Deep Learning Algorithm for Simultaneous Noise Reduction and Edge Sharpening in Low-Dose CT Images:A Pilot Study Using Lumbar Spine CT

Objective@#The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. @*Materials and Methods@#This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AI TM , ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. @*Results@#Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). @*Conclusion@#DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.

Incremental Image Noise Reduction in Coronary CT Angiography Using a Deep Learning-Based Technique with Iterative Reconstruction

Objective@#To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. @*Materials and Methods@#We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction). @*Results@#Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons. @*Conclusion@#Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.

Application of Vendor-Neutral Iterative Reconstruction Technique to Pediatric Abdominal Computed Tomography

OBJECTIVE: To compare image qualities between vendor-neutral and vendor-specific hybrid iterative reconstruction (IR) techniques for abdominopelvic computed tomography (CT) in young patients. MATERIALS AND METHODS: In phantom study, we used an anthropomorphic pediatric phantom, age-equivalent to 5-year-old, and reconstructed CT data using traditional filtered back projection (FBP), vendor-specific and vendor-neutral IR techniques (ClariCT; ClariPI) in various radiation doses. Noise, low-contrast detectability and subjective spatial resolution were compared between FBP, vendor-specific (i.e., iDose1 to 5; Philips Healthcare), and vendor-neutral (i.e., ClariCT1 to 5) IR techniques in phantom. In 43 patients (median, 14 years; age range 1–19 years), noise, contrast-to-noise ratio (CNR), and qualitative image quality scores of abdominopelvic CT were compared between FBP, iDose level 4 (iDose4), and ClariCT level 2 (ClariCT2), which showed most similar image quality to clinically used vendor-specific IR images (i.e., iDose4) in phantom study. Noise, CNR, and qualitative imaging scores were compared using one-way repeated measure analysis of variance. RESULTS: In phantom study, ClariCT2 showed noise level similar to iDose4 (14.68–7.66 Hounsfield unit [HU] vs. 14.78–6.99 HU at CT dose index volume range of 0.8–3.8 mGy). Subjective low-contrast detectability and spatial resolution were similar between ClariCT2 and iDose4. In clinical study, ClariCT2 was equivalent to iDose4 for noise (14.26–17.33 vs. 16.01–18.90) and CNR (3.55–5.24 vs. 3.20–4.60) (p > 0.05). For qualitative imaging scores, the overall image quality ([reader 1, reader 2]; 2.74 vs. 2.07, 3.02 vs. 2.28) and noise (2.88 vs. 2.23, 2.93 vs. 2.33) of ClariCT2 were superior to those of FBP (p 0.05). CONCLUSION: Vendor-neutral IR technique shows image quality similar to that of clinically used vendor-specific hybrid IR technique for abdominopelvic CT in young patients.

Imaging Informatics: A New Horizon for Radiology in the Era of Artificial Intelligence, Big Data, and Data Science

We are witnessing the big wave of Industrial Revolution 4.0, enabled by artificial intelligence (AI) and big data, which has shaken the entire industry and day-to-day life as well as rapidly changed the landscapes of related academic disciplines. After the introduction of genome sequencing and analysis technology, biology and medical sciences have been rapidly transforming into data science. Radiology is facing a challenging period of transformation into a data science. This review article draws attention to imaging informatics as a vehicle to open a new horizon and to drive to the future path for radiology in the AI and big data era. We introduce the basic concepts of imaging informatics and consider the informatics features of picture archiving and communication system and digital imaging and communications in medicine. We discuss the concepts and differences of radiogenomics and radiomics, which are important specialties of imaging informatics. We introduce the basics of AI and its recent applications in radiology as well as requirements for the successful construction of big data for imaging informatics. We conclude by discussing unresolved issues, potential solutions, and directions for future developments.

Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software

OBJECTIVE: The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. MATERIALS AND METHODS: MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. RESULTS: Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant. CONCLUSION: The use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics.

