Computed Tomography Slice Thickness Research Articles

Puncture Accuracy of Robot-Assisted CT-Based Punctures in Interventional Radiology: An Ex Vivo Study.

The purpose of this study was to assess the performance of an optically tracked robot for computed-tomography (CT)-guided needle placements in a phantom study. In total, 240 needle punctures were carried out with the help of an optically tracked robotic device (Micromate) based on CT image datasets at three different slice thicknesses (1, 3, and 5 mm). Conically shaped targets inside a gelatin-filled plexiglass phantom were punctured. The target positioning error between the planned and actual needle trajectory was assessed by measuring the lateral positioning error (ND) between the target and the puncture needle and the Euclidean distance (ED) between the needle tip and target in control CTs. The mean ND and ED for the thinnest CT slice thickness were 1.34 mm (SD ± 0.82) and 2.1 mm (SD ± 0.75), respectively. There was no significant impact of target depth on targeting accuracy for ND (p = 0.094) or ED (p = 0.187). The mean duration for the planning of one trajectory and for needle positioning were 42 s (SD ± 4) and 64 s (SD ± 7), respectively. In this ex vivo study, the robotic targeting device yielded satisfactory accuracy results at CT slice thicknesses of 1 and 3 mm. This technology may be particularly useful in interventions where the accurate placement of needle-like instruments is required.

Exploring CT pixel and voxel size effect on anatomic modeling in mandibular reconstruction

BackgroundComputer-aided modeling and design (CAM/CAD) of patient anatomy from computed tomography (CT) imaging and 3D printing technology enable the creation of tangible, patient-specific anatomic models that can be used for surgical guidance. These models have been associated with better patient outcomes; however, a lack of CT imaging guidelines risks the capture of unsuitable imaging for patient-specific modeling. This study aims to investigate how CT image pixel size (X-Y) and slice thickness (Z) impact the accuracy of mandibular models.MethodsSix cadaver heads were CT scanned at varying slice thicknesses and pixel sizes and turned into CAD models of the mandible for each scan. The cadaveric mandibles were then dissected and surface scanned, producing a CAD model of the true anatomy to be used as the gold standard for digital comparison. The root mean square (RMS) value of these comparisons, and the percentage of points that deviated from the true cadaveric anatomy by over 2.00 mm were used to evaluate accuracy. Two-way ANOVA and Tukey-Kramer post-hoc tests were used to determine significant differences in accuracy.ResultsTwo-way ANOVA demonstrated significant difference in RMS for slice thickness but not pixel size while post-hoc testing showed a significant difference in pixel size only between pixels of 0.32 mm and 1.32 mm. For slice thickness, post-hoc testing revealed significantly smaller RMS values for scans with slice thicknesses of 0.67 mm, 1.25 mm, and 3.00 mm compared to those with a slice thickness of 5.00 mm. No significant differences were found between 0.67 mm, 1.25 mm, and 3.00 mm slice thicknesses. Results for the percentage of points deviating from cadaveric anatomy greater than 2.00 mm agreed with those for RMS except when comparing pixel sizes of 0.75 mm and 0.818 mm against 1.32 mm in post-hoc testing, which showed a significant difference as well.ConclusionThis study suggests that slice thickness has a more significant impact on 3D model accuracy than pixel size, providing objective validation for guidelines favoring rigorous standards for slice thickness while recommending isotropic voxels. Additionally, our results indicate that CT scans up to 3.00 mm in slice thickness may provide an adequate 3D model for facial bony anatomy, such as the mandible, depending on the clinical indication.

Development and validation of a CT-based deep learning algorithm to augment non-invasive diagnosis of idiopathic pulmonary fibrosis

