CT protocol review and optimization

Protocol parameter extraction and centralization framework for comprehensive and in-depth CT protocol review and management

CT protocol management is an arduous task that requires expertise from a variety of radiology professionals, including technologists, radiologists, radiology IT professionals, and medical physicists. Each CT vendor has unique, proprietary protocol file structures, some of which may vary by scanner model, making it difficult to develop a universal framework for distilling technical parameters to a human-readable file format. An ideal solution for CT protocol management is to minimize the work required for parameter extraction by introducing a data format into the workflow that is universal to all CT scanners. In this paper, we report a framework for CT protocol management that converts raw protocol files to an intermediary format before outputting them in a human-readable format for a variety of practical clinical applications, including routine protocol review, protocol version tracking, and cross-protocol comparisons. The framework was developed in Python 3. Technical parameters of interest were determined via collaborative effort between medical physicists and lead technologists. Protocol files were extracted and analyzed from a variety of scanners across our hospital-wide CT fleet, including various systems from Siemens and GE. Protocols were subcategorized based on relevant technical parameters into regular, dual-energy, and cardiac CT protocols. Backend code for technical parameter extraction from raw protocol files to a JavaScript Object Notation (JSON) format was performed on a per-system basis. Conversion from JSON to a readable output format (MS Excel) was performed identically for all scanners using the universal framework developed and presented in this work. Example results for Siemens and GE scanners are shown, including side-by-side comparisons for protocols with similar clinical indications. In conclusion, our CT protocol management framework may be deployed on any CT system to improve clinical efficiency in protocol review and upkeep.

Knowledge of computed tomography dose optimisation and justification among CT users and referring physicians: A single hospital study

INTRODUCTION

Radiation dose associated with computed tomography (CT) remains a concern, and radiation risk does not receive the needed attention, especially in low and middle-income countries. This because the frequency of this high-dose examination is rapidly growing and systems for protocol optimisation and dose justification are yet to be provided in CT imaging.

OBJECTIVE

To determine radiographers' and radiologists' awareness and knowledge of CT dose optimisation. We also determined knowledge of dose justification and use of the referral guidelines amongst the referring physicians.

METHODS

Radiographers and radiologists were invited to complete a web-based questionnaire whilst the referring physicians completed a self-administered questionnaire. The returned questionnaires were analysed and a significant difference was determined using Yates corrected Chi-square, and a p-value of 0.05 was considered at the 95% confidence interval.

RESULTS

The response rates were 50% (17 out 34) and 35% (16 out 46) for radiographers and radiologists respectively while referring physicians had a response rate of 84% (92 out of 110). Overall, more radiographers (47.1%) than radiologists (18.8%) had good knowledge of CT doses and image quality, however, the difference in knowledge was not found to be significant (p = 0.167). In addition, knowledge of diagnostic reference levels (DRLs) was significantly (p = 0.033) higher amongst radiographers (52.9%) as compared to radiologists (12.5%). Meanwhile, physicians understood the principles of dose justification. However, their knowledge of referral guidelines was limited.

CONCLUSION

The study revealed that radiographers were more knowledgeable on matters relating to radiation dose and image quality as well as DRLs when compared to radiologists. Meanwhile, the concept of dose justification was understood among physicians, however, they had limited awareness and knowledge of referral guidelines.

How Do Cancer-Specific Computed Tomography Protocols Compare With the American College of Radiology Dose Index Registry? An Analysis of Computed Tomography Dose at 2 Cancer Centers

BACKGROUND

Little guidance exists on how to stratify radiation dose according to diagnostic task. Changing dose for different cancer types is currently not informed by the American College of Radiology Dose Index Registry dose survey.

METHODS

A total of 9602 patient examinations were pulled from 2 National Cancer Institute designated cancer centers. Computed tomography dose (CTDI vol ) was extracted, and patient water equivalent diameter was calculated. N-way analysis of variance was used to compare the dose levels between 2 protocols used at site 1, and three protocols used at site 2.

