Diagnostic imaging costs before and after digital tomosynthesis implementation in patient management after detection of suspected thoracic lesions on chest radiography

Automatic Osteoporosis Screening System Using Radiomics and Deep Learning from Low-Dose Chest CT Images

OBJECTIVE

Develop two fully automatic osteoporosis screening systems using deep learning (DL) and radiomics (Rad) techniques based on low-dose chest CT (LDCT) images and evaluate their diagnostic effectiveness.

METHODS

In total, 434 patients who underwent LDCT and bone mineral density (BMD) examination were retrospectively enrolled and divided into the development set (n = 333) and temporal validation set (n = 101). An automatic thoracic vertebra cancellous bone (TVCB) segmentation model was developed. The Dice similarity coefficient (DSC) was used to evaluate the segmentation performance. Furthermore, the three-class Rad and DL models were developed to distinguish osteoporosis, osteopenia, and normal bone mass. The diagnostic performance of these models was evaluated using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA).

RESULTS

The automatic segmentation model achieved excellent segmentation performance, with a mean DSC of 0.96 ± 0.02 in the temporal validation set. The Rad model was used to identify osteoporosis, osteopenia, and normal BMD in the temporal validation set, with respective area under the receiver operating characteristic curve (AUC) values of 0.943, 0.801, and 0.932. The DL model achieved higher AUC values of 0.983, 0.906, and 0.969 for the same categories in the same validation set. The Delong test affirmed that both models performed similarly in BMD assessment. However, the accuracy of the DL model is 81.2%, which is better than the 73.3% accuracy of the Rad model in the temporal validation set. Additionally, DCA indicated that the DL model provided a greater net benefit compared to the Rad model across the majority of the reasonable threshold probabilities Conclusions: The automated segmentation framework we developed can accurately segment cancellous bone on low-dose chest CT images. These predictive models, which are based on deep learning and radiomics, provided comparable diagnostic performance in automatic BMD assessment. Nevertheless, it is important to highlight that the DL model demonstrates higher accuracy and precision than the Rad model.

AI-based computer-aided diagnostic system of chest digital tomography synthesis: Demonstrating comparative advantage with X-ray-based AI systems

BACKGROUND

Compared with chest X-ray (CXR) imaging, which is a single image projected from the front of the patient, chest digital tomosynthesis (CDTS) imaging can be more advantageous for lung lesion detection because it acquires multiple images projected from multiple angles of the patient. Various clinical comparative analysis and verification studies have been reported to demonstrate this, but there is no artificial intelligence (AI)-based comparative analysis studies. Existing AI-based computer-aided detection (CAD) systems for lung lesion diagnosis have been developed mainly based on CXR images; however, CAD-based on CDTS, which uses multi-angle images of patients in various directions, has not been proposed and verified for its usefulness compared to CXR-based counterparts.

BACKGROUND AND OBJECTIVE

This study develops and tests a CDTS-based AI CAD system to detect lung lesions to demonstrate performance improvements compared to CXR-based AI CAD.

METHODS

We used multiple (e.g., five) projection images as input for the CDTS-based AI model and a single-projection image as input for the CXR-based AI model to compare and evaluate the performance between models. Multiple/single projection input images were obtained by virtual projection on the three-dimensional (3D) stack of computed tomography (CT) slices of each patient's lungs from which the bed area was removed. These multiple images result from shooting from the front and left and right 30/60∘. The projected image captured from the front was used as the input for the CXR-based AI model. The CDTS-based AI model used all five projected images. The proposed CDTS-based AI model consisted of five AI models that received images in each of the five directions, and obtained the final prediction result through an ensemble of five models. Each model used WideResNet-50. To train and evaluate CXR- and CDTS-based AI models, 500 healthy data, 206 tuberculosis data, and 242 pneumonia data were used, and three three-fold cross-validation was applied.

RESULTS

The proposed CDTS-based AI CAD system yielded sensitivities of 0.782 and 0.785 and accuracies of 0.895 and 0.837 for the (binary classification) performance of detecting tuberculosis and pneumonia, respectively, against normal subjects. These results show higher performance than the sensitivity of 0.728 and 0.698 and accuracies of 0.874 and 0.826 for detecting tuberculosis and pneumonia through the CXR-based AI CAD, which only uses a single projection image in the frontal direction. We found that CDTS-based AI CAD improved the sensitivity of tuberculosis and pneumonia by 5.4% and 8.7% respectively, compared to CXR-based AI CAD without loss of accuracy.