RationaleNon-invasive diagnosis of idiopathic pulmonary fibrosis (IPF) involves identification of usual interstitial pneumonia (UIP) pattern by computed tomography (CT) and exclusion of other known etiologies of interstitial lung disease (ILD). However, uncertainty in identification of radiologic UIP pattern leads to the continued need for invasive surgical biopsy. We thus developed and validated a machine learning algorithm using CT scans alone to augment non-invasive diagnosis of IPF. MethodsThe primary algorithm was a deep learning convolutional neural network (CNN) with model inputs of CT images only. The algorithm was trained to predict IPF among cases of ILD, with reference standard of multidisciplinary discussion (MDD) consensus diagnosis. The algorithm was trained using a multi-center dataset of more than 2000 cases of ILD. A US-based multi-site cohort (n = 295) was used for algorithm tuning, and external validation was performed with a separate dataset (n = 295) from European and South American sources. ResultsIn the tuning set, the model achieved an area under the receiver operating characteristic curve (AUC) of 0.87 (CI: 0.83–0.92) in differentiating IPF from other ILDs. Sensitivity and specificity were 0.67 (0.57–0.76) and 0.90 (0.83–0.95), respectively. By contrast, pre-recorded assessment prior to MDD diagnosis had sensitivity of 0.31 (0.23–0.42) and specificity of 0.92 (0.87–0.95). In the external test set, c-statistic was also 0.87 (0.83–0.91). Model performance was consistent across a variety of CT scanner manufacturers and slice thickness. ConclusionThe presented deep learning algorithm demonstrated consistent performance in identifying IPF among cases of ILD using CT images alone and suggests generalization across CT manufacturers.

Influence of computed tomography slice thickness on deep learning-based, automatic coronary artery calcium scoring software performance.

The influence of computed tomography (CT) slice thickness on the accuracy of deep learning (DL)-based, automatic coronary artery calcium (CAC) scoring software has not been explored yet. This retrospective study included 844 subjects (477 men, mean age of 58.9±10.7 years) who underwent electrocardiogram (ECG)-gated CAC scoring CT scans with 1.5 and 3 mm slice thickness values between September 2013 and October 2020. Automatic CAC scoring was performed using DL-based software (3D patch-based U-Net architectures). Manual CAC scoring was set as the reference standard. The reliability of automatic CAC scoring was evaluated using intraclass correlation coefficients (ICCs) for both the 1.5 and 3 mm datasets. The agreement of CAC severity categories [Agatston score (AS) 0, 1-100, 101-400, >400] between automatic CAC scoring and the reference standard was analyzed using weighted kappa (κ) statistics for both 1.5 and 3 mm datasets. The CAC scoring agreement between the automatic CAC scoring and reference standard was excellent (ICC 0.982 for 1.5 mm, 0.969 for 3 mm, respectively). The categorical agreement of CAC severity between two methods was excellent for both 1.5 and 3 mm scans, with better agreement for 3 mm scans (weighted κ: 0.851 and 0.961, 95% confidence intervals: 0.823-0.879 and 0.945-0.974, respectively). Automatic CAC scoring shows excellent agreement with the reference standard for both 1.5 and 3 mm scans but results in lower agreement in the CAC severity category for 1.5 mm scans.

Impact of preoperative computed tomography image slice thickness on the planning of deep brain stimulation surgery: A phantom study

BackgroundPreoperative Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) coregistration is often applied to perform deep brain stimulation (DBS) surgeries. Thin sliced (high dose) CT is used and recommended because of the high reported accuracy but there are no comparative studies. Thin sliced CT could lead to a higher radiation exposure for the patient in contrast to thicker sliced CT (low dose) due to a longer scanning time. In this study we investigated if the preoperative CT slice thickness had an effect on the registration accuracy in a preoperative simulated DBS setting. Material and methodsAn implanted phantom, a Citrullus lanatus (watermelon), was used to acquire an MRI data set (2 millimeter (mm) T2) with a fixed reference point. Two observers targeted the reference point independently and they recorded and compared the coordinates, ring, and arc angles from all coregistered series with different CT slice thicknesses of 0.5 mm, 1 mm, 1.5 mm, 2 mm, 3 mm, 4 mm, and 5 mm. Separately, both MRI and CT were used as reference series for coregistration and analysis. Lastly, inter-observer reliability was calculated with Kendall’s coefficient of concordance (W). With W> 0.9 defined as very good. ResultsOur results show no relevant effect on the preoperative registration accuracies for the different CT’s with all absolute differences in mm for the stereotactic coordinates< 0.5 and angles in degrees< 0.4. Additionally, the inter-observer reliability was high (W 0.991). ConclusionWe found no relevant effect of increased slice thickness of preoperative CT on the preoperative registration accuracy in a simulated DBS setting.

