Computed Tomography Scout Images Research Articles

Adjustment of scan delay for bolus tracking with cardiothoracic ratio of CT scout image for hepatic artery phase of hepatic dynamic CT.

This study aimed to determine the scan delay for bolus tracking in the hepatic artery phase (HAP) of hepatic dynamic computed tomography (CT) using the cardiothoracic ratio (CTR) from CT scout images. We retrospectively studied 188 patients who underwent hepatic dynamic CT, 24 of whom had scan delays adjusted for CTR. The contrast enhancement of the abdominal aorta, portal vein, hepatic vein, and hepatic parenchyma was calculated for HAP. The adequacy of the scan timing for HAP was assessed using three classifications: early, appropriate, or late. The effect of HAP on scan timing adequacy was determined using multivariate logistic regression analysis, and the optimal cutoff value of CTR was evaluated using receiver operating characteristic analysis. The trigger times for bolus tracking (odds ratio: 1.58) and CTR (odds ratio: 1.23) were significantly affected by the appropriate scan timing of the HAP. The optimal cutoff value of CTR was 59.3%. The scan timing of HAP with a scan delay of 15s was 14% of early and 86% of appropriate, and the proportion of early in CTR ≥ 60% (early, 52%; appropriate, 48%) was higher than that in CTR < 60% (early, 6%; appropriate, 94%). Adjusting the scan delay to 20s in CTR ≥ 60% increased the proportion of appropriate (early, 4%; appropriate, 96%). The CTR of a CT scout image is an effective index for determining the scan delay for bolus tracking. Adjusting the scan delay by CTR can provide appropriate HAP images in more patients. Trial registration number: R-080; date of registration: 9 March 2023, retrospectively registered.

Development of a new body weight estimation method using head CT scout images.

Imaging examinations are crucial for diagnosing acute ischemic stroke, and knowledge of a patient's body weight is necessary for safe examination. To perform examinations safely and rapidly, estimating body weight using head computed tomography (CT) scout images can be useful. This study aims to develop a new method for estimating body weight using head CT scout images for contrast-enhanced CT examinations in patients with acute ischemic stroke. This study investigates three weight estimation techniques. The first utilizes total pixel values from head CT scout images. The second one employs the Xception model, which was trained using 216 images with leave-one-out cross-validation. The third one is an average of the first two estimates. Our primary focus is the weight estimated from this third new method. The third new method, an average of the first two weight estimation methods, demonstrates moderate accuracy with a 95% confidence interval of ±14.7 kg. The first method, using only total pixel values, has a wider interval of ±20.6 kg, while the second method, a deep learning approach, results in a 95% interval of ±16.3 kg. The presented new method is a potentially valuable support tool for medical staff, such as doctors and nurses, in estimating weight during emergency examinations for patients with acute conditions such as stroke when obtaining accurate weight measurements is not easily feasible.

Deep learning-based body weight from scout images can be an alternative to actual body weight in CT radiation dose management.

Accurate body weight measurement is essential to promote computed tomography (CT) dose optimization; however, body weight cannot always be measured prior to CT examination, especially in the emergency setting. The aim of this study was to investigate whether deep learning-based body weight from chest CT scout images can be an alternative to actual body weight in CT radiation dose management. Chest CT scout images and diagnostic images acquired for medical checkups were collected from 3601 patients. A deep learning model was developed to predict body weight from scout images. The correlation between actual and predicted body weight was analyzed. To validate the use of predicted body weight in radiation dose management, the volume CT dose index (CTDIvol ) and the dose-length product (DLP) were compared between the body weight subgroups based on actual and predicted body weight. Surrogate size-specific dose estimates (SSDEs) acquired from actual and predicted body weight were compared to the reference standard. The median actual and predicted body weight were 64.1 (interquartile range: 56.5-72.4) and 64.0 (56.3-72.2) kg, respectively. There was a strong correlation between actual and predicted body weight (ρ=0.892, p<0.001). The CTDIvol and DLP of the body weight subgroups were similar based on actual and predicted body weight (p<0.001). Both surrogate SSDEs based on actual and predicted body weight were not significantly different from the reference standard (p=0.447 and 0.410, respectively). Predicted body weight can be an alternative to actual body weight in managing dose metrics and simplifying SSDE calculation. Our proposed method can be useful for CT radiation dose management in adult patients with unknown body weight.