RESULTS

Sites 1 and 2 both independently stratified their doses according to cancer indications in similar ways. For example, both sites used lower doses ( P < 0.001) for follow-up of testicular cancer, leukemia, and lymphoma. Median dose at median patient size from lowest to highest dose level for site 1 were 17.9 (17.7-18.0) mGy (mean [95% confidence interval]) and 26.8 (26.2-27.4) mGy. For site 2, they were 12.1 (10.6-13.7) mGy, 25.5 (25.2-25.7) mGy, and 34.2 (33.8-34.5) mGy. Both sites had higher doses ( P < 0.001) between their routine and high-image-quality protocols, with an increase of 48% between these doses for site 1 and 25% for site 2. High-image-quality protocols were largely applied for detection of low-contrast liver lesions or subtle pelvic pathology.

CONCLUSIONS

We demonstrated that 2 cancer centers independently choose to stratify their cancer doses in similar ways. Sites 1 and 2 dose data were higher than the American College of Radiology Dose Index Registry dose survey data. We thus propose including a cancer-specific subset for the dose registry.

Establishment of Diagnostic Reference Levels in Cone Beam Computed Tomography Scans in the United Arab Emirates

This study aimed to address the knowledge gap in assessing the radiation doses from cone beam computed tomography (CBCT) procedures, establishing a typical value, and estimating effective and organ doses. A total of 340 patients aged 18-80 years were included in this study. Organ doses were estimated using VirtualDose IR software. The typical values were based on median values estimated as 1000 mGy cm². The mean ED (µSv) per procedure was 149.5 ± 56, and the mean of the peak skin dose during the CBCT examination was 39.29 mGy. The highest organ dose was received by the salivary glands (2.71 mGy), the extrathoracic region (1.64 mGy), thyroid (1.24 mGy) and eyes (0.61 mGy). The patients' doses were higher than in previous studies. Staff awareness, education, training and dose optimisation are highly recommended. With the establishment of local DRLs, patient dosages can be reduced successfully without compromising image quality.

Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.

AAPM Medical Physics Practice Guideline 1.b: CT protocol management and review practice guideline

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized. The following terms are used in the AAPM practice guidelines: (a) Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. (b) Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances.

A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre-A phantom study

Nowadays, given the technological advance in CT imaging and increasing heterogeneity in characteristics of CT scanners, a number of CT scanners with different manufacturers/technologies are often installed in a hospital centre and used by various departments. In this phantom study, a comprehensive assessment of image quality of 5 scanners (from 3 manufacturers and with different models) for head CT imaging, as clinically used at a single hospital centre, was hence carried out. Helical and/or sequential acquisitions of the Catphan-504 phantom were performed, using the scanning protocols (CTDI_vol range: 54.7–57.5 mGy) employed by the staff of various Radiology/Neuroradiology departments of our institution for routine head examinations. CT image quality for each scanner/acquisition protocol was assessed through noise level, noise power spectrum (NPS), contrast-to-noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD) and non-uniformity index analyses. Noise values ranged from 3.5 HU to 5.7 HU across scanners/acquisition protocols. NPS curves differed in terms of peak position (range: 0.21–0.30 mm^-1). A substantial variation of CNR values with scanner/acquisition protocol was observed for different contrast inserts. The coefficient of variation (standard deviation divided by mean value) of CNR values across scanners/acquisition protocols was 18.3%, 31.4%, 34.2%, 30.4% and 30% for teflon, delrin, LDPE, polystyrene and acrylic insert, respectively. An appreciable difference in MTF curves across scanners/acquisition protocols was revealed, with a coefficient of variation of f_50%/f_10% of MTF curves across scanners/acquisition protocols of 10.1%/7.4%. A relevant difference in LCD performance of different scanners/acquisition protocols was found. The range of contrast threshold for a typical object size of 3 mm was 3.7–5.8 HU. Moreover, appreciable differences in terms of NUI values (range: 4.1%-8.3%) were found. The analysis of several quality indices showed a non-negligible variability in head CT imaging capabilities across different scanners/acquisition protocols. This highlights the importance of a physical in-depth characterization of image quality for each CT scanner as clinically used, in order to optimize CT imaging procedures.