Diagnostic accuracy for coronary artery disease by computed tomography angiography as compared to conventional invasive angiography

Background: Emerging as a major cause of death and disability in the developing countries is coronary artery disease (CAD). Traditional coronary angiography has traditionally been the preferred diagnostic procedure for CAD. Non-invasive evaluation of coronary artery disease (CAD) using computed tomography (CT) coronary angiography shows promise. This observational study's goal is to assess the relative efficacy of noninvasive multi-section computed tomography (MSCT) coronary angiography vs invasive selective coronary angiography in detecting coronary stenosis.Method and patient: This observational study carried out in the Azadi teaching Hospital/Kirkuk between November 2021 to March 2022. Patients who suspected to have coronary artery disease underwent both CTCA and invasive coronary angiography in different centers in our country comparing and analyzing their results.Result: In total, 92 participants were enrolled in the trial. Patients had a mean age of 57.207.3 years, and men made up the vast majority of those who appeared (67.3 percent). Chest pain was the most common presenting complaint (94 percent). Patients exhibited a prevalence of 84% for HTN, 55% for hyperlipidaemia, 58% for diabetes, and 4% for ischemic heart disease. In addition, 50% of the patients are either current or former smokers. Half of the patients received 64-slice CT scans, nearly half had 128-slice scans, and 3.2% got 256-slice scans. CCTA's sensitivity was 100%, and its specificity was 66.7%. Positive predictive value for CCTA was 98.8 percent (meaning it correctly identified positive cases in 98.8 percent of patients) and negative predictive value was 100 percent, for a total diagnostic accuracy of 98.9 percent (which mean CCTA can exclude all negative cases and did not miss any case). When looking at individual arteries, the LAD artery was shown to be the most accurate, while the LCX artery was the least accurate (95.6 percent and 78.2 percent respectively). In terms of sensitivity, LAD performed at a 99.1% rate, while LMS performed at a 0% rate (33.3 percent). RCA had the most specificity (95.2 percent), whereas LAD had the lowest (88.8 percent) (40 percent). In order to determine what factors, influence CCTA positivity, we performed a binary logistic regression analysis for positive CCTA (negative as reference) with all variables from the studies. The results showed that IHD, lesions in the LAD artery, lesions in the LCX artery, and CT slice thickness (128 and 256 slices) all have a negative effect on CCTA (p0.05).Conclusions: When compared to traditional angiography, multi-slice computed tomography has demonstrated superior sensitivity and specificity for the identification of coronary artery disease.

Clinical commissioning of the first point-of-care spectral photon-counting CT for the upper extremities.

Acceptance testing and quality assurance (QA) of computed tomography (CT) scans are of great importance to ensure the appropriate performance of the systems. However, current standards and guidelines do not include a dedicated QA program for spectral photon-counting CT (SPCCT), nor adapted tolerancelevels. To evaluate the technical performance, in terms of image quality and radiation dose, of the first point-of-care SPCCT for the upper extremities (MARS Extremity 5X120, MARS Bioimaging Ltd., Christchurch, New Zealand) and to establish a comprehensive QAprogram. The specific dimensions of the scanner with a 125mm diameter gantry and a small voxel size of 0.1×0.1×0.1mm3 require the use of suitable phantoms and evaluation techniques. Indicators such as CT number accuracy, image noise, uniformity, and slice thickness were assessed to characterize the image quality. The in-plane and longitudinal spatial resolutions were evaluated by means of the modulation transfer function (MTF). Noise power spectra (NPS) were calculated to further evaluate the image noise. Material identification capabilities were assessed using clinically relevant high-Z materials (iodine, gold, gadolinium, and calcium). A 100-mm diameter CTDI-like phantom was used to measure the dose indices. A complete radiation survey was carried out to measure the radiation exposure at different points around thescanner. The proposed QA program is based on international and local recommendations as well as practical experience. It includes standardised CT tests and SPCCT-specific methods. Additional methodologies to further assess the system performance are also presented. Tolerance levels are discussed and revised when appropriate. Both in-plane and longitudinal high spatial resolutions were evidenced by the MTF measurements with 1.8lp· mm-1 and 5.0lp· mm-1 at 10%, respectively. The calculated effective slice thickness ranged between 0.15and 0.16mm for the five energy bins and for a reconstructed voxel size of 0.1×0.1×0.1mm3 . Reference values of the linear attenuation coefficient of water have been calculated and used to assess the CT number uniformity of water. Evaluation of the CT number accuracy and stability of various clinically relevant materials showed excellent spectral correlation and linearity between HU values and concentrations (r2 > 0.99). The NPS showed less noise correlation between slices than within transverse slice, as well as a systematic increase at low spatial frequencies. The volume CT dose index (CTDI ) for a custom-made 100mm diameter phantom was 9.32mGy. Radiation measurements around the scanner showed that it is completely shielded except for the access port, and that no additional protective measures are necessary for thepatient. A routine QA framework for SPCCT systems has been proposed. Image quality and radiation dose were assessed using newly designed phantoms, relevant metrics, and automated algorithms. Baseline values were established and tolerance levels discussed for the MARS SPCCT scanner based on collected data and internationalrecommendations.