Implementation of Consolidated HIS: Improving Quality and Efficiency of Healthcare / 대한의료정보학회지

OBJECTIVES: Adoption of hospital information systems offers distinctive advantages in healthcare delivery. First, implementation of consolidated hospital information system in Seoul National University Hospital led to significant improvements in quality of healthcare and efficiency of hospital management. METHODS: The hospital information system in Seoul National University Hospital consists of component applications: clinical information systems, clinical research support systems, administrative information systems, management information systems, education support systems, and referral systems that operate to generate utmost performance when delivering healthcare services. RESULTS: Clinical information systems, which consist of such applications as electronic medical records, picture archiving and communication systems, primarily support clinical activities. Clinical research support system provides valuable resources supporting various aspects of clinical activities, ranging from management of clinical laboratory tests to establishing care-giving procedures. CONCLUSIONS: Seoul National University Hospital strives to move its hospital information system to a whole new level, which enables customized healthcare service and fulfills individual requirements. The current information strategy is being formulated as an initial step of development, promoting the establishment of next-generation hospital information system.

Image Quality Evaluation of Digital X-Ray Detector Using Amorphous Selenium Layer and Amorphous Silicon TFT Array / 의학물리

In this study, we have conducted characterization of imaging performance for a flat panel digital X-ray detector using amorphous Selenium and a-Si TFT which was developed by the authors. The procedures for characterization were in concordance with internationally recommended standards such as IEC (international electrotechnical commission). The measures used for imaging performance characterization include response characteristic, modulation transfer function (MTF), detective quantum efficiency (DQE), noise power spectrum (NPS), and quantum limited performance. The measured DQEs at lowest and highest spatial frequencies were 40% and 25% respectively, which was superior to that of commercial products by overseas vendor. The MTF values were significantly superior to that of CR and indirect type DRs. The quantum limited performance showed the detector was limited by quantum noise at the entrance exposure level below 0.023 mR, which is sufficiently low for general X-ray examination.

Diagnostic Performance of Combined Single Photon Emission Computed Tomographic Scintimammography and Ultrasonography Based on Computer-Aided Diagnosis for Breast Cancer / 핵의학분자영상

PURPOSE: We investigated whether the diagnostic performance of SPECT scintimammography (SMM) can be improved by adding computer-aided diagnosis (CAD) of ultrasonography (US). MATERIALS AND METHODS: We reviewed breast SPECT SMM images and corresponding US images from 40 patients with breast masses (21 malignant and 19 benign tumors). The quantitative data of SPECT SMM were obtained as the uptake ratio of lesion to contralateral normal breast. The morphologic features of the breast lesions on US were extracted and quantitated using the automated CAD software program. The diagnostic performance of SPECT SMM and CAD of US alone was determined using receiver operating characteristic (ROC) curve analysis. The best discriminating parameter (D-value) combining SPECT SMM and the CAD of US was created. The sensitivity, specificity and accuracy of combined two diagnostic modalities were compared to those of a single one. RESULTS: Both SPECT SMM and CAD of US showed a relatively good diagnostic performance (area under curve = 0.846 and 0.831, respectively). Combining the results of SPECT SMM and CAD of US resulted in improved diagnostic performance (area under curve =0.860), but there was no statistical differerence in sensitivity, specificity and accuracy between the combined method and a single modality. CONCLUSION: It seems that combining the results of SPECT SMM and CAD of breast US do not significantly improve the diagnostic performance for diagnosis of breast cancer, compared with that of SPECT SMM alone. However, SPECT SMM and CAD of US may complement each other in differential diagnosis of breast cancer.

Artificial Intelligence Aiding the Thin-section CT Diagnosis of Diffuse Pulmonary Diseases

PURPOSE: We wanted to develop and test an artificial intelligence (AI) to assist physicians in making the thin-section CT diagnosis of diffuse pulmonary diseases. MATERIALS AND METHODS: The AI was composed of knowledge bases (KB) of 12 diffuse pulmonary diseases and an inference engine (IE). The KB of a disease included both the inclusion criteria (IC) and the exclusion criteria (EC), which were the clinical or thin-section CT findings that were known to be present or absent in that particular disease, respectively. From imputing the clinical or thin-section CT findings by the operator who was reading the thin-section CT, AI instantly executed the following two steps. First, the IE eliminated all diseases from the list which the EC had for those particular findings. Next, from a list of remaining diseases, the AI selected those diseases having those findings in its IC to formulate the 1st-step differential diagnosis (DD1). For the differential diagnosis in the next step, the reader could choose one more clinical or thin-section CT finding from the new list: [(all the findings in the IC or EC of DD1) - (the findings in the IC common to all the DD1s)]. The reader could proceed even further if needed. The system was tested on 10 radiology residents who solved 24 problems (two problems for each of 12 diffuse pulmonary diseases) without and then with the aid of the AI. The scores were compared using the Wilcoxon signed rank test. RESULTS: An AI was made; it was composed of 280 rules (214 IC and 66 EC) and three interfaces (two for program management and another for problem solving). Contestants scored higher (p = 0.0078) using the AI (167 vs. 110 respectively), and they responded that they felt that the program was helpful in making decisions. CONCLUSION: AI appeared to be helpful in making thin-section CT diagnosis.