TOWARD NATIONAL CT DIAGNOSTIC REFERENCE LEVELS IN THE UNITED ARAB EMIRATES: A MULTICENTER REVIEW OF CT DOSE INDEX AND DOSE LENGTH PRODUCT

This multicenter study evaluated computed tomography dose index volume (CTDIvol) and dose length product (DLP) to contribute to establishing computed tomography (CT) national diagnostic reference levels (NDRLs) in the United Arab Emirates (UAE). Data from 240 patients, who underwent CT head, chest, abdomen-pelvis and urography examinations, were analyzed, including patient age, sex and weight, CTDIvol (mGy) and DLP (mGy cm). The proposed DRLs for each examination were calculated as the third quartile. DRLs are proposed using CTDIvol (mGy) and DLP (mGy cm) for CT head (67 and 1189, respectively), chest (8 and 302, respectively), abdomen-pelvis (28 and 1122, respectively) and urography (20 and 714, respectively). These values are comparable with the initial NDRLs and published international DRLs. Baseline values for International Radiology Center (IRC) CT DRLs were calculated on frequently performed CT examinations. Implementation of DRL values improves dose optimization based on procedures, scanner type and patient characteristics while maintaining acceptable image quality and diagnostic confidence.

Individualization of computed tomography protocols for suspected pulmonary embolism: a national investigation of routines

Objective

Given the extensive use of computed tomography (CT) in radiation-sensitive patients such as pregnant and pediatric patients, and considering the importance of tailoring CT protocols to patient characteristics for both the radiation dose and image quality, this study was performed to investigate the extent to which individualization of CT protocols is practiced across Norway.

Methods

This cross-sectional study involved collection of CT protocols and administration of a mini-questionnaire to obtain additional information about how CT examinations are individualized. All public hospitals performing CT to detect pulmonary embolism were invited, and 41% participated.

Results

Tailoring a standard protocol to different patient groups was more common than using dedicated protocols. Most of the available radiation dose-reduction approaches were used. However, implementation of these strategies was not systematic. Children and pregnant patients were examined without using dedicated CT protocols or by using protocol adjustments focusing on radiation dose reduction in 30% and 39% of the hospitals, respectively.

Conclusion

Practice optimization is needed, especially the development of dedicated CT protocols or guidelines that tailor the existing protocol to pediatric and pregnant patients. Practice might benefit from a more systematic approach to individualization of CT examinations, such as inserting tailoring instructions into CT protocols.

Pilot study of the multicentre DISCHARGE Trial: image quality and protocol adherence results of computed tomography and invasive coronary angiography

OBJECTIVE

To implement detailed EU cardiac computed tomography angiography (CCTA) quality criteria in the multicentre DISCHARGE trial (FP72007-2013, EC-GA 603266), we reviewed image quality and adherence to CCTA protocol and to the recommendations of invasive coronary angiography (ICA) in a pilot study.

MATERIALS AND METHODS

From every clinical centre, imaging datasets of three patients per arm were assessed for adherence to the inclusion/exclusion criteria of the pilot study, predefined standards for the CCTA protocol and ICA recommendations, image quality and non-diagnostic (NDX) rate. These parameters were compared via multinomial regression and ANOVA. If a site did not reach the minimum quality level, additional datasets had to be sent before entering into the final accepted database (FADB).

RESULTS

We analysed 226 cases (150 CCTA/76 ICA). The inclusion/exclusion criteria were not met by 6 of the 226 (2.7%) datasets. The predefined standard was not met by 13 of 76 ICA datasets (17.1%). This percentage decreased between the initial CCTA database and the FADB (multinomial regression, 53 of 70 vs 17 of 75 [76%] vs [23%]). The signal-to-noise ratio and contrast-to-noise ratio of the FADB did not improve significantly (ANOVA, p = 0.20; p = 0.09). The CTA NDX rate was reduced, but not significantly (initial CCTA database 15 of 70 [21.4%]) and FADB 9 of 75 [12%]; p = 0.13).