Analysis of source dwell position during treatment in brachytherapy using CT scout images.

Several cases of inaccurate irradiation in brachytherapy have been reported, occurring similarly to external radiation. Due to a large dose per fraction in brachytherapy, inaccurate irradiation can seriously harm a patient. Although various studies have been conducted, systems that detect inaccurate irradiation in brachytherapy are not as developed as those for external irradiation. This study aimed to construct a system that analyzes the source dwell position during irradiation using computed tomography (CT) scout images. The novelty of the study was that by using CT scout images, high versatility and analysis of absolute coordinates can be achieved. A treatment plan was designed with an iridium-192 (192Ir) source delivering radiation at two dwell positions in a tandem applicator. CT scout images were taken during irradiation, and acquired under different imaging conditions and applicator geometries. First, we confirmed whether a source was visible in CT scout images. Then, employing in-house MATLAB program, source dwell coordinates were analyzed using the images. An analysis was considered adequate when the resulting source dwell coordinates agreed with the treatment plan within ±1 mm, in accordance with AAPM TG56 guidelines for source dwell position accuracy. The source dwelling was visible in CT scout image, which was enlarged or reduced depending on applicator geometries. The applicator was enlarged by 127% when 130 mm away from the center of CT gantry. The analysis results using our in-house program were considered adequate; although, analysis parameters required adjustments depending on imaging conditions. The proposed system can be easily implemented for image-guided brachytherapy and can analyze the absolute coordinates of source dwell position. Therefore, the system could be used for preventing inaccurate irradiation by verifying whether brachytherapy was performed properly.

A deep-learning method using computed tomography scout images for estimating patient body weight

Body weight is an indispensable parameter for determination of contrast medium dose, appropriate drug dosing, or management of radiation dose. However, we cannot always determine the accurate patient body weight at the time of computed tomography (CT) scanning, especially in emergency care. Time-efficient methods to estimate body weight with high accuracy before diagnostic CT scans currently do not exist. In this study, on the basis of 1831 chest and 519 abdominal CT scout images with the corresponding body weights, we developed and evaluated deep-learning models capable of automatically predicting body weight from CT scout images. In the model performance assessment, there were strong correlations between the actual and predicted body weights in both chest (ρ = 0.947, p < 0.001) and abdominal datasets (ρ = 0.869, p < 0.001). The mean absolute errors were 2.75 kg and 4.77 kg for the chest and abdominal datasets, respectively. Our proposed method with deep learning is useful for estimating body weights from CT scout images with clinically acceptable accuracy and potentially could be useful for determining the contrast medium dose and CT dose management in adult patients with unknown body weight.

The CT scout view: complementary value added to abdominal CT interpretation.

Computed tomography (CT) scout images, also known as CT localizer radiographs, topograms, or scanograms, are an important, albeit often overlooked part of the CT examination. Scout images may contain important findings outside of the scanned field of view on CT examinations of the abdomen and pelvis, such as unsuspected lung cancer at the lung bases. Alternatively, scout images can provide complementary information to findings within the scanned field of view, such as characterization of retained surgical foreign bodies. Assessment of scout images adds value and provides a complementary "opportunistic" review for interpretation of abdominopelvic CT examinations. Scout image review is a useful modern application of conventional abdominal radiograph interpretation that can help establish a diagnosis or narrow a differential diagnosis. This review discusses the primary purpose and intent of the CT scout images, addresses standard of care and bias related to scout image review, and presents a general systematic approach to assessing scout images with multiple illustrative examples, including potential pitfalls in interpreting scout images.