Quantitative Differences between X-Ray CT-Based and 137Cs-Based Attenuation Correction in Philips Gemini PET/CT / 대한핵의학회잡지

PURPOSE: There are differences between Standard Uptake Value (SUV) of CT attenuation corrected PET and that of 137Cs. Since various causes lead to difference of SUV, it is important to know what is the cause of these difference. Since only the X-ray CT and 137Cs transmission data are used for the attenuation correction, in Philips GEMINI PET/CT scanner, proper transformation of these data into usable attenuation coefficients for 511 keV photon has to be ascertained. The aim of this study was to evaluate the accuracy in the CT measurement and compare the CT and 137Cs-based attenuation correction in this scanner. METHODS: For all the experiments, CT was set to 40 keV (120 kVp) and 50 mAs. To evaluate the accuracy of the CT measurement, CT performance phantom was scanned and Hounsfield units (HU) for those regions were compared to the true values. For the comparison of CT and 137Cs-based attenuation corrections, transmission scans of the elliptical lung-spine-body phantom and electron density CT phantom composed of various components, such as water, bone, brain and adipose, were performed using CT and 137Cs. Transformed attenuation coefficients from these data were compared to each other and true 511 keV attenuation coefficient acquired using 68Ge and ECAT EXACT 47 scanner. In addition, CT and 137Cs-derived attenuation coefficients and SUV values for 18F-FDG measured from the regions with normal and pathological uptake in patients' data were also compared. RESULTS: HU of all the regions in CT performance phantom measured using GEMINI PET/CT were equivalent to the known true values. CT based attenuation coefficients were lower than those of 68Ge about 10% in bony region of NEMA ECT phantom. Attenuation coefficients derived from 137Cs data was slightly higher than those from CT data also in the images of electron density CT phantom and patients' body with electron density. However, the SUV values in attenuation corrected images using 137Cs were lower than images corrected using CT. Percent difference between SUV values was about 15%. CONCLUSION: Although the HU measured using this scanner was accurate, accuracy in the conversion from CT data into the 511 keV attenuation coefficients was limited in the bony region. Discrepancy in the transformed attenuation coefficients and SUV values between CT and 137Cs-based data shown in this study suggests that further optimization of various parameters in data acquisition and processing would be necessary for this scanner.

Automated Lung Nodule Detection at Low-Dose CT: Preliminary Experience

OBJECTIVE: To determine the usefulness of a computer-aided diagnosis (CAD) system for the automated detection of lung nodules at low-dose CT. MATERIALS AND METHODS : A CAD system developed for detecting lung nodules was used to process the data provided by 50 consecutive low-dose CT scans. The results of an initial report, a second look review by two chest radiologists, and those obtained by the CAD system were compared, and by reviewing all of these, a gold standard was established. RESULTS : By applying the gold standard, a total of 52 nodules were identified (26 with a diameter 5 mm). Compared to an initial report, four additional nodules were detected by the CAD system. Three of these, identified only at CAD, formed part of the data used to derive the gold standard. For the detection of nodules > 5 mm in diameter, sensitivity was 77% for the initial report, 88% for the second look review, and 65% for the CAD system. There were 8.0+/-5.2 false-positive CAD results per CT study. CONCLUSION : These preliminary results indicate that a CAD system may improve the detection of pulmonary nodules at low-dose CT.

Analysis of Signal Intensity Curve on Dynamic Contrast-Enhanced MR Imaging of Postoperative Scars in Rabbits:Comparison of Gadopentetate Dimeglumine and 24-gadolinium-tetraazacy-clododecanetetraacetic acid (DOTA)-dendrimer