CONCLUSIONS

This study comparatively proves that CDTS-based AI CAD technology can improve performance more than CXR. These results suggest that we can enhance the clinical application of CDTS. Our code is available at https://github.com/kskim-phd/CDTS-CAD-P.

Digital Tomosynthesis as a Problem-Solving Technique to Confirm or Exclude Pulmonary Lesions in Hidden Areas of the Chest

Objectives: To evaluate the capability of digital tomosynthesis (DTS) to characterize suspected pulmonary lesions in the so-called hidden areas at chest X-ray (CXR). Materials and Methods: Among 726 patients with suspected pulmonary lesions at CXR who underwent DTS, 353 patients (201 males, 152 females; age 71.5 ± 10.4 years) revealed suspected pulmonary lesions in the apical, hilar, retrocardiac, or paradiaphragmatic lung zones and were retrospectively included. Two readers analyzed CXR and DTS images and provided a confidence score: 1 or 2 = definitely or probably benign pulmonary or extra-pulmonary lesion, or pulmonary pseudo-lesion deserving no further diagnostic work-up; 3 = indeterminate lesion; 4 or 5 = probably or definitely pulmonary lesion deserving further diagnostic work-up by CT. The nature of DTS findings was proven by CT (n = 108) or CXR during follow-up (n = 245). Results: In 62/353 patients the suspected lung lesions were located in the lung apex, in 92/353 in the hilar region, in 59/353 in the retrocardiac region, and in 140/353 in the paradiaphragmatic region. DTS correctly characterized the CXR findings as benign pulmonary or extrapulmonary lesion (score 1 or 2) in 43/62 patients (69%) in the lung apex region, in 56/92 (61%) in the pulmonary hilar region, in 40/59 (67%) in the retrocardiac region, and in 106/140 (76%) in the paradiaphragmatic region, while correctly recommending CT in the remaining cases due to the presence of true solid pulmonary lesion, with the exception of 22 false negative findings (60 false positive findings). DTS showed a significantly (p < 0.05) increased sensitivity, specificity, and overall diagnostic accuracy and area under ROC curve compared to CXR alone. Conclusions: DTS allowed confirmation or exclusion of the presence of true pulmonary lesions in the hidden areas of the chest.

Diagnostic Accuracy of Chest Digital Tomosynthesis in Patients Recovering after COVID-19 Pneumonia

Purpose: To assess the diagnostic accuracy of traditional chest X-ray (CXR) and digital tomosynthesis (DTS) compared to computed tomography (CT) in detecting pulmonary interstitial changes in patients having recovered from severe COVID-19. Materials and Methods: This was a retrospective observational study, and received local ethics committee approval. Patients suspected of having COVID-19 pneumonia upon emergency department admission between 1 March and 31 August 2020, and who underwent CXR followed by DTS and CT, were considered. Inclusion criteria were as follows: (1) patients with previous SARS-CoV-2 infection proven by a positive RT-PCR on nasopharyngeal swabs performed upon admission to the hospital, and with complete clinical recovery; (2) a diagnosis of SARS-CoV-2-related ARDS, according to the Berlin criteria, during hospitalization; (3) no recent history of other lung disease; and (4) complete imaging follow-up by CXR, DTS, and CT for at least 6 months and up to one year. Analysis of DTS images was carried out independently by two radiologists with 16 and 10 years of experience in chest imaging, respectively. The following findings were evaluated: (1) ground-glass opacities (GGOs); (2) air-space consolidations with or without air bronchogram; (3) reticulations; and (4) linear consolidation. Indicators of diagnostic performance of RX and digital tomosynthesis were calculated using CT as a reference. All data were analyzed using R statistical software (version 4.0.2, 2020). Results: Out of 44 patients initially included, 25 patients (17 M/8 F), with a mean age of 64 years (standard deviation (SD): 12), met the criteria and were included. The overall average numbers of findings confirmed by CT were GGOs in 11 patients, lung consolidations in 8 patients, 7 lung interstitial reticulations, and linear consolidation in 20 patients. DTS showed a significantly higher diagnostic accuracy compared to CXR in recognizing interstitial lung abnormalities—especially GGOs (p = 0.0412) and linear consolidations (p = 0.0009). The average dose for chest X-ray was 0.10 mSv (0.07–0.32), for DTS was 1.03 mSv (0.74–2.00), and for CT scan was 3 mSv. Conclusions: According to our results, DTS possesses a high diagnostic accuracy, compared with CXR, in revealing lung fibrotic changes in patients who have recovered from COVID-19 pneumonia.