Standardizing ordinal subadult age indicators: Testing for observer agreement and consistency across modalities

Skeletal and dental data for subadult analyses obtained from dry bones or various types of medical images, such as computed tomography (CT) scans or conventional radiographs/x-rays, should be consistent and repeatable to ensure method applicability across modalities and support combining study samples. The present study evaluates observer agreement of epiphyseal fusion and dental development stages obtained on CT scans of a U.S. sample and the consistency of epiphyseal fusion stages between CT scans and projected scan radiographs/scout images (U.S. CT sample), and between dry bones and conventional x-rays (Colombian osteological sample). Results show that both intra- and interobserver agreements of scores on CT scans were high (intra: mean Cohen’s kappa=0.757–0.939, inter: mean Cohen’s kappa=0.773–0.836). Agreements were lower for dental data (intra: mean Cohen’s kappa=0.757, inter: mean Cohen’s kappa=0.773–0.0.820) compared to epiphyseal fusion data (intra: mean Cohen’s kappa=0.939, inter: mean Cohen’s kappa=0.807–0.836). Consistency of epiphyseal fusion stages was higher between dry bones and conventional x-rays than between CT scans and scout images (mean Cohen’s kappa=0.708–0.824 and 0.726–0.738, respectively). Differences rarely surpassed a one-stage value between observers or modalities. The complexity of some ossification patterns and superimposition had a greater negative impact on agreement and consistency rates than observer experience. Results suggest ordinal subadult skeletal data can be collected and combined across modalities.

Predicting Pathologic Bone Lesions Using Scout Computed Tomography (CT) Imaging

The purpose of this study is to evaluate the benefit of reviewing scout CT images, obtained for routine oncologic surveillance, for the early identification of pathologic bony lesions. A retrospective review was conducted on patients who previously underwent surgical treatment by two orthopedic oncology surgeons at a tertiary care institution from 2009–2019 for pathologic lesions or fractures of the humerus or femur. Radiographic records were reviewed to identify patients in this cohort who had available scout views from CT imaging prior to official diagnosis of the bony lesion or fracture. CT scout images were assessed by two independent reviewers to identify any pathologic lesions, and radiographic reports were reviewed to identify if the lesions were noted by radiology at the time of the initial scan interpretation. One hundred and forty-four patients were identified, and thirty-nine had an available scout CT image prior to official diagnosis of the lesion. Twenty-five patients (64.1%) had lesions identified by authors on scout CT versus only 9 (23.1%) who had lesions that were documented in the initial CT radiologic report. There was a total of 29 lesions identified by the study authors on scout CT, and 19 (65.5%) were not reported in the initial radiographic interpretation with an average interval between observation by authors and official diagnosis of 202 days. Of the impending fractures, three patients (16.7%) went on to complete fracture prior to referral to orthopedics with an average interval between these missed lesions on scout CT and their presentation with fracture of 68 days. This study advocates for the careful review of all scout CT imaging as an essential part of the work up for metastatic disease and encourages all practitioners to utilize this screening tool for the identification of pathologic bony lesions which may help expedite early treatment to reduce patient morbidity.

Computed Tomography Guidance for Percutaneous Glycerol Rhizotomy for Trigeminal Neuralgia.

