Investigation of misfiled cases in the PACS environment and a solution to prevent filing errors for chest radiographs

RATIONALE AND OBJECTIVE: The aim of the study was to survey misfiled cases in a picture archiving and communication system environment at two hospitals and to demonstrate the potential usefulness of an automated patient recognition method for posteroanterior chest radiographs based on a template-matching technique designed to prevent filing errors. MATERIALS AND METHODS: We surveyed misfiled cases obtained from different modalities in one hospital for 25 months, and misfiled cases of chest radiographs in another hospital for 17 months. For investigating the usefulness of an automated patient recognition and identification method for chest radiographs, a prospective study has been completed in clinical settings at the latter hospital. RESULTS: The total numbers of misfiled cases for different modalities in one hospital and for chest radiographs in another hospital were 327 and 22, respectively. The misfiled cases in the two hospitals were mainly the result of human errors (eg, incorrect manual entries of patient information, incorrect usage of identification cards in which an identification card for the previous patient was used for the next patient's image acquisition). The prospective study indicated the usefulness of the computerized method for discovering misfiled cases with a high performance (ie, an 86.4% correct warning rate for different patients and 1.5% incorrect warning rate for the same patients). CONCLUSION: We confirmed the occurrence of misfiled cases in the two hospitals. The automated patient recognition and identification method for chest radiographs would be useful in preventing wrong images from being stored in the picture archiving and communication system environment.     

Computerized image-searching method for finding correct patients for misfiled chest radiographs in a PACS server by use of biological fingerprints

We have developed an automated image-searching method based on biological fingerprints for identifying correct patients in misfiled chest radiographs in a picture archiving and communication system (PACS) server. We used five biological fingerprints including distinctive anatomic structures in a misfiled chest radiograph of an unknown patient to find another image of the same patient stored with correct patient information in a PACS server. The correlation values were determined for the corresponding biological fingerprints in all images in the image server. The correlation indices as a measure of the overall similarity of the two images were determined from the summation of five correlation values and the combination of correlation values with the weighting factors. Finally, the correct patient was identified automatically by the image with the highest correlation index. By use of the summation of five correlation values as the correlation index, 78.0 % (156/200) of the 200 patients for misfiled images were correctly identified in the database. When we applied the weighting factors for each biological fingerprint to determine the correlation index, the performance in identifying the correct patient was improved to 87.5 % (175/200). An additional 5.0 % (10/200) of images were included in the Top 10 ranking of the correlation index in the database. These cases could be identified manually by radiology personnel. We conclude that the automated image-searching method based on biological fingerprints with weighting factors would be useful for identification of the correct patient in the case of misfiled chest radiographs in a PACS server.     

Automated image-matching technique for comparative diagnosis of the liver on CT examination

When interpreting enhanced computer tomography (CT) images of the upper abdomen, radiologists visually select a set of images of the same anatomical positions from two or more CT image series (i.e., non-enhanced and contrast-enhanced CT images at arterial and delayed phase) to depict and to characterize any abnormalities. The same process is also necessary to create subtraction images by computer. We have developed an automated image selection system using a template-matching technique that allows the recognition of image sets at the same anatomical position from two CT image series. Using the template-matching technique, we compared several anatomical structures in each CT image at the same anatomical position. As the position of the liver may shift according to respiratory movement, not only the shape of the liver but also the gallbladder and other prominent structures included in the CT images were compared to allow appropriate selection of a set of CT images. This novel technique was applied in 11 upper abdominal CT examinations. In CT images with a slice thickness of 7.0 or 7.5 mm, the percentage of image sets selected correctly by the automated procedure was 86.6+/-15.3% per case. In CT images with a slice thickness of 1.25 mm, the percentages of correct selection of image sets by the automated procedure were 79.4+/-12.4% (non-enhanced and arterial-phase CT images) and 86.4+/-10.1% (arterial- and delayed-phase CT images). This automated method is useful for assisting in interpreting CT images and in creating digital subtraction images.     