Abstract No. 160 MR Susceptibility-Weighted Imaging During Transurethral Prostate Sono-Ablation Procedures for Guidance of Device Placement to Counter Effect of Intra-Prostatic Calcifications

Men seeking MRI-guided transurethral ultrasound ablation (TULSA) for treatment of prostate cancer (PCa) are screened for calcifications. Large calcifications can block ultrasound (US) and cause inadequate heating. Smaller calcifications (≤3 mm) can be accommodated by aligning the ultrasound applicator (UA) with calcifications between transducer elements. We compare calcification detection and size measurement using susceptibility-weighted MRI (SWI) vs. computed tomography (CT). We also assess the impact of calcifications on ablation coverage benchmarked against a previously published pivotal trial. Pre-TULSA screening for calcifications (calcs) was performed with CT for 17 men. The mean (range) of CT slice thickness was 1.6 (0.6-5.0) mm. When relevant calcs were detected, intraprocedural SWI (1.0-mm slices) was used to guide positioning of UA elements with respect to calcs. Calcification in-plane and through-plane diameters were measured on CT and SWI, and their impact on ablation coverage was assessed using MR thermometry. Maximum temperature and thermal dose maps from MR thermometry were segmented in 90-degree quadrants across the active UA elements, with presence of calcification assessed based on SWI magnitude and phase images. 25 prostatic calcs were identified across 17 men. All calcs identified on CT were visible on SWI. In 4 men, SWI phase images were used to differentiate calcs from iron. Mean (range) diameter was 3.8 (1.4-10.4) mm on CT and 4.0 (2.2-10.8) mm using SWI. SWI diameters were larger by median 22% in at least one dimension for all men and in 42/50 measurements overall. With SWI-guided UA placement in 9 men, median (IQR) proportion of target volume reaching boiling temperature was 4.0 (2-8.0) % and 3.0 (0-7.0) % in sectors with and without calcs based on MR thermometry. Adequate thermal dose was achieved in men with and without calcs: 98 (93-100) % vs 98 (95-100) %. In the pivotal trial of 115 patients, which did not have SWI-guided UA placement, 93% (90-98%) of quadrants with calcs reached adequate thermal coverage compared with 98 (93-100)% overall and 6 (1-9)% with calcs had target volume approaching boiling vs 0 (0-5) % overall. Intraprocedural SWI detected all CT-identified calcifications, tending to overestimate the diameter but guiding effective device positioning. CT remains the gold standard for pre-TULSA calcification screening, and further studies are warranted to optimize SWI protocols, correlate the size of calcifications on CT and SWI, and predict their impact on ablation coverage.

Different CT slice thickness and contrast-enhancement phase in radiomics models on the differential performance of lung adenocarcinoma.