CONCLUSION

We were able to increase conformity to the inclusion/exclusion criteria and CCTA protocol, improve image quality and decrease the CCTA NDX rate by implementing EU CCTA quality criteria and ICA recommendations.

KEY POINTS

• Failure to meet protocol adherence in cardiac CTA was high in the pilot study (77.6%). • Image quality varies between sites and can be improved by feedback given by the core lab. • Conformance with new EU cardiac CT quality criteria might render cardiac CTA findings more consistent and comparable.

Development and validation of image quality scoring criteria (IQSC) for pediatric CT: a preliminary study

OBJECTIVE

To develop and assess the value and limitations of an image quality scoring criteria (IQSC) for pediatric CT exams.

METHODS

IQSC was developed for subjective assessment of image quality using the scoring scale from 0 to 4, with 0 indicating desired anatomy or features not seen, 3 for adequate image quality, and 4 depicting higher than needed image quality. Pediatric CT examinations from 30 separate patients were selected, five each for routine chest, routine abdomen, kidney stone, appendicitis, craniosynostosis, and ventriculoperitoneal (VP) shunt. Five board-certified pediatric radiologists independently performed image quality evaluation using the proposed IQSC. The kappa statistics were used to assess the interobserver variability.

RESULTS

All five radiologists gave a score of 3 to two-third (67%) of all CT exams, followed by a score of 4 for 29% of CT exams, and 2 for 4% exams. The median image quality scores for all exams were 3 and the interobserver agreement among five readers (acceptable image quality [scores 3 or 4] vs sub-optimal image quality ([scores 1 and 2]) was moderate to very good (kappa 0.4-1). For all five radiologists, the lesion detection was adequate for all CT exams.

CONCLUSIONS

The image quality scoring criteria covering routine and some clinical indication-based imaging scenarios for pediatric CT examinations has potential to offer a simple and practical tool for assessing image quality with a reasonable degree of interobserver agreement. A more extensive and multi-centric study is recommended to establish wider usefulness of these criteria.

Assessment of Image Quality and Dosimetric Performance of CT Simulators

BACKGROUND

CT simulator for radiation therapy aims to produce high-quality images for dose calculation and delineation of target and organs at risk in the process of treatment planning. Selection of CT imaging protocols that achieve a desired image quality while minimizing patient dose depends on technical CT parameters and their relationship with image quality and radiation dose. For similar imaging protocols using comparable technical CT parameters, there are also variations in image quality metrics between different CT simulator models. Understanding the relationship and variation is important for selecting appropriate imaging protocol and standardizing QC process. Here, we proposed an automated method to determine the relationship between image quality and radiation dose for various CT technical parameters.

MATERIAL AND METHOD

The impact of scan parameters on various aspects of image quality and volumetric CT dose index for a Philips Brilliance Big Bore and a Toshiba Aquilion One CT scanners were determined by using commercial phantom and automated image quality analysis software and cylindrical radiation dose phantom.

RESULTS AND DISCUSSION

Both scanners had very similar and satisfactory performance based on the diagnostic acceptance criteria recommended by ACR, International Atomic Energy Agency, and American Association of Physicists in Medicine. However, our results showed a compromise between different image quality components such as low-contrast and spatial resolution with the change of scanning parameters and revealed variations between the two scanners on their image quality performance. Measurement using a generic phantom and analysis by automated software was unbiased and efficient.

CONCLUSION

This method provides information that can be used as a baseline for CT scanner image quality and dosimetric QC for different CT scanner models in a given institution or across sites.

Detection of unwarranted CT radiation exposure from patient and imaging protocol meta-data using regularized regression

BACKGROUND

Variability in radiation exposure from CT scans can be appropriate and driven by patient features such as body habitus. Quantitative analysis may be performed to discover instances of unwarranted radiation exposure and to reduce the probability of such occurrences in future patient visits. No universal process to perform identification of outliers is widely available, and access to expertise and resources is variable.