Potential usefulness of biological fingerprints in chest radiographs for automated patient recognition and identification

RATIONALE AND OBJECTIVES: The purpose of this study was to demonstrate the potential usefulness of "biological fingerprints" in chest radiographs for automated patient recognition and identification. MATERIALS AND METHODS: Thoracic fields, cardiac shadows, the superior mediastinum, lung apices, a part of the right lung, and the right lower lung that includes the costophrenic angle were used as biological fingerprints in chest radiographs. Each of the biological fingerprints in a current chest radiograph was used as a template for determination of the correlation value with the corresponding biological fingerprint in a previous chest radiograph for patient recognition and identification. The overall performance of the method developed was examined in terms of receiver operating characteristic curves. RESULTS: Receiver operating characteristic curves obtained with different biological fingerprints, except for the part of the right lung, indicated a high performance in identifying patients. These results showed that a new concept of biological fingerprints in radiologic images would be useful in patient recognition and identification. The low performance with the part of the right lung seems to be related to a general observation that this region does not usually include features unique to a specific patient. The performance of the artificial neural networks by use of a combination of five biological fingerprints was higher than results obtained with each biological fingerprint. CONCLUSION: The use of automated patient identification based on biological fingerprints in chest radiographs is promising for helping to discover misfiled patient images, especially in a picture archiving and communication system environment.     

Development of computerized method for automated classification of the body parts in digital radiographs

PURPOSE: In picture archiving and communication systems (PACS), the information on the body parts included in radiographs is often not or incorrectly recorded in an image header. In order to apply the computer-aided diagnosis (CAD) system in the PACS environment, the body parts in radiographs need to be recognized correctly by computer. The purpose of this study is to develop a computerized method for correctly classifying the body parts in digital radiographs based on a template matching technique.METHODS/MATERIALS: The image database used in this study was 1032 digital radiographs (14 x 17 inches) obtained with a computed radiography, and included 505 chest of postetroanterior view, 39 chest of lateral view, 241 abdomen, 108 pelvis, 10 upper limbs, 125 lower limbs, and 4 thoracic spine. In this method, test images were classified into four body parts, i.e., (1) chest, (2) abdomen, (3) pelvis, and (4) upper/lower limbs and thoracic spine. This computerized method was tested with 852 images, since 180 images were employed for creation of 98 templates, which represented the average radiographs for various body parts. Our approach was to examine the similarity of a given test image with templates by use of the cross-correlation values as the similarity measures. The body part of the test image was identified as the body part in the template yielding the maximum correlation value. Our method consisted of the following five steps. First, test images were classified into one of three groups; i.e. 1) chest and abdomen, 2) pelvis, and 3) upper/lower limbs and thoracic spine by using the templates obtained from images with the average size and position. Second, the remaining uncertain images were classified by using additional templates in various directions. Third, the chest and abdomen group was separated into two subgroups; i.e.chest and abdomen. Fourth, in order to classify some uncertain images, templates were shifted horizontally and vertically. Fifth, outer pixels of templates were eliminated to avoid the misclassification due to x-ray collimation. RESULTS: Our preliminary results indicated that the body parts for 850 cases (99.8%) were correctly classified with our method. CONCLUSIONS: This method would be useful for automated identification of the body parts in radiographs when various CAD systems would be implemented in the PACS environment.     

Integrating digital ICU viewing into the global working environment

We illustrate that to benefit from the advantages of Picture Archiving and Communication Systems (PACS) for the Intensive Care Unit (ICU), the PACS must be strongly integrated within the overall working environment. This includes adaptation of the PACS toward specific working patterns and integrating it with the Hospital Information System (HIS). This is reflected in our prototype system in different ways. The user interface of the viewing station is centered around often used patterns in ICU viewing. Information about bed occupancy is retrieved from the HIS and exploited in the viewing station. A digital connection between the phosphorplate scanner and the HIS ensures that images are correctly related to other patient information and to previous images. Using minor adaptations to the existing HIS, PACS and HIS have been made to cooperate in integrated presentation of images and radiological reports, as a step towards a multimedia medical information system. We discuss the relation between PACS and the global information environment, emphasizing organizational issues rather than technological aspects.     