Digital tomosynthesis and ground glass nodules: Optimization of acquisition protocol. A phantom study

INTRODUCTION

Ground-glass nodules may be the expression of benign conditions, pre-invasive lesions or malignancies. The aim of our study was to evaluate the capability of chest digital tomosynthesis (DTS) in detecting pulmonary ground-glass opacities (GGOs).

METHODS

An anthropomorphic chest phantom and synthetic nodules were used to simulate pulmonary ground-glass nodules. The nodules were positioned in 3 different regions (apex, hilum and basal); then the phantom was scanned by multi-detector CT (MDCT) and DTS. For each set (nodule-free phantom, nodule in apical zone, nodule in hilar zone, nodule in basal zone) seven different scans (n = 28) were performed varying the following technical parameters: Cu-filter (0.1-0.3 mm), dose rateo (10-25) and X-ray tube voltage (105-125 kVp). Two radiologists in consensus evaluated the DTS images and provided in agreement a visual score: 1 for unidentifiable nodules, 2 for poorly identifiable nodules, 3 for nodules identifiable with fair certainty, 4 for nodules identifiable with absolute certainty.

RESULTS

Increasing the dose rateo from 10 to 15, GGOs located in the apex and in the basal zone were better identified (from a score = 2 to a score = 3). GGOs located in the hilar zone were not visible even with a higher dose rate. Intermediate density GGOs had a good visibility score (score = 3) and it did not improve by varying technical parameters. A progressive increase of voltage (from 105 kVp to 125 kVp) did not provide a better nodule visibility.

CONCLUSION

DTS with optimized technical parameters can identify GGOs, in particular those with a diameter greater than 10 mm.

IMPLICATIONS FOR PRACTICE

DTS could have a role in the follow-up of patients with known GGOs identified in lung apex or base region.

Tomosynthesis Is Equivalent to Computed Tomography for Evaluating Osseous Integration After Anterior Cruciate Ligament Reconstruction

Purpose

To compare tomosynthesis and computed tomography (CT) for evaluating bone plug integration after anterior cruciate ligament (ACL) reconstruction with a bone–patellar tendon–bone (BPTB) graft.

Methods

Data of consecutive adult patients who underwent ACL reconstruction with BPTB were analyzed. Bone integration between the bone plug and bone tunnel was evaluated by tomosynthesis and CT, which were both performed 3 months postoperatively. The obtained data for both modalities were reconstructed with slice thickness of 2 mm. Evaluation of bone integration were separately performed using coronal- and sagittal-reconstructed images for the femur and tibia. The ratio of bone integration between the reconstructed slices in which bone grafting was involved, for both tomosynthesis and CT, was investigated by 2 blinded examiners. The equivalence of tomosynthesis to CT was tested by comparing the bone integration ratio for both modalities. The accuracy of diagnosing bone union using tomosynthesis and CT was also investigated.

Results

The diagnostic accuracy of tomosynthesis and CT exceeded 80%. Interobserver agreement of bone integration in the sagittal plane on the femoral side was 0.92 (intraclass correlation coefficient) for CT and 0.76 (intraclass correlation coefficient) for tomosynthesis.

Conclusions

Although it showed poor reliability, tomosynthesis was equivalent to CT in evaluating bone plug integration after ACL reconstruction with BPTB.

Level of Evidence

Level II, diagnostic study.

Determination of radiation dose and low-dose protocol for digital chest tomosynthesis using radiophotoluminescent (RPL) glass dosimeters

PURPOSE

This study aimed to determine a low-dose protocol for digital chest tomosynthesis (DTS).

METHODS

Five simulated nodules with a CT number of approximately 100 HU with size diameter of 3, 5, 8, 10, and 12 mm were inserted into an anthropomorphic chest phantom (N1 Lungman model), and then scanned by DTS system (Definium 8000) with varying tube voltage, copper filter thickness, and dose ratio. Three radiophotoluminescent (RPL) glass dosimeters, type GD-352 M with a dimension of 1.5 × 12 mm, were used to measure the entrance surface air kerma (ESAK) in each protocol. The effective dose (ED) was calculated using the recorded total dose-area-product (DAP). The signal-to-noise ratio (SNR) was determined for qualitative image quality evaluation. The image criteria and nodule detection capability were scored by two experienced radiologists. The selected low-dose protocol was further applied in a clinical study with 30 pulmonary nodule follow-up patients.