OBJECTIVE

The goal of this study is to develop an automated outlier detection procedure to identify all scans with an unanticipated high radiation exposure, given the characteristics of the patient and the type of the exam.

MATERIALS AND METHODS

This Institutional Review Board-approved retrospective cohort study was conducted from June 30, 2012 - December 31, 2013 in a quaternary academic medical center. The de-identified dataset contained 28 fields for 189,959 CT exams. We applied the variable selection method Least Absolute Shrinkage and Selection Operator (LASSO) to select important variables for predicting CT radiation dose. We then employed a regression approach that is robust to outliers, to learn from data a predictive model of CT radiation doses given important variables identified by LASSO. Patient visits whose predicted radiation dose was statistically different from the radiation dose actually received were identified as outliers.

RESULTS

Our methodology identified 1% of CT exams as outliers. The top-5 predictors discovered by LASSO and strongly correlated with radiation dose were Tube Current, kVp, Weight, Width of collimator, and Reference milliampere-seconds. A human expert validation of the outlier detection algorithm has yielded specificity of 0.85 [95% CI 0.78-0.92] and sensitivity of 0.91 [95% CI 0.85-0.97] (PPV = 0.84, NPV = 0.92). These values substantially outperform alternative methods we tested (F1 score 0.88 for our method against 0.51 for the alternatives).

CONCLUSION

The study developed and tested a novel, automated method for processing CT scanner meta-data to identify CT exams where patients received an unwarranted amount of radiation. Radiation safety and protocol review committees may use this technique to uncover systemic issues and reduce future incidents.

Practical considerations for obtaining high quality quantitative computed tomography data of the skeletal system

Quantitative CT (QCT) analysis involves the calculation of specific parameters such as bone volume and density from CT image data, and can be a powerful tool for understanding bone quality and quantity. However, without careful attention to detail during all steps of the acquisition and analysis process, data can be of poor- to unusable-quality. Good quality QCT for research requires meticulous attention to detail and standardization of all aspects of data collection and analysis to a degree that is uncommon in a clinical setting. Here, we review the literature to summarize practical and technical considerations for obtaining high quality QCT data, and provide examples of how each recommendation affects calculated variables. We also provide an overview of the QCT analysis technique to illustrate additional opportunities to improve data reproducibility and reliability. Key recommendations include: standardizing the scanner and data acquisition settings, minimizing image artifacts, selecting an appropriate reconstruction algorithm, and maximizing repeatability and objectivity during QCT analysis. The goal of the recommendations is to reduce potential sources of error throughout the analysis, from scan acquisition to the interpretation of results.

CT and MR Protocol Standardization Across a Large Health System: Providing a Consistent Radiologist, Patient, and Referring Provider Experience

Building and maintaining a comprehensive yet simple set of standardized protocols for a cross-sectional image can be a daunting task. A single department may have difficulty preventing "protocol creep," which almost inevitably occurs when an organized "playbook" of protocols does not exist and individual radiologists and technologists alter protocols at will and on a case-by-case basis. When multiple departments or groups function in a large health system, the lack of uniformity of protocols can increase exponentially. In 2012, the University of Colorado Hospital formed a large health system (UCHealth) and became a 5-hospital provider network. CT and MR imaging studies are conducted at multiple locations by different radiology groups. To facilitate consistency in ordering, acquisition, and appearance of a given study, regardless of location, we minimized the number of protocols across all scanners and sites of practice with a clinical indication-driven protocol selection and standardization process. Here we review the steps utilized to perform this process improvement task and insure its stability over time. Actions included creation of a standardized protocol template, which allowed for changes in electronic storage and management of protocols, designing a change request form, and formation of a governance structure. We utilized rapid improvement events (1 day for CT, 2 days for MR) and reduced 248 CT protocols into 97 standardized protocols and 168 MR protocols to 66. Additional steps are underway to further standardize output and reporting of imaging interpretation. This will result in an improved, consistent radiologist, patient, and provider experience across the system.