PURPOSE: To compare the enhancement patterns of 24-gadolinium-tetrazacyclodode-cane tetracetic acid (DOTA)-dendrimer (Gadomer-17) with those of gadopentetate dimeglumine (Magnevist) in postoperative scars in rabbits. MATERIALS AND METHODS: Twelve rabbit thighs with experimentally induced postoperative scars underwent dynamic contrast-enhanced MR imaging with both Gadomer-17 and gadopentetate dimeglumine at a 24-hr interval at one (n = 10), two (n = 8) and three months (n=4) after scar induction. The enhancement and the ratios of lesions at each time point, peak enhancement ratios, and the slope and shape of curves were assessed. RESULTS: At all time points, enhancement ratios were significantly lower after the injection of Gadomer-17 than with gadopentetate dimeglumine (p<0.05). Peak enhancement ratios were significantly lower with Gadomer-17 (1.29+/-0.15) than with gadopentetate dimeglumine (1.61+/-0.31) (p<0.01). The slope values were 2.99%/min+/-2.72 after Gadomer-17 injection and 8.99%/min+/-7.32 after gadopentetate dimeglumine injection (p<0.01). The enhancement ratio curves showed mostly the plateau pattern with Gadomer-17 (90.9%), while for gadopentetate dimeglumine, the curve pattern was either plateau (50%) or washout (50%). Difference in enhancement characteristics between the two contrast agents were most pronounced for one-month scars. CONCLUSION: With Gadomer-17, weaker enhancement and the plateau pattern were found in postoperative scars, whereas stronger enhancement and either washout or the plateau pattern were found with gadopentetate dimeglumine.

Impact of Image Post-Processing on PACS Workstation: Dynamic Range Suppression(DRS) of Chest Radiographs

PURPOSE: To investigate the impact of post-processing on a PACS workstation before and after use of thedynamic range suppression method for the normal chest radiographs. MATERIALS AND METHODS: Forty normal chestradiographs of healthy adult volunteers aged 20 to 33 (average 27; M:F = 29:11) were acquired by FCR using adigital interface and then transferred to an in-house-developed PACS workstation. The image size of computed chestradiographs was 7.5MB with 1760 x 2140 matrix. An image enhancement processing named DRS, developed by theauthors, was applied to the acquired images and generated a total of 40 chest radiographs. These were presented tothree groups of observers, each consisting of one radiologist and one technician on the PACS workstation, whichhad two monitors of 1712 x 2100 resolution. So that external light would not affect the visibility of imagesduring observation, these were displayed in a light-controlled room. The J.J.Vucich method, suitably modified, wasused to evaluate the anatomical structures and physical parameters of processed and unprocessed radiographs. Usinga percentage scale, the observers evaluated both anatomical sections (seven anatomical items : cortical margins ofribs, left diaphragms, thoracic vertebrae, trachea, pulmonary vasculature, trabeculae of ribs and clavicle,diaphragm outline) and physical sections (four items : contrast, graininess, density, detail). The results for thethree groups, both before and after DRS processing, were then compared. RESULTS: There was a statisticallysignificant difference between the three groups: in the anatomical section, 78.64 before DRS and 82.55 after ; andin the physical section, 75.48 and 79.78 (p<0.05). The average values of all items were 77.06 before DRS and 81.17after (p<0.05). CONCLUSION: Post-processing of computed chest radiographs on the PACS workstation improves boththe visibility of anatomical features and general image quality. Thus, in a PACS environment, it can be a usefultool for enhancing the diagnostic efficacy of radiography.

Impact of Image Post-Processing on PACS Workstation: Dynamic Range Suppression(DRS) of Chest Radiographs

PURPOSE: To investigate the impact of post-processing on a PACS workstation before and after use of thedynamic range suppression method for the normal chest radiographs. MATERIALS AND METHODS: Forty normal chestradiographs of healthy adult volunteers aged 20 to 33 (average 27; M:F = 29:11) were acquired by FCR using adigital interface and then transferred to an in-house-developed PACS workstation. The image size of computed chestradiographs was 7.5MB with 1760 x 2140 matrix. An image enhancement processing named DRS, developed by theauthors, was applied to the acquired images and generated a total of 40 chest radiographs. These were presented tothree groups of observers, each consisting of one radiologist and one technician on the PACS workstation, whichhad two monitors of 1712 x 2100 resolution. So that external light would not affect the visibility of imagesduring observation, these were displayed in a light-controlled room. The J.J.Vucich method, suitably modified, wasused to evaluate the anatomical structures and physical parameters of processed and unprocessed radiographs. Usinga percentage scale, the observers evaluated both anatomical sections (seven anatomical items : cortical margins ofribs, left diaphragms, thoracic vertebrae, trachea, pulmonary vasculature, trabeculae of ribs and clavicle,diaphragm outline) and physical sections (four items : contrast, graininess, density, detail). The results for thethree groups, both before and after DRS processing, were then compared. RESULTS: There was a statisticallysignificant difference between the three groups: in the anatomical section, 78.64 before DRS and 82.55 after ; andin the physical section, 75.48 and 79.78 (p<0.05). The average values of all items were 77.06 before DRS and 81.17after (p<0.05). CONCLUSION: Post-processing of computed chest radiographs on the PACS workstation improves boththe visibility of anatomical features and general image quality. Thus, in a PACS environment, it can be a usefultool for enhancing the diagnostic efficacy of radiography.

