Clinical application of high-resolution spiral CT scanning in the diagnosis of auriculotemporal and ossicle.

Precision and intelligence in evaluating the complexities of middle ear structures are required to diagnose auriculotemporal and ossicle-related diseases within otolaryngology. Due to the complexity of the anatomical details and the varied etiologies of illnesses such as trauma, chronic otitis media, and congenital anomalies, traditional diagnostic procedures may not yield accurate diagnoses. This research intends to enhance the diagnosis of diseases of the auriculotemporal region and ossicles by combining High-Resolution Spiral Computed Tomography (HRSCT) scanning with Deep Learning Techniques (DLT). This study employs a deep learning method, Convolutional Neural Network-UNet (CNN-UNet), to extract sub-pixel information from medical photos. This method equips doctors and researchers with cutting-edge resources, leading to groundbreaking discoveries and better patient healthcare. The research effort is the interaction between the CNN-UNet model and high-resolution Computed Tomography (CT) scans, automating activities including ossicle segmentation, fracture detection, and disruption cause classification, accelerating the diagnostic process and increasing clinical decision-making. The suggested HRSCT-DLT model represents the integration of high-resolution spiral CT scans with the CNN-UNet model, which has been fine-tuned to address the nuances of auriculotemporal and ossicular diseases. This novel combination improves diagnostic efficiency and our overall understanding of these intricate diseases. The results of this study highlight the promise of combining high-resolution CT scanning with the CNN-UNet model in otolaryngology, paving the way for more accurate diagnosis and more individualized treatment plans for patients experiencing auriculotemporal and ossicle-related disruptions.

Volumetric Analysis of Hand and Rotary Instrumentation, Root Canal Filling Techniques, and Obturation Materials in Primary Teeth Using Spiral CT.

AIM AND BACKGROUND: To compare the root canal volume in primary teeth using hand and rotary instruments and to evaluate root canal filling techniques and flow of root canal obturation materials in the postinstrumented root canal volume using spiral computed tomography (SCT). MATERIALS AND METHODS: Freshly extracted 16 primary molars were randomly divided into two groups and subjected to SCT analysis before and after instrumentation. For the manual technique (group I) with eight teeth were prepared using K files, and rotary (group II) eight teeth preparation was performed with ProTaper files. The filled volume in each canal was measured using SCT, and the percentage of obturated volume was calculated. The data were statistically analyzed using the Mann-Whitney U test. RESULTS: There was a statistically significant difference in both groups' volume of root canals enlarged. Even though both K files and the ProTaper system brought about enlarged canals after instrumentation, there was a statistically significant increase in volume after using K files in two canals. In three canals, there was a statistically significant increase in volume after using ProTaper. Irrespective of the obturation technique and materials used, there is no statistically significant difference in the volume after obturation. CONCLUSION: From the results of this study, the ProTaper file system shows suitable volumetric enlargement up to an optimum level, which is needed in primary root canal walls, and is better in canal shaping, as evidenced by good postobturation volume. CLINICAL SIGNIFICANCE: The traditional method of cleaning and shaping the root canals in permanent teeth using manual stainless-steel files can lead to undesirable curvatures in root canal morphology, making correctly filling the root canals difficult. It is also time-consuming and sometimes leads to iatrogenic errors. Rotary nickel-titanium (Ni-Ti) instrumentation techniques have been developed to overcome these problems. How to cite this article: Yadav DBUC, Varma RB, Kumar JS, et al. Volumetric Analysis of Hand and Rotary Instrumentation, Root Canal Filling Techniques, and Obturation Materials in Primary Teeth Using Spiral CT. J Contemp Dent Pract 2024;25(3):250-259.

Influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting detector CT.

The goal of this experimental study was to quantify the influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting CT (UHR-PCCT). Cervical and lumbar spine, pelvis, and upper legs of two fresh-frozen cadaveric specimens were subjected to nine dose-matched UHR-PCCT scan protocols employing a collimation of 120 × 0.2 mm with varying pitch (0.3/1.0/1.2) and rotation time (0.25/0.5/1.0 s). Image quality was analyzed independently by five radiologists and further substantiated by placing normed regions of interest to record mean signal attenuation and noise. Effective mAs, CT dose index (CTDIvol), size-specific dose estimate (SSDE), scan duration, and raw data file size were compared. Regardless of anatomical region, no significant difference was ascertained for CTDIvol (p ≥ 0.204) and SSDE (p ≥ 0.240) among protocols. While exam duration differed substantially (all p ≤ 0.016), the lowest scan time was recorded for high-pitch protocols (4.3 ± 1.0 s) and the highest for low-pitch protocols (43.6 ± 15.4 s). The combination of high helical pitch and short gantry rotation times produced the lowest perceived image quality (intraclass correlation coefficient 0.866; 95% confidence interval 0.807-0.910; p < 0.001) and highest noise. Raw data size increased with acquisition time (15.4 ± 5.0 to 235.0 ± 83.5 GByte; p ≤ 0.013). Rotation time and pitch factor have considerable influence on image quality in UHR-PCCT and must therefore be chosen deliberately for different musculoskeletal imaging tasks. In examinations with long acquisition times, raw data size increases considerably, consequently limiting clinical applicability for larger scan volumes.

Impact of beam collimation of z-overscanning on dose to the lens and thyroid gland in paediatric thoracic computed tomography imaging.