Tracking Patterns of Nonadherence to Prescribed CT Protocol Parameters

PURPOSE

Quantification of the frequency, understanding the motivation, and documentation of the changes made by CT technologists at scan time are important components of monitoring a quality CT workflow.

METHODS

CT scan acquisition data were collected from one CT scanner for a period of 1 year. The data included all relevant acquisition parameters needed to define the technical side of a CT protocol. An algorithm was created to sort these data in groups of irradiation events with the same combinations of scan acquisition parameters. For scans modified at scan time, it was hypothesized that these examinations would show up only once in the organized data. A classification scheme was developed to place each "one-off" examination into a category related to what motivated the scan-time change.

RESULTS

A total of 132,707 irradiation events were organized into 434 groups of unique scan acquisition parameters. One hundred forty-four irradiation events had acquisition parameters that showed up only once in the data. These "one-offs" were classified as follows: 25% represented rarely used protocols, 17% were due to service scans, 16% were changed for unknown and therefore undesired reasons, 15% were changed by technologists trying to adapt protocol to patient size, 12% were allowable scan-time changes, 8% of scans had tube current maxed out, and 6% of scans were changed to a higher dose mode as requested by radiologists.

CONCLUSIONS

The outcome of this study suggests many areas of needed technologist training and chances for optimizing this institution's CT protocols.

Implementation and evaluation of a protocol management system for automated review of CT protocols

Protocol review is important to decrease the risk of patient injury and increase the consistency of CT image quality. A large volume of CT protocols makes manual review labor‐intensive, error‐prone, and costly. To address these challenges, we have developed a software system for automatically managing and monitoring CT protocols on a frequent basis. This article describes our experiences in the implementation and evaluation of this protocol monitoring system. In particular, we discuss various strategies for addressing each of the steps in our protocol‐monitoring workflow, which are: maintaining an accurate set of master protocols, retrieving protocols from the scanners, comparing scanner protocols to master protocols, reviewing flagged differences between the scanner and master protocols, and updating the scanner and/or master protocols. In our initial evaluation focusing only on abdomen and pelvis protocols, we detected 309 modified protocols in a 24‐week trial period. About one‐quarter of these modified protocols were determined to contain inappropriate (i.e., erroneous) protocol parameter modifications that needed to be corrected on the scanner. The most frequently affected parameter was the series description, which was inappropriately modified 47 times. Two inappropriate modifications were made to the tube current, which is particularly important to flag as this parameter impacts both radiation dose and image quality. The CT protocol changes detected in this work provide strong motivation for the use of an automated CT protocol quality control system to ensure protocol accuracy and consistency.

PACS number(s): 87.57.Q‐

Insight into the Molecular Imaging of Alzheimer's Disease

Alzheimer's disease is a complex neurodegenerative disease affecting millions of individuals worldwide. Earlier it was diagnosed only via clinical assessments and confirmed by postmortem brain histopathology. The development of validated biomarkers for Alzheimer's disease has given impetus to improve diagnostics and accelerate the development of new therapies. Functional imaging like positron emission tomography (PET), single photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), and proton magnetic resonance spectroscopy provides a means of detecting and characterising the regional changes in brain blood flow, metabolism, and receptor binding sites that are associated with Alzheimer's disease. Multimodal neuroimaging techniques have indicated changes in brain structure and metabolic activity, and an array of neurochemical variations that are associated with neurodegenerative diseases. Radiotracer-based PET and SPECT potentially provide sensitive, accurate methods for the early detection of disease. This paper presents a review of neuroimaging modalities like PET, SPECT, and selected imaging biomarkers/tracers used for the early diagnosis of AD. Neuroimaging with such biomarkers and tracers could achieve a much higher diagnostic accuracy for AD and related disorders in the future.

