mammography is challenging because of the spatial and contrast resolution demands present in mammograms. We have designed and developed a softcopy mammography display application, Mammoview, which is capable of allowing radiologists to read mammograms as quickly and as accurately as they can on film alternators. We review the studies using Mammoview to elucidate the requirements of a successful softcopy display station. The design and development of the Mammoview softcopy display station are described in this article, and results of several studies using Mammoview are reported, including subjective feedback from Radiological Society of North America (RSNA) conference demonstrations, and clinical studies measuring performance in terms of speed and accuracy. Additional analysis of user interactions and user feedback is used to study the successes and shortcomings of mammography display stations like Mammoview. Overall, radiologist readings using Mammoview have been shown to be as fast and as accurate as readings using mammography film alternators. However, certain parts of the softcopy interface were more successful than their film counterparts, whereas others were less successful. Data analysis of the recorded human–computer interactions for the softcopy component of the clinical trial indicate statistically significant correlations between the difference in review time of softcopy versus alternator readings and three factors: the number of interactions, the reader, and the size of the image being reviewed. The first factor (number of interactions) suggests that simpler interfaces require less time to use; the second factor, the reader, supports previous findings that radiologists vary in how fast they read screening mammography studies; the third, size of image, suggests that the speed of softcopy review is increased relative to film readings when images are significantly larger than the display size. Feedback from radiologists using the system in clinical trials and at demonstration exhibits at RSNA indicated good acceptance of the interface and easy adaptation. Radiologists indicated that they felt comfortable using the interface, and that they would use such a softcopy interface in clinical practice. Finally, preliminary work suggests that the addition of a simple interaction to incorporate computer-aided detection (CAD) results would improve reading accuracy without significantly increasing reader times.     

Integrating Multiple Clinical Information Systems using the Java Message Service Framework to Enable the Delivery of Urgent Exam Results at the Point of Care

The aim of this study is to determine if network-enabled personal digital assistants (PDAs) can be used to facilitate the timely delivery of urgent radiological exam results by reducing the interval from when the radiologist's initial interpretation is available to when it is first viewed by an emergency department (ED) physician. A web- and Java message service (JMS)-based application was built to replace the original fax-based wet-read procedure. The new system allows radiologists to enter wet-reads from the picture archiving and communication system (PACS) display station and to track discrepancies between the wet-read and final report. It also notifies the ED physicians when exam results are available via the PDAs and permits them to view the full text of the wet-read and final reports from the devices. The new system is compared to the original procedure with the results showing improvements with the wireless method. Furthermore, feedback from a qualitative survey of PDA users was positive, suggesting that PDAs may provide one means for accessing urgent clinical data at the point of care.     

Evaluation of Irreversible JPEG Compression for A Clinical Ultrasound Practice

A prior ultrasound study indicated that images with low to moderate levels of JPEG and wavelet compression were acceptable for diagnostic purposes. The purpose of this study is to validate this prior finding using the Joint Photographic Experts Group (JPEG) baseline compression algorithm, at a compression ratio of approximately 10:1, on a sufficiently large number of grayscale and color ultrasound images to attain a statistically significant result. The practical goal of this study is to determine if it is feasible for radiologists to use irreversibly compressed images as an integral part of the day to day ultrasound practice (ie, perform primary diagnosis with, and store irreversibly compressed images in the ultrasound PACS archive). In this study, 5 Radiologists were asked to review 300 grayscale and color static ultrasound images selected from 4 major anatomic groups. Each image was compressed and decompressed using the JPEG baseline compression algorithm at a fixed quality factor resulting in an average compression ratio of approximately 9:1. The images were presented in pairs (original and compressed) in a blinded fashion on a PACS workstation in the ultrasound reading areas, and radiologists were asked to pick which image they preferred in terms of diagnostic utility and their degree of certainty (on a scale from 1 to 4). Of the 1499 total readings, 50.17% (95% confidence intervals at 47.6%, and 52.7%) indicated a preference for the original image in the pair, and 49.83% (95% confidence intervals at 47.3%, and 52.0%) indicated a preference for the compressed image. These findings led the authors to conclude that static color and gray-scale ultrasound images compressed with JPEG at approximately 9:1 are statistically indistinguishable from the originals for primary diagnostic purposes. Based on the authors laboratory experience with compression and the results of this and other prior studies, JPEG compression is now being applied to all ultrasound images in the authors' radiology practice before reading. No image quality-related issues have been encountered after 12 months of operation (approximately 48000 examinations).     