Computed Radiogra p hy in Skeletal Imaging: Visual Assessment of Compressed Image Quality

PURPOSE: To evaluate the effect of lossy image compression on skeletal images and to determine the compression ratio which does not lead to difficulties when images are interpreted for diagnostic purposes. MATERIALS AND METHODS: Thirty-two computed radiographs (CR) of osteolytic bone tumors were obtained from Picture Archiving and Communication System. They were compressed to three different levels (Q factor 30, 70, 120) using the JPEG (Joint Photographic Expert Group) technique. Ninety-six pairs of uncompressed and compressed images were randomly ordered and then serially displayed on two high-resolution monitors. During a side-by-side review, three radiologists independently compared each pair of uncompressed and compressed images, and these were rated once using a five-category ordinal scale for tumor-related findings, linear structures, and soft tissues. The reviewers were then obliged to decide which image in each pair was of better quality, and finally, they were asked to evaluate the influence of image compression on diagnostic accuracy. RESULTS: The reviewers found no significant difference in image quality between uncompressed and compressed images with a Q factor 30. Compressed images with a Q factor of 70 or 120, however, revealed clinically relevant degradation. Among 96 observations of compressed images, 15 with a Q factor of 70 and 35 with a Q factor of 120 were considered inadequate for clinical purposes. CONCLUSION: If the JPEG technique is used, compressed CR skeletal images with a Q factor of 30 are acceptable for clinical application. Compressed images with a Q factor of 70 or 120 may, however, cause diagnostic difficulty and thus cannot be used for clinical purposes.

Transmission of DICOM 3.0 type MR data to the personal computer in the hospital without PACS

PURPOSE: To transmit DICOM data to a personal computer in the hospital without PACS, and estimate theusefulness of digital image management and its convenience for physicians through transmitted file size,transmission time and quality of transmitted images. MATERIALS AND METHODS: The raw data of three brain MRI andlumbar spine MRI were transmitted from an MR system to a personal computer via Ethernet TCP/IP connection. Thefile size and transmission time of transmitted images were measured according to the matrix number. Threeboard-certified radiologists compared the image quality of the transmitted and scanned images. RESULTS: Thetransmission of DICOM data to the personal computer was successful and the transmitted images and their headerinformation were displayed by various personal computer-based DICOM viewing programs. The file size andtransmission time of the 256 and 512 matrix images were 136 Kbyte, 2.17 seconds/slice and 520 Kbyte, 4.37seconds/slice, respectively. All radiologists regarded the transmitted brain MRI images as superior. Oneradiologist considered the transmitted lumbar spine MRI images superior, while others decided that the quality oftransmitted and scanned images was the same. CONCLUSION: The transmission of DICOM format image data to apersonal computer through an appropriate DICOM receiving program is useful for managing digital images andconvenient for physicians in the hospital without PACS.

Dynamic and Interactive Web-based Radiology Teaching File Using Layer and JavaScript

PURPOSE: To improve the Web-based radiology teaching file by means of a dynamic and interactive interfaceusing Layer and JavaScript. MATERIALS AND METHODS: The radiology teaching file for medical students at the author's medical school was used. By mean of a digital camera, films were digitized and compressed to JointPhotographic Expert Group (JPEG) format. Layers which had arrows or lines pointing out lesions and anatomicalstructures were converted to transparent CompuServe Graphics Interchange Format (GIF). Basically, HyperTextMark-up Language (HTML) was used for each Web page. Using JavaScript, Layers were made to be overlapped withradiologic images at the user's request. RESULTS: Each case page consisted of radiologic images and texts foradditional information and explanation. By moving the cursor or clicking onto key words, indicators pointing outcorresponding lesions and anatomical strutures were automatically shown on radiologic images. CONCLUSION: Although not compatible with some Web-browsers, a dynamic and interactive interface using Layer and JavaScript haslittle effect on the time needed for data transfer through a network, and is therefore an effective method ofaccessing radiologic images using the World-Wide Web and using these for teaching and learning.