Percutaneous glycerol rhizotomy (PGR) is a well-described treatment for trigeminal neuralgia; however, the technique in using surface landmarks and fluoroscopy has not drastically changed since being first introduced. In this paper, we describe a protocol for PGR using computed tomography (CT) guidance based on an experience of over 7 yr and 200 patients. To introduce an approach for PGR using CT guidance and, in doing so, demonstrate possible benefits over the traditional fluoroscopic technique. Using a standard CT scanner, patients are placed supine with head in extension. Barium paste and a CT scout image are used to identify and plan a trajectory to the foramen ovale. A laser localization system built into the CT scanner helps to guide placement of the spinal needle into the foramen ovale. The needle position in the foramen is confirmed with a short-sequence CT scan. CT-guided PGR provides multiple benefits over standard fluoroscopy, including improved visualization of the skull base and significant reduction in radiation exposure to the surgeon and staff. Side benefits include improved procedure efficiency, definitive imaging evidence of correct needle placement, and potentially increased patient safety. We have had no significant complications in over 200 patients. CT-guided PGR is a useful technique for treating trigeminal neuralgia based on better imaging of the skull base, better efficiency of the procedure, and elimination of radiation exposure for the surgeon and staff compared to traditional fluoroscopic based techniques.

The Association Between Femoral Neck-Shaft Angle and Aging and Its Influence on the Performance of Functional Activity: A Cross-Sectional Investigation.

The purposes of this study were first to examine the association between aging and both the magnitude and asymmetry in the femoral neck-shaft angle (NSA). The second purpose was to determine the effects of both the magnitude and NSA asymmetry on the performance of functional activities in healthy individuals. Fifty-one subjects participated in this study. The femoral NSA was measured on computed tomography scout images. The participants performed four performance tests. Four hierarchical regression models were constructed to explore the effect of each predictor on the outcomes. Aging was associated with NSA asymmetry, but not with the degree of NSA. Age contributed significantly to the variability of all functional performance tests except the 10-m walking speed. The degree of the NSA did not contribute to the prediction of the functional performance tests. However, asymmetry in the NSA added significantly to the prediction of all functional performance tests except the 10-m walking speed.

Computed tomography follow-up identifies radically treatable new primaries after resection for lung cancer.

The optimal imaging programme for the follow-up of patients who have undergone resection of primary lung cancer is yet to be determined. We investigated the incidence and patterns of new and recurrent malignancy after resection for early-stage lung cancer in patients enrolled into a computed tomography (CT) follow-up programme. We reviewed the outcomes of consecutive patients who underwent CT follow-up after resection of early-stage primary lung cancer at the Oxford University Hospitals NHS Foundation Trust, between 2013 and 2017. Four hundred and sixty-six consecutive patients underwent resection of primary lung cancer between 1 January 2013 and 31 March 2017. Three hundred and thirty-one patients (71.0%) were enrolled in CT follow-up. The median follow-up was 98 weeks (range 26-262). Sixty patients (18.2%) were diagnosed with programme-detected malignancy. Recurrence was diagnosed in 36 patients (10.9%), new primary lung cancer in 16 patients (4.8%) and non-lung primary tumours in 8 patients (2.4%). A routine CT scan identified the majority of new primary lung cancers (84.2%) and those with disease recurrence (85.7%). The majority of programme-detected malignancies were radically treatable (55%). The median survival of programme-detected cancers was 92.4 versus 23.0 weeks for patients with clinically detected tumours (P < 0.0001). Utilizing the CT scout image as a surrogate for chest X-ray, the sensitivity of this modality was 16.95% (8.44-28.97%) and specificity was 89.83% (79.17-96.18%). Negative likelihood ratio was 0.92 (0.8-1.07). CT follow-up of surgically treated primary lung cancer patients identifies malignancy at a stage where radical treatment is possible in the majority of patients. Chest X-ray follow-up may not be of benefit following lung cancer resection.

Determination of appropriate conversion factors for calculating size-specific dose estimates based on X-ray CT scout images after miscentering correction.