RESULTS

The average ESAK obtained from the standard default protocol was 1.68 ± 0.15 mGy, while an ESAK of 0.47 ± 0.02 mGy was found for a low-dose protocol. The EDs for the default and low-dose protocols were 313.98 ± 0.72 µSv and 100.55 ± 0.28 µSv, respectively. There were small non-significant differences in the image criteria and nodule detection scoring between the low-dose and default protocols interpreted by two radiologists. The effective dose of 98.87 ± 0.08 µSv was obtained in clinical study after applying the low-dose protocol.

CONCLUSIONS

The low-dose protocol obtained in this study can substantially reduce radiation dose while preserving an acceptable image quality compared to the standard protocol.

New Imaging Techniques in the Management of Stone Disease

Recent advances in computed tomography, X-ray-based imaging, and ultrasonography have improved the accuracy of urinary stone detection and differentiation of stone composition while minimizing radiation exposure. Dual-energy computed tomography and digital tomosynthesis show promise in predicting mineral composition to optimize medical and surgical therapy. Electromagnetic tracking may enhance the use of ultrasonography to achieve percutaneous renal access for nephrolithotomy. This article reviews innovations in imaging technology in the contemporary management of urinary stone disease.

Abdominal Radiography With Digital Tomosynthesis: An Alternative to Computed Tomography for Identification of Urinary Calculi?

OBJECTIVE

To compare the accuracy of plain abdominal radiography (kidneys, ureter, and bladder [KUB]) with digital tomosynthesis (DT) to noncontrast computed tomography (NCCT), the gold standard imaging modality for urinary stones. Due to radiation and cost concerns, KUB is often used for diagnosis and follow-up of nephrolithiasis. DT, a novel technique that produces high-quality radiographs with less radiation and/or cost than low-dose NCCT, has not been assessed in this situation.

MATERIALS AND METHODS

Seven fresh tissue cadavers were implanted with stones of known size and/or composition and imaged with KUB, DT, and NCCT. Four blinded readers (2 urologists, 2 radiologists) evaluated KUBs for presence and/or location of calculi. They then re-evaluated with addition of tomograms to assess additional value. After a memory extinction period, readers evaluated NCCT images. Accuracy of detection was determined using nearest-neighbor match with generalized linear mixed modeling.

RESULTS

Total of 59 stones were identified on reference read. Overall, NCCT and DT were both superior to KUB alone (P < .001) while the difference between DT and NCCT was not significant (P = .06). When evaluating uric acid stones, NCCT and DT outperformed KUB (P < .01 and P < .05, respectively) while DT and NCCT were similar (P = .16). Intrarenal stones were better evaluated on DT and NCCT (P < .001 compared to KUB), while DT and NCCT were similar (P = 1.00). Accuracy was lower than anticipated across modalities due to use of the cadaver model.

CONCLUSION

Our study demonstrates DT is superior to KUB for identification of intrarenal calculi and could replace routine use of KUB or NCCT for detecting renal stones, even those composed of uric acid.

Dependency of image quality on acquisition protocol and image processing in chest tomosynthesis-a visual grading study based on clinical data

OBJECTIVE

To compare the quality of images obtained with two different protocols with different acquisition time and the influence from image post processing in a chest digital tomosynthesis (DTS) system.

METHODS

20 patients with suspected lung cancer were imaged with a chest X-ray equipment with tomosynthesis option. Two examination protocols with different acquisition times (6.3 and 12 s) were performed on each patient. Both protocols were presented with two different image post-processing (standard DTS processing and more advanced processing optimised for chest radiography). Thus, 4 series from each patient, altogether 80 series, were presented anonymously and in a random order. Five observers rated the quality of the reconstructed section images according to predefined quality criteria in three different classes. Visual grading characteristics (VGC) was used to analyse the data and the area under the VGC curve (AUC_VGC) was used as figure-of-merit. The 12 s protocol and the standard DTS processing were used as references in the analyses.