Radiological Findings and Interventions for Iatrogenic Vascular Injuries

PURPOSE: To evaluate the radiological findings and effectiveness of radiological interventions in patientswith iatrogenic vascular injuries. MATERIALS AND METHODS: We analyzed 50 patients with iatrogenic vascularinjuries treated with radiological intervention. The causes of injuries were surgery(n=20), cardiovascularintervention(n=15), non-cardiovascular radiological intervention(n=14), and endoscopic intervention(n=1). Theinjury had resulted in hemorrhage in 35 cases. The iliac and/or femoral, hepatic, and renal vessels were commonlyinjured. Angiography, ultrasonography with Doppler examination, CT, and CT angiography were performed to diagnosevascular injuries and guide the radiological intervention. The mean follow-up period was 23 months and in 16 caseswas more than one year. RESULTS: The major radiological findings were extravasation, pseudoaneurysm,arteriovenous shunt, or vascular obstruction. To control these lesions, radiological interventions such asembolization(n=36), local urokinase administration, stent insertion, foreign body removal, ultrasonography-guidedcompression, or stent-graft insertion were performed. The clinical problems were immediately controlled by thesingle trials of radiological interventions and did not recur in 40 cases (80%). CONCLUSION: Radiologicalexaminations and interventions are useful in cases with iatrogenic vascular injuries.

Multimedia Radiology Self-Learning Course on the World Wide Web

PURPOSE: The creation and maintainance of radiology teaching materials is both laborious and very time-consuming but at a teaching hospital is important. Through use of the technology offered by today's worldwide web, this problem can be efficiently solved, and on this basis, we divised a multimedia radiology self-learning course for abdominal ultrasound and CT. MATERIALS AND METHODS: A combination of video and audio tapes has been used as teaching material; the authors digitized and converted these to Hypertext Mark-up Language(HTML) format. Films were digitized with a digital camera and compressed to Joint Photographic Expert Group (JPEG) format, while audio tapes were digitized with a sound recorder and compressed to Real Audio format. RESULTS: The self-learning course for abdominal ultrasound consists of 14 steps, and that for abdominal CT, 19 steps. Both provide images, voice anrrations, and related texts and graphics. The learner can navigate the course at his/her own speed, repeating or skipping any part, as required. CONCLUSION: 'Multimedia on the Worldwide Web' will facilitate easy management and maintenauce of a self-learning course. To make this more suitable for practical use, continual upgrading on the basis of experience is needed.

Airway Responses to Bronchoprovocation Using High-Resolution Computed Tomography in Patients with Bronchial Asthma / 결핵

BACKGROUND: Bronchial hyperresponsiveness and abnormal response such as a loss of distensi- bility are pathophysiologic characteristics if bronchial asthma. The only means of direct in vivo measurement of airway size had been a tantalium bronchography, until high-resolution computed tomography(HRCT) enabled to measure noninvasively two dimensional airway area more accurately and reliably. METHOD: To investigate airway area responses to bronchial provocation with methacholine and evaluate the major sites of bronchial constriction in patients with bronchial asthma. We examined HRCT scans in five patients with bronchial asthma who had significant bronchoconstriction(20% or more decrease in FEV1) using CT scanner(5,000T CT, Shimadzu Co, Japan) before and in 3~5 min. after methacholine inhalation. Airways which were matched by parenchymal anatomic landmarks in each patient before and after methacholine inhalation were measured using film scanner(TZ-3X scanner; Truvel Co. Chatsworth CA, USA) and a semiautomated region growing method. RESULTS: 1) We identified 9 to 12 airways in each patient which were matched by parenchymal anatomic landmarks before and after methacholine inhalation. 2) Airway responses to methacholine are quite different even in a patient. 3) The constriction of small airways(average diameter 2 mm; area >3.14 mm2), 53.8% (4.4;SEM, n=10), but not significantly different(p>0.05). 4) There was no significant difference in the degree of constriction between upper(44.3% +5.8; mean + SEM, n=30) and lower lung regions(56.7% +4.5, n=23). CONCLUSIONS: Thus airway responses to methacholine bronchoprovocation is quite variable in a patient with bronchial asthma and has no typical pattern in patients with bronchial asthma.