Evaluation of the usefulness of modified biological fingerprints in chest radiographs for patient recognition and identification

We have been developing an image-searching method to identify misfiled images in a PACS server. Developing new biological fingerprints (BFs) that would reduce the influence of differences in positioning and breathing phases to improve the performance of recognition is desirable. In our previous studies, the whole lung field (WLF) that included the shadows of the body and lungs was affected by differences in positioning and/or breathing phases. In this study, we showed the usefulness of a circumscribed lung with a rectangular region of interest and the upper half of a chest radiograph as modified BFs. We used 200 images as hypothetically misfiled images. The cross-correlation identifies the resemblance between the BFs in the misfiled images and the corresponding BFs in the database images. The modified BFs indicated better results than did WLF in a receiver operating characteristic analysis; therefore, they could be used as identifiers for patient recognition and identification.     

Gradient correction and classification of CT lung images for the automated quantification of mosaic attenuation pattern

PURPOSE: The detection of density differences, or "mosaic attenuation pattern," on CT images may be difficult when the regional inhomogeneity of the density of the lung parenchyma is subtle. The purpose of this work was to develop a fully automated method for the reproducible quantification of the underattenuated areas of the lung parenchyma. This technique may be useful in increasing the precision of investigation of structure/function relationships. METHOD: Anatomical segmentation was achieved by a structure-filtering operator based on mathematical morphology. To compensate for the density gradient visible on lung CT scans, a model-based iterative deconvolution filter and an adaptive clustering algorithm were developed. Validation was performed with CT images from a lung phantom, 15 patients with constrictive obliterative bronchiolitis, and 8 normal subjects. RESULTS: The accuracy of the estimate of the density gradient on phantom studies was 93.3%. The automated quantification of the areas of decreased attenuation on scans of constrictive obliterative bronchiolitis was within 8.2% from the average scoring of two experienced observers. CONCLUSION: The proposed technique is fully automated and can accurately correct for density gradient and classify areas of decreased attenuation on lung CT images.     

Digital teaching library (DTL) development for radiography education

PurposeHaving access to a library of radiological images in the university setting is important for teaching and learning in diagnostic radiography. Modern modalities such as PETCT create data volumes rather than single static 2D images. A PACS repository of images alone does not constitute a teaching library without some text based searchable index. A review of several options for acquiring a digital teaching library (DTL) of such indexed DICOM data is presented.DiscussionThe data protection principles, current guidance and potential methods for migrating and cleansing large quantities of DICOM data from a clinical PACS prior to transfer to a university setting is discussed. The chosen method is described and the important enabling technology identified. Various methods of index construction are outlined and a method of migrating and cleansing HL7 data from a clinical RIS described.ResultsThree terabytes of de-normalised DICOM image files were cleansed of patient, staff and geographic identifiers, within the header tags and pixel data. These files were then migrated to an educational PACS hosted at a university. A searchable index database was created based on 90,200 reports and associated data, and 886,263 DICOM headers to enable meaningful results to be found from the 51,304 unique patient specific cases.ConclusionA large DTL in the university setting using PACS technology is becoming a valuable resource for teaching, learning and assessment.     

IHE profiles applied to regional PACS

PACS has been widely adopted as an image storage solution that perfectly fits the radiology department workflow and that can be easily extended to other hospital departments. Integrations with other hospital systems, like the Radiology Information System, the Hospital Information System and the Electronic Patient Record are fully achieved but still challenging aims. PACS also creates the perfect environment for teleradiology and teleworking setups. One step further is the regional PACS concept where different hospitals or health care enterprises share the images in an integrated Electronic Patient Record. Among the different solutions available to share images between different hospitals IHE (Integrating the Healthcare Enterprise) organization presents the Cross Enterprise Document Sharing profile (XDS) which allows sharing images from different hospitals even if they have different PACS vendors. Adopting XDS has multiple advantages, images do not need to be duplicated in a central archive to be shared among the different healthcare enterprises, they only need to be indexed and published in a central document registry. In the XDS profile IHE defines the mechanisms to publish and index the images in the central document registry. It also defines the mechanisms that each hospital will use to retrieve those images regardless on the Hospital PACS they are stored.     