How to use the equipment you have for appropriate quality at low radiation dose

A CT department's ability to image with low radiation doses is determined primarily by the CT scan protocols and the radiologists' image quality expectations and to a lesser extent by the dose-reduction features available. The CT technology level has a smaller influence than might be expected. There are, however, exceptions where dose is directly linked to the scanner's technical capabilities. The key to appropriate image quality with low radiation dose is therefore optimised scan protocols. To optimise effectively, an in-depth understanding of the technical performance of the scanner is required. Therefore, optimisation is best carried out by a multi-disciplinary team that includes radiologists, technologists and medical physics experts. This article describes practical strategies for carrying out such exercises.

On the same page--physicist and radiologist perspectives on protocol management and review

To sustain compliance with accreditation requirements of the ACR, Joint Commission, and state-specific statutes and regulatory requirements, a CT protocol review committee requires a structure for systematic analysis of protocols. Safe and reproducible practice of CT in a complex environment requires that physician supervision processes and protocols be precisely and clearly presented. This article discusses necessary components for data structure, and a description of an IT-based approach for protocol review based on experiences at 2 academic centers, 3 community hospitals, 1 cancer center, and 2 outpatient clinics.

Compliance with AAPM Practice Guideline 1.a: CT Protocol Management and Review - from the perspective of a university hospital

The purpose of this paper is to describe our experience with the AAPM Medical Physics Practice Guideline 1.a: “CT Protocol Management and Review Practice Guideline”. Specifically, we will share how our institution's quality management system addresses the suggestions within the AAPM practice report. We feel this paper is needed as it was beyond the scope of the AAPM practice guideline to provide specific details on fulfilling individual guidelines. Our hope is that other institutions will be able to emulate some of our practices and that this article would encourage other types of centers (e.g., community hospitals) to share their methodology for approaching CT protocol optimization and quality control. Our institution had a functioning CT protocol optimization process, albeit informal, since we began using CT. Recently, we made our protocol development and validation process compliant with a number of the ISO 9001:2008 clauses and this required us to formalize the roles of the members of our CT protocol optimization team. We rely heavily on PACS‐based IT solutions for acquiring radiologist feedback on the performance of our CT protocols and the performance of our CT scanners in terms of dose (scanner output) and the function of the automatic tube current modulation. Specific details on our quality management system covering both quality control and ongoing optimization have been provided. The roles of each CT protocol team member have been defined, and the critical role that IT solutions provides for the management of files and the monitoring of CT protocols has been reviewed. In addition, the invaluable role management provides by being a champion for the project has been explained; lack of a project champion will mitigate the efforts of a CT protocol optimization team. Meeting the guidelines set forth in the AAPM practice guideline was not inherently difficult, but did, in our case, require the cooperation of radiologists, technologists, physicists, IT, administrative staff, and hospital management. Some of the IT solutions presented in this paper are novel and currently unique to our institution.

PACS number: 87.57.Q

Data-driven CT protocol review and management—experience from a large academic hospital

PURPOSE

Protocol review plays a critical role in CT quality assurance, but large numbers of protocols and inconsistent protocol names on scanners and in exam records make thorough protocol review formidable. In this investigation, we report on a data-driven cataloging process that can be used to assist in the reviewing and management of CT protocols.

METHODS

We collected lists of scanner protocols, as well as 18 months of recent exam records, for 10 clinical scanners. We developed computer algorithms to automatically deconstruct the protocol names on the scanner and in the exam records into core names and descriptive components. Based on the core names, we were able to group the scanner protocols into a much smaller set of "core protocols," and to easily link exam records with the scanner protocols. We calculated the percentage of usage for each core protocol, from which the most heavily used protocols were identified.

RESULTS

From the percentage-of-usage data, we found that, on average, 18, 33, and 49 core protocols per scanner covered 80%, 90%, and 95%, respectively, of all exams. These numbers are one order of magnitude smaller than the typical numbers of protocols that are loaded on a scanner (200-300, as reported in the literature). Duplicated, outdated, and rarely used protocols on the scanners were easily pinpointed in the cataloging process.

CONCLUSIONS

The data-driven cataloging process can facilitate the task of protocol review.