BackgroundTo investigate the effects of computed tomography (CT) reconstruction slice thickness and contrast‐enhancement phase on the differential diagnosis performance of radiomic signature in lung adenocarcinoma.MethodsA total of 187 patients who had been pathologically confirmed with lung adenocarcinoma and nonadenocarcinoma were divided into a training cohort (n = 149) and validation cohort (n = 38). All the patients underwent contrast‐enhanced CT and the images were reconstructed with different slice thickness. The radiomic features were extracted from different slice thickness and scan phase. The logistic regression (LR) algorithm was used to build a machine learning model for each group. The area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve and DeLong test was used to evaluate its discriminating performance.ResultsFinally, 34 image features and five semantic features were selected to establish a radiomics model. Based on the three contrast‐enhanced CT phases and four reconstruction slice thickness, 12 groups of radiomics models showed good discrimination ability with the AUCs range from 0.9287 to 0.9631, sensitivity range from 0.8349 to 0.9083, specificity range from 0.825 to 0.925 in the training group. Similar results were observed in the validation group. However, there was no statistical significance between the different CT scan phase groups and different slice thickness (p > 0.05).ConclusionsThe radiomic analysis of contrast‐enhanced CT can be used for the differential diagnosis of lung adenocarcinoma. Moreover, different slice thickness and contrast‐enhanced scan phase did not affect the discriminating ability in the radiomics models.

Applying Taguchi Methodology to Optimize the Brain Image Quality of 128-Sliced CT: A Feasibility Study

Injuries due to traffic accidents have been significant causes of death in Taiwan and traffic accidents have been most common in recent years. Brain computed tomography (CT) examinations can improve imaging quality and increase the value of an imaging diagnosis. The image quality of the brain gray/white matter was optimized using the Taguchi design with an indigenous polymethylmethacrylate (PMMA) slit gauge to imitate the adult brain and solid water phantoms. The two gauges without coating contrast media were located inside the center of a plate to simulate the brain and scanned to obtain images for further analysis. Five major parameters—CT slice thickness, milliampere-seconds, current voltage, filter type, and field of view—were optimized. Analysis of variance was used to determine individual interactions among all control parameters. The optimal experimental acquisition/settings were: slice thickness 2.5 mm, 300 mAs, 140 kVp, smooth filter, and FOV 200 mm2. Signal-to-noise was improved by 106% (p &lt; 0.001) over a routine examination. The effective dose (HE) is approximately 1.33 mSv. Further clinical verification and the image quality of the ACR 464 head phantom is also discussed.

QAMaster: A new software framework for phantom-based computed tomography quality assurance.

The regular evaluation of imaging performance of computed tomography (CT) scanners is essential for CT quality assurance. For automation of this process, the software QAMaster was developed at the Universitätsklinikum Erlangen, which provides based on CT scans of the CatPhan® 504 (The Phantom Laboratory, Salem, USA) automated image quality analysis and documentation by evaluating CT number accuracy, spatial linearity, uniformity, contrast‐noise‐ratio, spatial resolution, noise, and slice thickness. Dose assessment is supported by calculations of the weighted computed tomography dose index (CTDI w ) and weighted cone beam dose index (CBDI w ). QAMaster was tested with CatPhan® 504 scans and compared to manual evaluations of these scans, whereby high consistency of the respective results was observed. The CT numbers, spatial linearity, uniformity, contrast‐noise‐ratio, noise, and slice thickness deviated by only (0.13 ± 0.25) HU, (0.02 ± 0.05) mm, (−0.01 ± 0.03)%, 0.8 ± 1.8, (0.131 ± 0.05) HU, and (0.004 ± 0.005) mm between both evaluations, respectively. The QAMaster results for spatial resolution did not differ significantly (p = 0.34) from the CatPhan® 504 based manual resolution assessment. Dose computations were fully consistent between QAMaster and manual calculations. Thus, QAMaster proved to be a comprehensive and functional software for performing an automated CT quality assurance routine. QAMaster will be open‐source after its release.