The case for RIS/PACS integration

Why integrate PACS with the RIS? To improve workflow, of course, but what workflow? Much of the focus is on improving the flow of images for the radiologist, which is certainly a good thing to do, but what about the rest of the order process? Typical PACS system architecture begins with the HIS since this is where the correct patient demographic information and in many cases the orders originate. Correct patient and order information is sent from the HIS to the RIS using HL7 commands for Admission/Discharge/Transfer (ADT) and Order/Entry. HL7 is the communications protocol used in virtually all information systems. For the first step in communicating with PACS, patient and order information from the RIS is sent to a device called a PACS broker. This is necessary because most PACS systems do not support HL7 directly, and a translation is required. Images from each imaging modality are also sent to the broker using the DICOM standard. If an imaging modality does not support DICOM, then an additional box is used to convert the images to a DICOM file. The broker then sends completed DICOM files to the PACS for storage, distribution and viewing. That approach has worked well for the first stage of PACS utilization. However, experienced PACS users have identified the need to improve workflow, and many feel that closer communication with the RIS will solve many of the current limitations. This approach is sometimes called a "brokerless" solution but is probably better described as incorporating broker functions into the RIS. There are several potential advantages of incorporating the broker functions into the RIS: Access to all RIS information on patients, orders and results is available and can be used in many ways to improve workflow. Supporting all DICOM services directly from the RIS ensures that the latest and most complete information is always used. For example, DICOM Modality Worklists can be provided directly from the RIS, which guarantees that they are updated immediately. The RIS can manage the complete order workflow, not just images. License, implementation and support costs can be reduced by eliminating HL7 interfaces to an external broker. Managing workflow is the key to improved productivity and patient care from PACS. However, coordinated management of order workflow from the RIS and image workflow from the PACS is required to get the full benefit. The RIS has immediate and broad access to patient and order information. As a result, it is the natural place to take the lead in managing this coordinated workflow. While many older RIS and PACS systems are not yet capable of some of the integration features described above, several new systems are moving rapidly in that direction.     

Development of a method of automated extraction of biological fingerprints from chest radiographs as preprocessing of patient recognition and identification

This paper describes the development of an automated method of extraction of biological fingerprints (BFs), including detection of image orientation in chest radiographs. The image orientation of a target image was recognized and modified by examination of normalized cross-correlation values between a target image and averaged male and female images with correct image orientation. Templates of BFs were extracted from averaged images. Then, each BF in the target image was extracted from locations that showed the highest cross-correlation value between the template of BF in the averaged image and the corresponding BF in the target image. With our method, 100% (200/200) of image orientations were recognized correctly. If the orientation was recognized as inappropriate, our algorithm modified it into the appropriate chest image orientation. In addition, the BFs automatically extracted from target images were improved. This method would be useful in a preprocessing system for patient recognition and identification.     

PACS: the silent revolution

More than 15 years ago the idea of a Picture Archiving and Communication System (PACS) and a filmless hospital was created. In a PACS environment images are acquired, read, communicated and stored digitally. After many years of unsuccessful attempts and prototype installations, the necessary hardware components for a successful PACS installation are now readily available. However, software development is still lagging behind. Only very recently, software developers have realized that it is not sufficient for PACS software to store, communicate and display images, but that PACS software should effectively support the radiologist in the task of interpreting and communicating imaging findings through context-dependent default display arrangements, work-flow management, radiological and hospital information systems integration, and computer-assisted diagnosis. This review examines hard- and software requirements for efficient PACS operation, analyses costs and benefits, and discusses future developments. Received: 26 October 1998; Revision received: 11 January 1999; Accepted: 4 February 1999     

Orthopaedic measurements with computed radiography. Methodological development, accuracy, and radiation dose with special reference to the weight-bearing lower extremity and the dislocating patella