Online Error Reporting for Managing Quality Control Within Radiology

Information technology systems within health care, such as picture archiving and communication system (PACS) in radiology, can have a positive impact on production but can also risk compromising quality. The widespread use of PACS has removed the previous feedback loop between radiologists and technologists. Instead of direct communication of quality discrepancies found for an examination, the radiologist submitted a paper-based quality-control report. A web-based issue-reporting tool can help restore some of the feedback loop and also provide possibilities for more detailed analysis of submitted errors. The purpose of this study was to evaluate the hypothesis that data from use of an online error reporting software for quality control can focus our efforts within our department. For the 372,258 radiologic examinations conducted during the 6-month period study, 930 errors (390 exam protocol, 390 exam validation, and 150 exam technique) were submitted, corresponding to an error rate of 0.25 %. Within the category exam protocol, technologist documentation had the highest number of submitted errors in ultrasonography (77 errors [44 %]), while imaging protocol errors were the highest subtype error for computed tomography modality (35 errors [18 %]). Positioning and incorrect accession had the highest errors in the exam technique and exam validation error category, respectively, for nearly all of the modalities. An error rate less than 1 % could signify a system with a very high quality; however, a more likely explanation is that not all errors were detected or reported. Furthermore, staff reception of the error reporting system could also affect the reporting rate.     

A Comparative Study of Conventional Mammography Film Interpretations with Soft Copy Readings of the Same Examinations

An acceptable mammography film digitizer must provide high-quality images at a level of diagnostic accuracy comparable to reading conventional film examinations. The purpose of this study was to determine if there are significant differences between the interpretations of conventional film-screen mammography examinations and soft copy readings of the images produced by a mammography film digitizer. Eight radiologists interpreted 120 mammography examinations, half as original films and the other half as digital images on a soft copy work station. No radiologist read the same examination twice. The interpretations were recorded in accordance with the Breast Imaging Reporting and Data System and included other variables such as perceived image quality and diagnostic difficulty and confidence. The results provide support for the hypothesis that there are no significant differences between the interpretations of conventional film-screen mammography examinations and soft copy examinations produced by a mammography film digitizer. The study was conducted primarily at the Johns Hopkins Medical Institutions in Baltimore, MD where all of the authors except Dr. Chad Mitchell are located. He is a Naval Officer at the Uniformed Services University of the Health Sciences in Bethesda, MD.     

Detection of interstitial lung abnormalities on picture archive and communication system video monitors