In this study, we proposed and evaluated the validity of an optimized size-specific dose estimate, a widely used index of radiation dose in X-ray computed tomography (CT) examinations. Based on miscentering correction of scout images, we determined the appropriate conversion factors (CF) by using a phantom. Scans were conducted using a multi-detector CT system (Aquilion ONE, Canon Medical Systems). Four cylindrical phantoms were taken in the anteroposterior (AP) and axial directions to determine the relationship between pixel value and water-equivalent length (Lw). In the AP scout image, the pixel values at the selected slice positions were converted to Lw to calculate the water-equivalent diameter (Dw). The CF was derived from Dw and CF values before and after miscentering correction was calculated. Finally, the CF values were compared to those calculated from the axial image using the conventional methodology of the American Association of Physicists in Medicine. Before miscentering correction, the maximum difference between the CF values of the axial and scout images was 7.26%. However, after miscentering correction, the maximum difference was 1.34%. Validation using a whole-body phantom generally revealed low maximum differences between the CF from the axial image and the values from the miscentering-corrected scout images. These were 2.41% in the chest, 6.30% in the upper abdomen, 1.43% in the abdomen, and 2.45% in the pelvic region. Consequently, we concluded that our miscentering correction method for deriving the appropriate CF values based on scout images is advantageous.

Investigation of Low-Dose CT Lung Cancer Screening Scan "Over-Range" Issue Using Machine Learning Methods.

Low-dose computed tomography (CT) lung cancer screening is recommended by the US Preventive Services Task Force for high lung cancer-risk populations. In this study, we investigated an important factor affecting the CT dose-the scan length, for this CT exam. A neural network model based on the "UNET" framework was established to segment the lung region in the CT scout images. It was trained initially with 247 chest X-ray images and then with 40 CT scout images. The mean Intersection over Union (IOU) and Dice coefficient were reported to be 0.954 and 0.976, respectively. Lung scan boundaries were determined from this segmentation and compared with the boundaries marked by an expert for 150 validation images, resulting an average 4.7% difference. Seven hundred seventy CT low-dose lung screening exams were retrospectively analyzed with the validated model. The average "desired" scan length was 252mm with a standard deviation of 28mm. The average "over-range" was 58.5mm or 24%. The upper boundary (superior) on average had an "over-range" of 17mm, and the lower boundary (inferior) on average had an "over-range" of 41mm. Further analysis of this data showed that the extent of "over-range" was independent of acquisition date, acquisition time, acquisition station, and patient age, but dependent on technologist and patient weight. We concluded that this machine learning method could effectively support quality control on the scan length for CT low-dose screening scans, enabling the eliminations of unnecessary patient dose.

Thoracic Kyphosis and Physical Function: The Framingham Study.

To evaluate the association between thoracic kyphosis and physical function. Prospective cohort. Framingham, Massachusetts. Framingham Heart Study Offspring and Third Generation cohort members who had computed tomography (CT) performed between 2002 and 2005 and physical function assessed a mean 3.4 years later (N = 1,100; mean age 61 ± 8, range 50-85). Thoracic kyphosis (Cobb angle, T4-T12) was measured in degrees using supine CT scout images. Participants were categorized according to Cobb angle to compare those in the highest quartile (Q4, most-severe kyphosis) with those in the lowest quartiles (Q1-Q3). Quick walking speed (m/s), chair-stand time (seconds), grip strength (kg), and self-reported impairments were assessed using standardized procedures. Analyses were adjusted for age, height, weight, smoking, follow-up time, vertebral fractures, and prevalent spinal degeneration. Thoracic kyphosis was not associated with physical function in women or men, and these results were consistent in those younger than 65 and those aged 65 and older. For example, walking speed was similar in adults younger than 65 with and without severe kyphosis (women, Q4: 1.38 m/s, Q1-Q3: 1.40 m/s, P = .69; men, Q4: 1.65 m/s, Q1-Q3: 1.60 m/s; P = .39). In healthy relatively high-functioning women and men, kyphosis severity was not associated with subsequent physical function. Individuals at risk of functional decline cannot be targeted based on supine CT thoracic curvature measures alone.

Automatic heart positioning method in computed tomography scout images.