The overall aim of this study was to develop and evaluate a measurement system for computed radiography (CR) and Picture Archiving and Communication Systems (PACS), permitting measurements of long distances and angles in and between related images. The developed measurement system, which was based on the QUESTOR Precision Radiography (QPR) system, was applied to the weight-bearing knee with special reference to the dislocating patella. The QPR system modified for CR fulfilled the criteria for measuring the weight-bearing knee. The special measuring assistance tools that were developed were important for the implementation of CR and PACS, particularly in workstations programmed for musculoskeletal radiology. The energy imparted to the patient was reduced by 98% at the lowest exposure of the CR-system, compared with our conventional analogue method, without loss of diagnostic accuracy. The CR technique creates a possibility, to an extent not previously feasible, to differentiate the exposure parametres (and thus minimise the radiation dose to the patient) by carefully considering the purpose of the examination. A radiographic method for measuring the rotation of the femur and the tibia, the Q-angle, and the patellar translation was developed and applied to healthy volunteers. The introduced patellar variables have yielded new insights into the complex sequence of motions between the femur, tibia, and patella. The patients with a dislocating patella were subdivided into one "clean" group of spontaneous dislocations and one group with various traumas in the history, which thus resulted in two groups with distinct radiographic differences. The Q-angle was decreased in knees that had suffered dislocations, and the traditional surgical treatment with a further reduction of the Q-angle must be challenged. The use of clinical measurements of the Q-angle was not an optimal way to evaluate the mechanical alignment in the patellofemoral joint under physiological conditions. In this study, we have proved that the developed method for CR and PACS is a useful technique for measurements in and between related images, and is superior to the conventional analogue technique.     

Robust correction of spike noise: Application to diffusion tensor imaging

Echo‐planar imaging (EPI) ‐based diffusion tensor imaging (DTI) is particularly prone to spike noise. However, existing spike noise correction methods are impractical for corrupted DTI data because the methods correct the complex MRI signal, which is not usually stored on clinical MRI systems. The present work describes a novel Outlier Detection De‐spiking technique (ODD) that consists of three steps: detection, localization, and correction. Using automated outlier detection schemes, ODD exploits the data redundancy available in DTI data sets that are acquired with a minimum of six different diffusion‐weighted images (DWIs) with similar signal and noise properties. A mathematical formulation, describing the effects of spike noise on magnitude images, yields appropriate measures for an outlier detection scheme used for spike detection while a normalization‐dependent outlier detection scheme is used for spike localization. ODD performs accurately on diverse DTI data sets corrupted by spike noise and can be used for automated control of DTI data quality. ODD can also be extended to other MRI applications with data redundancy, such as dynamic imaging and functional MRI. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.     

Image storing system for radiation therapy (radiation oncology information system: ROIS) as a branch of diagnostic PACS; implementation and evaluation.

We have implemented the new system that is called as ROIS for storing medical images of the patients underwent radiotherapy as a branch of medium-scale diagnostic PACS. It was estimated that, for about nine years, we can store all medical images of the patients who received radiation therapy under the on-line storage condition. Further, we can retrieve all medical images of the radiotherapy patients on ROIS faster than conventional film library or on the diagnostic PACS, even if the patient had been treated many years ago. Implementation of ROIS provided us a great help in our clinical work.     

Multi-detector computed tomography and 3-dimensional imaging in a multi-vendor picture archiving and communications systems (PACS) environment

RATIONALE AND OBJECTIVES: To show the impact of the introduction of multi-detector computed tomography (CT) on radiologic workflow and to demonstrate how this reflects on picture archiving and communications systems (PACS) requirements. MATERIALS AND METHODS: Production measurements were obtained from different CT scanners (first two single-slice CT scanners; from December 2001 single and 4-slice CT; from April 2002 single and 16-slice CT) in number of patients from the radiologic information system. Implications on our PACS were recorded in terms of images and studies stored. Furthermore, our PACS design was made so that optimal use of 3-dimensional imaging within the radiologic workflow was possible. Finally, the number of non-diagnosed studies were recorded every day since the start of the transition to a filmless radiology department. RESULTS: This PACS design achieved a high level of integration between simple viewing and advanced 3-dimensional imaging and is optimized for handling large amounts of data. Overall increase of patients scanned with CT from January 2002-December 2003 was 54%. The number of series increased by 286% from December 2001-April 2003 and by 130% from April 2002-December 2003. From January 2002-February 2003, the number of images per patient increased from 175 to 450 (157%). Non-diagnosed studies decreased from about 100-120 before to practically zero after PACS implementation. CONCLUSION: PACS significantly increases productivity because of availability of the images and elimination of certain manual tasks. These results show that although the amount of examinations increases significantly with the introduction of MDCT, simultaneous introduction of PACS and filmless operation allows radiologists to handle the growth in workload.     