The purpose of this study was to compare the detection of interstitial lung abnormalities on video display workstation monitors between radiologists experienced with video image interpretation and radiologists who lack this experience. Twenty-four patients with interstitial lung abnormalities documented by high-resolution computed tomography (HRCT) and lung biopsy, and 26 control patients with no history of pulmonary disease or a normal HRCT and normal chest radiographs were studied. Images were acquired using storage phosphor digital radiography and displayed on 1,640×2,048 pixel resolution video monitors. Five board-certified radiologists evaluated the images in a blinded and randomized manner by using a six-point presence of abnormality grading scale. Three radiologists were from 1 to 4 years out of residency and considered to be experienced workstation monitor readers with between 1 to 3 years of video monitor image interpretation. For the inexperienced readers, one radiologist had no prior experience with reading images from a video monitor and was direct out of residency, and the other radiologist had less than 4 months of intermittent exposure and was 1 year out of residency. Sensitivity and specificity were determined for individual readers. Positive predictive values, negative predictive values, accuracy, and receiver-operating curves were alsoggenerated. A comparison was made between experienced and inexperienced readers. For readers experienced with video monitor image interpretation, the sensitivity ranged from 87.5% to 92%, specificity from 69% to 92%, positive predictive value (PPV) from 73% to 87.5%, negative predictive value (NPV) from 87% to 90%, and accuracy from 80% to 88%. For inexperienced readers, these values were sensitivity 58%, specificity 50% to 65% PPV 52% to 61%, NPV 56.5% to 63%, and accuracy 54% to 62%. Comparing image interpretation between experienced and inexperienced readers, there were statistically significant differences for sensitivity (P<.01), specificity (P<.01), PPV (P<.05), NPV (P<.05), accuracy (P<.05), and area under the receiver operator curve (Az) (P<.01). Within the respective experienced and inexperienced groups, no statistical significant differences were present. Our results show that digitally acquired chest radiographs displayed on high-resolution workstation monitors are adequate for the detection of interstitial lung abnormalities when the images are interpreted by radiologists experienced with video image interpretation. Radiologists inexperienced with video monitor image interpretation, however, cannot reliably interpret images for the detection of interstitial lung abnormalities.     

Data Management Solution for Large-Volume Computed Tomography in an Existing Picture Archiving and Communication System (PACS)

Multidetector row computed tomography (MDCT) creates massive amounts of data, which can overload a picture archiving and communication system (PACS). To solve this problem, we designed a new data storage and image interpretation system in an existing PACS. Two MDCT image datasets, a thick- and a thin-section dataset, and a single-detector CT thick-section dataset were reconstructed. The thin-section dataset was archived in existing PACS disk space reserved for temporary storage, and the system overwrote the source data to preserve available disk space. The thick-section datasets were archived permanently. Multiplanar reformation (MPR) images were reconstructed from the stored thin-section datasets on the PACS workstation. In regular interpretations by eight radiologists during the same week, the volume of images and the times taken for interpretation of thick-section images with (246 CT examinations) or without (170 CT examinations) thin-section images were recorded, and the diagnostic usefulness of the thin-section images was evaluated. Thin-section datasets and MPR images were used in 79% and 18% of cases, respectively. The radiologists’ assessments of this system were useful, though the volume of images and times taken to archive, retrieve, and interpret thick-section images together with thin-section images were significantly greater than the times taken without thin-section images. The limitations were compensated for by the usefulness of thin-section images. This data storage and image interpretation system improves the storage and availability of the thin-section datasets of MDCT and can prevent overloading problems in an existing PACS for the moment.Key words: CT, MDCT, PACS, computer applications     

Evaluation of teleradiology for interpretation of intravenous urograms

The diagnostic yield of a commercial teleradiology/picture archiving and communication system (ATT-Philips Comm View T/PACS) was evaluated for 100 urograms. A single image from each examination was digitized (2048 x 1684 x 12-bit pixels) and transmitted from a satellite hospital over a T-1 line using the T/PACS system. The video display of each digitized image was reviewed independently by four radiologists. The same four radiologists reviewed the original film images at a different time without knowledge of their T/PACS interpretation. There was no statistically significant difference in the sensitivity for clinical findings between T/PACS (86%) and film (89%). The false positive rate, however, was significantly higher with T/PACS than with film (44 versus 32 false positive findings per 100 films). We conclude that T/PACS of the type studied here demonstrates sufficient sensitivity for the detection of clinically important urographic findings in the emergency setting. A final reading of the original films is still necessary, however, to assure appropriate specificity.     