RESULTS

The protocol with 6.3 s acquisition time had a statistically significant advantage over the vendor-recommended protocol with 12 s acquisition time for the classes of criteria, Demarcation (AUC_VGC = 0.56, p = 0.009) and Disturbance (AUC_VGC = 0.58, p < 0.001). A similar value of AUC_VGC was found also for the class Structure (definition of bone structures in the spine) (0.56) but it could not be statistically separated from 0.5 (p = 0.21). For the image processing, the VGC analysis showed a small but statistically significant advantage for the standard DTS processing over the more advanced processing for the classes of criteria Demarcation (AUC_VGC = 0.45, p = 0.017) and Disturbance (AUC_VGC = 0.43, p = 0.005). A similar value of AUC_VGC was found also for the class Structure (0.46), but it could not be statistically separated from 0.5 (p = 0.31).

CONCLUSION

The study indicates that the protocol with 6.3 s acquisition time yields slightly better image quality than the vender-recommended protocol with acquisition time 12 s for several anatomical structures. Furthermore, the standard gradation processing  (the vendor-recommended post-processing for DTS), yields to some extent advantage over the gradation processing/multiobjective frequency processing/flexible noise control processing in terms of image quality for all classes of criteria. Advances in knowledge: The study proves that the image quality may be strongly affected by the selection of DTS protocol and that the vendor-recommended protocol may not always be the optimal choice.

Value of a Computer-aided Detection System Based on Chest Tomosynthesis Imaging for the Detection of Pulmonary Nodules

Purpose To assess the value of a computer-aided detection (CAD) system for the detection of pulmonary nodules on chest tomosynthesis images. Materials and Methods Fifty patients with and 50 without pulmonary nodules underwent both chest tomosynthesis and multidetector computed tomography (CT) on the same day. Fifteen observers (five interns and residents, five chest radiologists, and five abdominal radiologists) independently evaluated tomosynthesis images of 100 patients for the presence of pulmonary nodules in a blinded and randomized manner, first without CAD, then with the inclusion of CAD marks. Multidetector CT images served as the reference standard. Free-response receiver operating characteristic analysis was used for the statistical analysis. Results The pooled diagnostic performance of 15 observers was significantly better with CAD than without CAD (figure of merit [FOM], 0.74 vs 0.71, respectively; P = .02). The average true-positive fraction and false-positive rate per all cases with CAD were 0.56 and 0.26, respectively, whereas those without CAD were 0.47 and 0.20, respectively. Subanalysis showed that the diagnostic performance of interns and residents was significantly better with CAD than without CAD (FOM, 0.70 vs 0.62, respectively; P = .001), whereas for chest radiologists and abdominal radiologists, the FOM with CAD values were greater but not significantly: 0.80 versus 0.78 (P = .38) and 0.74 versus 0.73 (P = .65), respectively. Conclusion CAD significantly improved diagnostic performance in the detection of pulmonary nodules on chest tomosynthesis images for interns and residents, but provided minimal benefit for chest radiologists and abdominal radiologists. ^© RSNA, 2017 Online supplemental material is available for this article.

Comparison of digital tomosynthesis and chest radiography for the detection of pulmonary nodules: systematic review and meta-analysis

OBJECTIVE

To compare the diagnostic accuracy of digital tomosynthesis (DTS) with that of chest radiography for the detection of pulmonary nodules by meta-analysis.

METHODS

A systematic literature search was performed to identify relevant original studies from 1 January 1 1976 to 31 August 31 2016. The quality of included studies was assessed by quality assessment of diagnostic accuracy studies-2. Per-patient data were used to calculate the sensitivity and specificity and per-lesion data were used to calculate the detection rate. Summary receiver-operating characteristic curves were drawn for pulmonary nodule detection.

RESULTS

16 studies met the inclusion criteria. 1017 patients on a per-patient basis and 2159 lesions on a per-lesion basis from 16 eligible studies were evaluated. The pooled patient-based sensitivity of DTS was 0.85 [95% confidence interval (CI) 0.83-0.88] and the specificity was 0.95 (0.93-0.96). The pooled sensitivity and specificity of chest radiography were 0.47 (0.44-0.51) and 0.37 (0.34-0.40), respectively. The per-lesion detection rate was 2.90 (95% CI 2.63-3.19).

CONCLUSION

DTS has higher diagnostic accuracy than chest radiography for detection of pulmonary nodules. Chest radiography has low sensitivity but similar specificity, comparable with that of DTS. Advances in knowledge: DTS has higher diagnostic accuracy than chest radiography for the detection of pulmonary nodules.