Clinical importance of second-opinion interpretations of abdominal imaging studies in a cancer hospital and its impact on patient management

PurposeThe purpose of this retrospective study was to evaluate the quality of outside hospital imaging and associated reports submitted to us for reinterpretation related to clinical care at our tertiary cancer center. We compared the initial study interpretations to that of interpretations performed by subspecialty-trained abdominal radiologists at our center and whether this resulted in a change in inpatient treatment. Materials and methodsWe performed an institutional review board-approved retrospective single-institution study of 915 consecutive outside computed tomography (CT) and magnetic resonance (MR) abdominal imaging studies that had been submitted to our institution between August 1, 2020 and November 30, 2020. The assessed parameters included the quality and accuracy of the report, the technical quality of the imaging compared to that at our institution, the appropriateness of the imaging for staging or restaging, usage of oral and IV contrast, and CT slice thickness. Clinical notes, pathologic findings, and subsequent imaging were used to establish an accurate diagnosis and determine the effect on clinical treatment. Discrepancies between the initial and secondary interpretations were identified independently by a panel of radiologists to assess changes in treatment. The impact of discrepancies on treatment was evaluated based on current treatment guidelines. ResultsOf 744 CT (81%) and 171 MR (19%) outside imaging studies, 65% had suboptimal quality compared to the images at our institution, and 31% were inappropriate for oncological care purposes. Only 21% of CT studies had optimal slice thickness of <3 mm. Of 375 (41%) outside reports, 131 (34%) had discrepancies between secondary and initial interpretations. Of the 88 confirmed discrepant studies, 42 patients (48%) had a change in treatment based on the secondary interpretation. ConclusionsImaging studies from outside institutions have variable image quality and are often inadequate for oncologic imaging. The secondary interpretations by subspecialty-trained radiologists resulted in treatment change.

Patient-specific simulation for tracheobronchial reconstruction procedures using 3-dimensional operable models: A proof-of-concept study.

Patient-specific simulation for tracheobronchial reconstruction procedures using 3-dimensional operable models: A proof-of-concept study.

Validation of the influence of CT slice thickness on the quantitative accuracy and image quality of single photon emission computed tomography.

Computed tomography (CT) images are used for precise anatomical location of lesions and for accurate attenuation correction in single-photon emission computed tomography (SPECT) image reconstruction in SPECT/CT examination. The aim of this study was to verify the effects of varying CT collimation width and slice thickness on CT images and on CT attenuation corrected SPECT images. We acquired SPECT/CT images of a micro-coin phantom and the National Electrical Manufacturers Association body phantom filled with 99mTc-pertechnetate while varying the abovementioned CT parameters. The full width at half maximum of the slice sensitivity profile, the standard deviation of CT image background noise, and the radiation dose from CT scans were evaluated. Subsequently, the percentage contrast, background variability, and absolute recovery coefficient of the SPECT image were measured. Furthermore, we retrospectively reviewed the clinical bone SPECT images of 23 patients, and statistical testing of differences was performed. As the collimation width and reconstruction slice thickness of the CT image increased, z-axis resolution deteriorated, and background noise decreased. In addition, CT radiation dose decreased with increasing collimation width. Meanwhile, SPECT image quality and quantitative accuracy were unchanged with varying CT collimation width and slice thickness. There were no notable variations in clinical SPECT images and no statistically significant differences. When high-resolution CT slices on the z-axis are not required for clinical diagnosis, increasing collimation width or slice thickness can reduce the radiation dose and image noise with no influence on the quality of SPECT images .

Discriminating malignant and benign clinical T1 renal masses on computed tomography: A pragmatic radiomics and machine learning approach.

The aim of this study was to discriminate malignant and benign clinical T1 renal masses on routinely acquired computed tomography (CT) images using radiomics and machine learning techniques.Adult patients undergoing surgical resection and histopathological analysis of clinical T1 renal masses were included. Preoperative CT studies in venous phase from multiple referring centers were included, without restriction to specific CT scanners, slice thickness, or degrees of artifacts. Renal masses were segmented and 120 standardized radiomic features extracted. Machine learning algorithms were used to predict malignancy of renal masses using radiomics features and cross-validation. Diagnostic accuracy of machine learning models and assessment by independent blinded radiologists were compared based on the gold standard of histopathologic diagnosis.A total of 94 patients met inclusion criteria (benign renal masses: n = 18; malignant: n = 76). CT studies from 18 different scanners were assessed with median slice thickness of 2.5 mm and artifacts in 15 cases (15.9%).Area under the receiver-operating-characteristics curve (AUC) of random forest (random forest [RF], AUC = 0.83) was significantly higher compared to the radiologists (AUC = 0.68, P = .047). Sensitivity was significantly higher for RF versus radiologists (0.88 vs 0.80, P = .045), whereas specificity was numerically higher for RF (0.67 vs 0.50, P = .083).Although limited by an overall small sample size and few benign renal tumors, a radiomic features and machine learning approach suggests a high diagnostic accuracy for discrimination of malignant and benign clinical T1 renal masses on venous phase CT. The presented algorithm robustly outperforms human readers in a real-life scenario with nonstandardized imaging studies from various referring centers.