Picture archiving and communication system training for physicians: Lessons learned at the Baltimore VA Medical Center

Physicians practicing at the “filmless” Baltimore VA Medical Center need to be proficient in the use of the picture archiving and communication system (PACS) to be able to view radiologic images and accompanying reports. PACS training is necessary to assure optimal patient care and to satisfy potential medicolegal requirements. Providing such training is the responsibility of both the Imaging Department and the hospital. Training in the use of the PACS at the Baltimore VA is conducted by an on-site application specialist. Data were collected from interviews with the trainer, training log sheets, and physician surveys. Although 100% of radiologists received formal training, only 22% of nonradiologists were formally trained; 32% of these physicians identified themselves as having been trained by their peers and 41% stated they were self-trained. We identified two goals of a PACS training program. The first is to teach physicians how to retrieve images and reports from current as well as prior studies and display them on a computer workstation. Secondly, the training should include instruction on the use of the various workstation tools to enhance image interpretation. Imaging requirements and usage by different physician groups vary, and PACS training should be tailored accordingly. Difficulties in the scheduling of training sessions during working hours and the widespread use of a “generic” log-on identification have contributed to the low (22%) compliance of nonradiologists with the formal training program. Although we believe that one-on-one training is most effective and can be best tailored to the needs and computer expertise of an individual particular physician, computer based training (both on and off-line) may provide an acceptable, and in some cases, a preferred alternative.     

The reliability and distinguishability of ultrasound diagnosis of ovarian masses

Background: For any radiologist, intra-observer agreement in observing and decision making in diagnosis of any disease is of great importance, and so is observing and reading ultrasound pictures of ovarian masses and distinguishing amongst their categories. Aims: In this study, the reliability and consistency of ultrasound diagnosis of ovarian tumors have been evaluated. Settings and Design: Two experienced and three less experienced radiologists assessed ultrasounds of 40 patients of Mirza Koochak Khan Hospital in Tehran, Iran, in 2005. Materials and Methods: In this prospective observational study, the ultrasounds were performed by an expert radiologist, with a single apparatus. These ultrasounds have been evaluated separately and independently in two periods (with a 1-week interval). Statistical Analysis Used: Weighted kappa was used to calculate intra-observer agreement (reliability), and two statistical models were applied to assess category distinguishability (consistency). SPSS version 10, SAS version 8, and EXCEL 2003 have been used to do an appropriate statistical analysis. Results: Mean of weighted kappa was 0.81, and mean of distinguishability was 0.995 for our experienced radiologists, due to their superior results. Because of weaker results obtained by the less experienced radiologists, mean of weighted kappa and mean of distinguishability were 0.65 and 0.967 respectively. Overall mean of distinguishability for benign and borderline categories was 0.969; and for malignant and borderline categories, it was 0.987. Conclusion: Although experienced radiologists functioned better than the less experienced radiologists, all of them showed appropriate distinguishability and intra-observer agreement in diagnosis and categorization of the ovarian masses. Distinguishing benign category from borderline was more difficult than distinguishing malignant category from borderline. In general, experienced radiologists showed better results compared to less experienced radiologists.     

Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective

Mammographic breast density has been established as an independent risk marker for developing breast cancer. Breast density assessment is a routine clinical need in breast cancer screening and current standard is using the Breast Imaging and Reporting Data System (BI-RADS) criteria including four qualitative categories (i.e., fatty, scattered density, heterogeneously dense, or extremely dense). In each mammogram examination, a breast is typically imaged with two different views, i.e., the mediolateral oblique (MLO) view and cranial caudal (CC) view. The BI-RADS-based breast density assessment is a qualitative process made by visual observation of both the MLO and CC views by radiologists, where there is a notable inter- and intra-reader variability. In order to maintain consistency and accuracy in BI-RADS-based breast density assessment, gaining understanding on radiologists’ reading behaviors will be educational. In this study, we proposed to leverage the newly emerged deep learning approach to investigate how the MLO and CC view images of a mammogram examination may have been clinically used by radiologists in coming up with a BI-RADS density category. We implemented a convolutional neural network (CNN)-based deep learning model, aimed at distinguishing the breast density categories using a large (15,415 images) set of real-world clinical mammogram images. Our results showed that the classification of density categories (in terms of area under the receiver operating characteristic curve) using MLO view images is significantly higher than that using the CC view. This indicates that most likely it is the MLO view that the radiologists have predominately used to determine the breast density BI-RADS categories. Our study holds a potential to further interpret radiologists’ reading characteristics, enhance personalized clinical training to radiologists, and ultimately reduce reader variations in breast density assessment.     