Computed tomography (CT) radiation dose can be reduced significantly by region of interest (ROI) CT scan. Automatically positioning the heart in CT scout images is an essential step to realize the ROI CT scan of the heart. This paper proposed a fully automatic heart positioning method in CT scout image, including the anteroposterior (A-P) scout image and lateral scout image. The key steps were to determine the feature points of the heart and obtaining part of the heart boundary on the A-P scout image, and then transform the part of the boundary into polar coordinate system and obtain the whole boundary of the heart using slant elliptic equation curve fitting. For heart positioning on the lateral image, the top and bottom boundary obtained from A-P image can be inherited. The proposed method was tested on a clinical routine dataset of 30 cases (30 A-P scout images and 30 lateral scout images). Experimental results show that 26 cases of the dataset have achieved a very good positioning result of the heart both in the A-P scout image and the lateral scout image. The method may be helpful for ROI CT scan of the heart.

Organ dose calculation in CT based on scout image data and automatic image registration

Computed tomography (CT) has become the main contributor of the cumulative radiation exposure in radiology. Information on cumulative exposure history of the patient should be available for efficient management of radiation exposures and for radiological justification. To develop and evaluate automatic image registration for organ dose calculation in CT. Planning radiograph (scout) image data describing CT scan ranges from 15 thoracic CT examinations (9 men and 6 women) and 10 abdominal CT examinations (6 men and 4 women) were co-registered with the reference trunk CT scout image. 2-D affine transformation and normalized correlation metric was used for image registration. Longitudinal (z-axis) scan range coordinates on the reference scout image were converted into slice locations on the CT-Expo anthropomorphic male and female models, following organ and effective dose calculations. The average deviation of z-location of studied patient images from the corresponding location in the reference scout image was 6.2 mm. The ranges of organ and effective doses with constant exposure parameters were from 0 to 28.0 mGy and from 7.3 to 14.5 mSv, respectively. The mean deviation of the doses for fully irradiated organs (inside the scan range), partially irradiated organs and non-irradiated organs (outside the scan range) was 1%, 5%, and 22%, respectively, due to image registration. The automated image processing method to registrate individual chest and abdominal CT scout radiograph with the reference scout radiograph is feasible. It can be used to determine the individual scan range coordinates in z-direction to calculate the organ dose values. The presented method could be utilized in automatic organ dose calculation in CT for radiation exposure tracking of the patients.

Resolution improvement and detail enhancement for computed tomography scout images

New applications currently demand utilizing computed tomography (CT) scout images for diagnostic purposes. However, many CT scout images cannot be used diagnostically due to their poor resolution, particularly in the direction of table movement, and loss of detail when displayed with one view. We present two methods to address these two problems. First, spatial resolution generally can be improved with image restoration techniques. Based on the principles of Wiener filtering and inverse filtering, a modified Wiener filtering approach is presented in the frequency domain. The concept of an equivalent target point spread function is also introduced, which makes the restoration process steerable. Consequently, balancing resolution improvement with noise suppression is facilitated. Relevant experiments compare the image quality with traditional inverse filtering and Wiener filtering. The modified Wiener filtering method has been shown to restore the scout image with higher resolution and lower noise. In addition, CT scout images have a wide dynamic range, from 0 to 105 intensity values. They are difficult to display in full detail with only 8 bits (256 intensities). An image fusion approach is developed to preserve and enhance details of CT scout images. The enhanced image is obtained by high-boosting one fused image from another, both of which are computed by fusing a set of preenhanced subimages which derived from the original, using different fusion rules. Image fusion is performed pixel by pixel by the discrete wavelet transform. Final experiments compare the image quality of the resolution-improved and detail-enhanced image and the noise level with those of the original image. Results show that more details, easily observed by a radiologist, are present in the restored and enhanced image than in the original.

Optimal computed tomography imaging of the midfoot: an improved technique.

A new protocol for computed tomography (CT) imaging of the midfoot is described. This imaging technique places the CT cuts parallel to and perpendicular to the talus-first metatarsal axis, as viewed on the lateral CT scout image. For imaging the midfoot, this technique is an improvement over previously described hindfoot or midfoot protocols.