Effect of Computed Tomography Slice Thickness on Calculated Coronary Artery Calcium Score in the Assessment of Possible Radiation Induced Cardiac Toxicity

Studies have suggested that the occurrence of radiation induced cardiac toxicity in breast cancer patients is significantly higher in women with pre-existing cardiac risk factors. Therefore, it is important to quantify the relationship between radiation induced cardiac toxicity and a measurable level of pre-existing cardiac risk such as the patient’s coronary artery calcium Agatston score. To assess the extent of coronary artery calcium present in the walls of patients’ coronary arteries before they received treatment, Agatston scores may be calculated using thoracic CT scans acquired for external beam radiotherapy planning. However, these planning CT scans can vary in slice thickness and resolution, thus complicating the calculation of calcium scores using scans with slice thicknesses other than the 3mm routinely employed for traditional Agatston scoring. The objective of this project is to quantify the effect of varying CT scan slice thickness in the calculation of coronary artery calcium scores so that a method of standardization might be developed. This is accomplished through the design, fabrication, and scanning of an anthropomorphic phantom featuring calcium inserts of varying sizes. Analysis of how the scores change with increasing slice thickness is used to construct a simple linear scaling method of standardization which corrects for varying slice thickness and the resulting partial volume distortions. A linear scaling method was successfully validated for the calculation of coronary artery calcium Agatston scores across a range of slice thicknesses increasing from 0.625 mm to 5 mm. Scaling is applied by multiplying the score by the slice thickness and dividing by 3 mm. This method is potentially applicable in any clinical or research endeavour which calls for retroactive cardiac calcium quantification. With a simple linear scaling method, external beam radiation therapy planning CT scans with slice thicknesses ranging from 0.625 mm to 5 mm can be used to calculate coronary artery calcium Agatston scores and thereby measure a patient’s level of cardiac risk before treatment.

Improved Computed Tomography Accuracy with a 1-mm versus 2- or 3-mm Slice Thickness for the Detection of Medial Coronoid Disease in Dogs

Computed tomography (CT) is used complementarily to radiography for the evaluation of medial coronoid disease (MCD). We hypothesized that a slice thickness > 2 mm would significantly affect the image quality and detection of fragmentation of the medial coronoid process. This study aimed to assess CT features indicating direct and indirect evidence of MCD in 168 CT studies with slice thicknesses of 1-, 2- and 3 mm. The CT studies were blinded in terms of CT slice thickness and patient data and randomly assessed by two independent observers. All dogs underwent arthroscopic evaluation of the elbow joints. Both observers were unaware of the arthroscopic findings. Notably, blurring of the bone contour (p = 0.0001) was significantly influenced by slice thickness; here, a 1-mm thickness yielded a predominantly sharp and well-defined bone contour (observer 1, 91%; observer 2, 79%), whereas 2- (observer 1, 39.3%; observer 2, 56.3%) and especially 3-mm slice thicknesses yielded blurred margins with significantly reduced sharpness (observer 1, 0%; observer 2, 12.5%). The 1-mm slice thickness also yielded the highest fragment detection rate (observer 1, 55.4%; observer 2, 60.4%). Furthermore, the detection of fragment positions and of single fragments and fissures differed substantially with slice thickness. The findings of this study support the hypothesis that a CT slice thickness of ≥ 2 mm significantly affects fragment detection. In conclusion, a CT slice thickness of at least 1 mm is recommended for the assessment of MCD of the canine elbow.