AN ANALYSIS OF THE POTENTIAL ROLE OF CHEST TOMOSYNTHESIS IN OPTIMISING IMAGING RESOURCES IN THORACIC RADIOLOGY

The aim of the study was to investigate the potential role of chest tomosynthesis (CTS) at a tertiary referral centre by exploring to what extent CTS could substitute chest radiography (CXR) and computed tomography (CT). The study comprised 1433 CXR, 523 CT and 216 CTS examinations performed 5 years after the introduction of CTS. For each examination, it was decided if CTS would have been appropriate instead of CXR (CXR cases), if CTS could have replaced the performed CT (CT cases) or if CT would have been performed had CTS not been available (CTS cases). It was judged that (a) CTS had been appropriate in 15 % of the CXR examinations, (b) CTS could have replaced additionally 7 % of the CT examinations and (c) CT would have been carried out in 63 % of the performed CTS examinations, had CTS not been available. In conclusion, the potential role for CTS to substitute other modalities during office hours at a tertiary referral centre may be in the order of 20 and 25 % of performed CXR and chest CT, respectively.

Diagnostic impact of digital tomosynthesis in oncologic patients with suspected pulmonary lesions on chest radiography

OBJECTIVES

To assess the actual diagnostic impact of digital tomosynthesis (DTS) in oncologic patients with suspected pulmonary lesions on chest radiography (CXR).

METHODS

A total of 237 patients (135 male, 102 female; age, 70.8 ± 10.4 years) with a known primary malignancy and suspected pulmonary lesion(s) on CXR and who underwent DTS were retrospectively identified. Two radiologists (experience, 10 and 15 years) analysed in consensus CXR and DTS images and proposed a diagnosis according to a confidence score: 1 or 2 = definitely or probably benign pulmonary or extrapulmonary lesion, or pseudolesion; 3 = indeterminate; 4 or 5 = probably or definitely pulmonary lesion. DTS findings were proven by CT (n = 114 patients), CXR during follow-up (n = 105) or histology (n = 18).

RESULTS

Final diagnoses included 77 pulmonary opacities, 26 pulmonary scars, 12 pleural lesions and 122 pulmonary pseudolesions. DTS vs CXR presented a higher (P < 0.05) sensitivity (92 vs 15 %), specificity (91 vs 9 %), overall accuracy (92 vs 12 %), and diagnostic confidence (area under ROC, 0.997 vs 0.619). Mean effective dose of CXR vs DTS was 0.06 vs 0.107 mSv (P < 0.05).

CONCLUSIONS

DTS improved diagnostic accuracy and confidence in comparison to CXR alone in oncologic patients with suspected pulmonary lesions on CXR with only a slight, though significant, increase in radiation dose.

KEY POINTS

• Digital tomosynthesis (DTS) improves accuracy of chest radiography (CXR) in oncologic patients. • DTS improves confidence of CXR in oncologic patients. • DTS allowed avoidance of CT in about 50 % of oncologic patients.

A retrospective study of chest tomosynthesis as a tool for optimizing the use of computed tomography resources and reducing patient radiation exposure

RATIONALE AND OBJECTIVES

To investigate potential benefits and drawbacks of the clinical use of chest tomosynthesis (CTS), to what extent CTS obviates the need for chest computed tomography (CT), and what reduction in radiation dose thereby can be achieved.

MATERIALS AND METHODS

The Regional Ethical Review Board approved the follow-up study of patients examined with CTS as part of clinical routine. For each case, two radiologists in consensus determined whether CT would have been performed, had CTS not been an option, and whether CTS was an adequate examination. Thereafter, it was determined whether the use of CTS instead of CT in retrospect was beneficial, neutral, or detrimental for the radiological work-up. The radiation dose to the patient population was determined both for the actual clinical situation and for the alternative scenario that would result, had CTS not been available.

RESULTS

During 1 month 3.5 years before the survey, 149 patients (74 women, age 18-91 years) had undergone CTS for clinical purposes. It was judged that CT would have been performed in 100 cases, had CTS not been available, and that CTS obviated the need for CT in 80 cases. CTS was judged as beneficial, neutral, and detrimental for the radiological work-up in 85, 13, and two cases, respectively. For the entire study population, the use of CTS decreased the average effective dose from 2.7 to 0.7 mSv.

CONCLUSIONS

The present study indicates that CTS may have benefits for the radiological work-up as it has the potential to both optimize the use of CT resources and reduce the effective dose to the patient population. A drawback is that CTS examinations may fail to reveal pathology visible with CT and in clinically doubtful cases further investigations including other imaging procedures should be considered.