Distributing medical images with internet technologies: a DICOM web server and a DICOM java viewer.

With the advent of filmless radiology, it becomes important to be able to distribute radiologic images digitally throughout an entire hospital. A new approach based on World Wide Web technologies was developed to accomplish this objective. This approach involves a Web server that allows the query and retrieval of images stored in a Digital Imaging and Communications in Medicine (DICOM) archive. The images can be viewed inside a Web browser with use of a small Java program known as the DICOM Java Viewer, which is executed inside the browser. The system offers several advantages over more traditional picture archiving and communication systems (PACS): It is easy to install and maintain, is platform independent, allows images to be manipulated and displayed efficiently, and is easy to integrate with existing systems that are already making use of Web technologies. The system is user-friendly and can easily be used from outside the hospital if a security policy is in place. The simplicity and flexibility of Internet technologies makes them highly preferable to the more complex PACS workstations. The system works well, especially with magnetic resonance and computed tomographic images, and can help improve and simplify interdepartmental relationships in a filmless hospital environment.     

Does PACS improve diagnostic accuracy in chest radiograph interpretations in clinical practice?

Objectives

To assess the impact of a Picture Archiving and Communication System (PACS) on the diagnostic accuracy of the interpretation of chest radiology examinations in a “real life” radiology setting.

Materials and methods

During a period before PACS was introduced to radiologists, when images were still interpreted on film and reported on paper, images and reports were also digitally stored in an image database. The same database was used after the PACS introduction. This provided a unique opportunity to conduct a blinded retrospective study, comparing sensitivity (the main outcome parameter) in the pre and post-PACS periods.We selected 56 digitally stored chest radiograph examinations that were originally read and reported on film, and 66 examinations that were read and reported on screen 2 years after the PACS introduction. Each examination was assigned a random number, and both reports and images were scored independently for pathological findings. The blinded retrospective score for the original reports were then compared with the score for the images (the gold standard).

Results

Sensitivity was improved after the PACS introduction. When both certain and uncertain findings were included, this improvement was statistically significant. There were no other statistically significant changes.

Conclusion

The result is consistent with prospective studies concluding that diagnostic accuracy is at least not reduced after PACS introduction. The sensitivity may even be improved.     

Computer-aided detection of ischemic lesions related to subcortical vascular dementia on magnetic resonance images

RATIONALE AND OBJECTIVES: The purpose of this study was to develop an automated method for detection of the hyperintense ischemic lesions related to subcortical vascular dementia based on conventional magnetic resonance images (T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery images [FLAIR]). MATERIALS AND METHODS: Our proposed method was based on subtraction between the T1-weighted image and the FLAIR image. First, a brain region was extracted by an automated thresholding technique based on a linear discriminant analysis for a pixel value histogram. Next, for enhancement of ischemic lesions, the T1-weighted image was subtracted from the fluid-attenuated inversion-recovery image. Ischemic lesion candidates were identified using a multiple gray-level thresholding technique and a feature-based region-growing technique on the subtraction image. Finally, an artificial neural network trained with 15 image features of the ischemic candidates was used to remove false-positives. We applied our method to nine patients with vascular dementia (age range, 64-94 years, mean age, 69.4 years; four males and five females), who were scanned on a 1.5-T magnetic resonance unit. RESULTS: Our method achieved a sensitivity of 90% with 4.0 false-positives per slice in detection of ischemic lesions. The overlap measure between ischemic lesion areas obtained by our method and a neuroradiologist was 60.7% on average. The ratio of ischemic lesion area to the whole brain area obtained by our method correlated with that determined by a neuroradiologist with a correlation coefficient of 0.911. CONCLUSION: Our preliminary results suggest that the proposed method may have feasibility for evaluation of the ischemic lesion area ratio.