Study and status consistency duplicate-read protection in a distributed architecture

This presentation will discuss the benefits and pitfalls of implementing a study status and duplicate-read protection mechanism within a distributed picture archiving and communication system (PACS) architecture. There are many advantages to a distributed PACS network in which image studies are proactively pushed to reading stations before they are required by a radiologist. The absence of a central server, which serves on demand, makes managing study status and protecting against duplicate reads challenging. The system to manage study status and read access must be efficient, robust, and easy to administer. A system is presented that accomplishes these goals while maintaining the advantages of a distributed architecture.Methods: The basic workflow of the system is that image studies acquired at a modality device are automatically sent to an archive server. Using a set of advanced routing rules, the archive automatically routes studies to diagnostic workstations where studies are candidates for diagnostic read. The workstations display a list of all local studies available for reading. A monitor application running on the workstations coordinates access to studies for diagnostic read. Once the status of a study has been changed, the workstations on the networks and the archive are notified, which causes the study to be automatically removed from any list on a workstation where it might be a read candidate. Results: Implementation of this system provides a balanced work-flow throughout the system while minimizing the need for costly high-speed network hardware. Additionally studies are read as soon as they are available by the next available radiologist. This workflow is enabled without the need for specific interaction by any of the radiologists on the network. By having the images available at the workstation in an organized worklist, this methodology increases the efficiency of the radiologist.Conclusion: The implementation of this system enables a radiology department, or even a specialty group within a department, to gain the benefit of a distributed system as well as the benefits provided by a central-server architecture. This can be done very cost effectively with minimal configuration overhead and hardware requirements.     

Radiologist Productivity Analytics: Factors Impacting Abdominal Pelvic CT Exam Reporting Times

The purpose is to determine factors impacting radiologist abdominal pelvic CT exam reporting time. This study was Research Ethics Board approved. Between January 2019 and March 2020, consecutive abdominal pelvic CT exams were documented as structured or unstructured based on application of templates with separate sections for different organs or organ systems. Radiologist reporting location, patient class (inpatient, Emergency Department (ED) patient, outpatient), radiologist fellowship-training, report word count, and radiologist years of experience were documented. Median reporting times were compared using the Wilcoxon Rank-sum test, Kruskal–Wallis test, and regression analysis. Spearman’s rank correlation was used to determine correlation between word count and radiologist experience with reporting time. P?<?0.05 is defined statistical significance. A total of 3602 abdominal pelvic CT exam reports completed by 33 radiologists were reviewed, including 1150 outpatient and 2452 inpatient and Emergency Department (ED) cases. 1398 of all reports were structured. Median reporting time for structured and unstructured reports did not differ (P?=?0.870). Reports dictated in-house were completed faster than reports dictated remotely (P?<?0.001), and reports for inpatients/ED patients were completed faster than for outpatients (P?<?0.001). Reporting time differences existed between radiologists (P?<?0.001) that were not explained by fellowship training (P?=?0.762). Median reporting time had a weak correlation with word count (ρ?=?0.355) and almost no correlation with radiologist years of experience (ρ?=?0.167), P?<?0.001. Abdominal pelvic CT reporting is most efficient when dictations are completed in-house and for high-priority cases; the use of structured templates, radiologist fellowship training, and years of experience have no impact on reporting times.