Enhanced Protocols for CT Slice Thickness on Clinical Target Volume for 3d Radiation Therapy

Radiation Therapy is used to treat the cancer diseases by ionization of radiations. From the beginning the aim of radiation therapy is to cure the cancer without any side effects. Tumour location and type, geometric accuracy and involvement in anatomic area affect the output of radiation therapy in which the amount of radiation dose is given. The tumour is controlled by production of high dosage of radiation. The amount of dosage is limited by possibility of damage of normal tissue. To control the amount of dose, for three dimensional radiation therapy computed tomography (CT) slice thickness is proposed in this paper. This paper defines the changes of CTV (clinical target volume) using various computed tomography slice thickness on three dimensional radiation therapy. For all computed tomography datasets, planning of three dimensional treatments is achieved.

Markerless tumor tracking using fast-kV switching dual-energy fluoroscopy on a benchtop system.

To evaluate markerless tumor tracking (MTT) using fast-kV switching dual-energy (DE) fluoroscopy on a bench top system. Fast-kV switching DE fluoroscopy was implemented on a bench top which includes a turntable stand, flat panel detector, and x-ray tube. The customized generator firmware enables consecutive x-ray pulses that alternate between programmed high and low energies (e.g., 60 and 120kVp) with a maximum frame rate of 15Hz. In-house software was implemented to perform weighted DE subtraction of consecutive images to create an image sequence that removes bone and enhances soft tissues. The weighting factor was optimized based on gantry angle. To characterize this system, a phantom was used that simulates the chest anatomy and tumor motion in the lung. Five clinically relevant tumor sizes (5-25mm diameter) were considered. The targets were programmed to move in the inferior-superior direction of the phantom, perpendicular to the x-ray beam, using a cos4 waveform to mimic respiratory motion. Target inserts were then tracked with MTT software using a template matching method. The optimal computed tomography (CT) slice thickness for template generation was also evaluated. Tracking success rate and accuracy were calculated in regions of the phantom where the target overlapped ribs vs spine, to compare the performance of single energy (SE) and DE imaging methods. For the 5mm target, a CT slice thickness of 0.75mm resulted in the lowest tracking error. For the larger targets (≥10mm) a CT slice thickness ≤2mm resulted in comparable tracking errors for SE and DE images. Overall DE imaging improved MTT accuracy, relative to SE imaging, for all tumor targets in a rotational acquisition. Compared to SE, DE imaging increased tracking success rate of small target inserts (5 and 10mm). For fast motion tracking, success rates improved from 23% to 64% and 74% to 90% for 5 and 10mm targets inserts overlapping ribs, respectively. For slow moving targets success rates improved from 19% to 59% and 59% to 91% in 5 and 10mm targets overlapping the ribs, respectively. Similar results were observed when the targets overlapped the spine. For larger targets (≥15mm) tracking success rates were comparable using SE and DE imaging. This work presents the first results of MTT using fast-kV switching DE fluoroscopy. Using DE imaging has improved the tracking accuracy of MTT, especially for small targets. The results of this study will guide the future implementation of fast-kV switching DE imaging using the on-board imager of a linear accelerator.

Prevalence of Radiographic Cochlear–Facial Nerve Dehiscence

To determine the prevalence of radiographic cochlear-facial nerve dehiscence (CFD). Retrospective radiological study. Two tertiary-referral centers. Two hundred six temporal-bone computed tomography (CT) scans (405 total ears) of otology/neurotology patients from two academic institutions between the years 2014 and 2017. Diagnostic. The cochlear-facial nerve partition width (CFPW) was measured on coronal CT sections and defined as the shortest distance between the cochlear basal turn and facial nerve (FN) labyrinthine segment. We used logistics regression analyses to determine positive predictors for radiographic evidence of CFD. The overall prevalence of radiographic CFD was 5.4% (22/406 ears). 9.2% of patients (19/206) had CFD. Of these 19 patients, only one patient had mixed hearing loss that could not be explained by any other vestibular or auditory etiology. Three out of 206 patients had dehiscence in both ears (1.4%). The average CFPW was 0.6 ± 0.2 mm, and fallopian canal width was 1.1 ± 0.02 mm (n = 405). Older age, use of traditional CT scans, and thinner CT slice thickness were significant predictors for radiographic CFD. The radiographic prevalence of CFD is higher than what is reported in histologic studies, and may over-estimate the true prevalence of CFD. The clinician should keep this in mind when considering this as potential cause for third-window symptoms.