BACKGROUND: Adaptive collimation reduces the dose deposited outside the imaged volume along the z-axis. An increase in the dose deposited outside the imaged volume (to the lens and thyroid) in the z-axis direction is a concern in paediatric computed tomography (CT). OBJECTIVE: To compare the dose deposited outside the imaged volume (to the lens and thyroid) between 40-mm and 80-mm collimation during thoracic paediatric helical CT. MATERIALS AND METHODS: We used anthropomorphic phantoms of newborns and 5-year-olds with 40-mm and 80-mm collimation during helical CT. We compared the measured dose deposited outside the imaged volume using optically stimulated luminescence dosimeters (OSLD) at the surfaces of the lens and thyroid and the image noise between the 40-mm and 80-mm collimations. RESULTS: There were significant differences in the dose deposited outside the imaged volume (to the lens and thyroid) between the 40-mm and 80-mm collimations for both phantoms (P < 0.01). CONCLUSION: Compared with that observed for 80-mm collimation in helical CT scans of the paediatric thorax, the dose deposited outside the imaged volume (to the lens and thyroid) was significantly lower in newborns and 5-year-olds with 40-mm collimation.

Reducing windmill artifacts in clinical spiral CT using a deep learning-based projection raw data upsampling: Method and robustness evaluation.

BACKGROUND: Multislice spiral computed tomography (MSCT) requires an interpolation between adjacent detector rows during backprojection. Not satisfying the Nyquist sampling condition along the z-axis results in aliasing effects, also known as windmill artifacts. These image distortions are characterized by bright streaks diverging from high contrast structures. PURPOSE: The z-flying focal spot (zFFS) is a well-established hardware-based solution that aims to double the sampling rate in longitudinal direction and therefore reduce aliasing artifacts. However, given the technical complexity of the zFFS, this work proposes a deep learning-based approach as an alternative solution. METHODS: We propose a supervised learning approach to perform a mapping between input projections and the corresponding rows required for double sampling in the z-direction. We present a comprehensive evaluation using both a clinical dataset obtained using raw data from 40 real patient scans acquired with zFFS and a synthetic dataset consisting of 100 simulated spiral scans using a phantom specifically designed for our problem. For the clinical dataset, we utilized 32 scans as training set and 8 scans as validation set, whereas for the synthetic dataset, we used 80 scans for training and 20 scans for validation purposes. Both qualitative and quantitative assessments are conducted on a test set consisting of nine real patient scans and six phantom measurements to validate the performance of our approach. A simulation study was performed to investigate the robustness against different scan configurations in terms of detector collimation and pitch value. RESULTS: In the quantitative comparison based on clinical patient scans from the test set, all network configurations show an improvement in the root mean square error (RMSE) of approximately 20% compared to neglecting the doubled longitudinal sampling by the zFFS. The results of the qualitative analysis indicate that both clinical and synthetic training data can reduce windmill artifacts through the application of a correspondingly trained network. Together with the qualitative results from the test set phantom measurements it is emphasized that a training of our method with synthetic data resulted in superior performance in windmill artifact reduction. CONCLUSIONS: Deep learning-based raw data interpolation has the potential to enhance the sampling in z-direction and thus minimize aliasing effects, as it is the case with the zFFS. Especially a training with synthetic data showed promising results. While it may not outperform zFFS, our method represents a beneficial solution for CT scanners lacking the necessary hardware components for zFFS.

[Effectiveness Evaluation of Low-dose Spiral Computed Tomography 
for Lung Cancer Screening in Minhang District of Shanghai].

BACKGROUND: Low-dose spiral computed tomography (LDCT) has been recommended for lung cancer screening in high-risk populations. However, evidence from Chinese populations was limited due to the different criteria for high-risk populations and the short-term follow-up period. This study aimed to evaluate the effectiveness in Chinese adults based on the Lung Cancer Screening Program in Minhang District of Shanghai initiated in 2013. METHODS: A total of 26,124 subjects aged 40 years or above were enrolled in the Lung Cancer Screening Program during the period of 2013 and 2017. Results of LDCT examination, and screen-detected cancer cases in all participants were obtained from the Reporting System of the Lung Cancer Screening Program. The newly-diagnosed cases and their vital status up to December 31, 2020 were identified through a record linkage with the Shanghai Cancer Registry and the Shanghai Vital Statistics. Standardized incidence ratio (SIR) and 95%CI were calculated using the local population at ages of 40 or above as the reference. Proportions of early-stage cancer (stage 0-I), pathological types, and 5-year observed survival rates of lung cancer cases were estimated and compared between the cases derived from the screened and non-screened populations. Cox regression models were applied to evaluate the hazard ratio (HR) and 95%CI of LDCT screening with all-cause death of the lung cancer cases. RESULTS: The crude and age-standardized incidence of lung cancer in screened population were 373.3 (95%CI: 343.1-406.1) and 70.3 per 100,000 person-years, respectively, with an SIR of 1.8 (95%CI: 1.6-1.9), which was observed to decrease with following-up time. The early-stage cancer accounted for 49.4% of all lung cancer cases derived from the screened population, significantly higher than 38.4% in cases from the non-screened population during the same period (P<0.05). The proportion of lung adenocarcinoma (40.7% vs 35.9%) and 5-year survival rate (53.7% vs 41.5%) were also significantly higher in the cases from the screened population (all P<0.05). LDCT screening was associated with 30% (HR=0.7, 95%CI: 0.6-0.8) reduced all-cause deaths of the cases. CONCLUSIONS: The participants of the screening program are at high-risk of lung cancer. LDCT favors the early-detection of lung cancer and improves 5-year survival of the screened cases, indicating a great potential of LDCT in reducing the disease burden of lung cancer in Chinese populations.

Use of Computed Tomography-Based Texture Analysis to Differentiate Benign From Malignant Salivary Gland Lesions.

OBJECTIVE: Salivary gland lesions show overlapping morphological findings and types of time/intensity curves. This research aimed to evaluate the role of 2-phase multislice spiral computed tomography (MSCT) texture analysis in differentiating between benign and malignant salivary gland lesions. METHODS: In this prospective study, MSCT was carried out on 90 patients. Each lesion was segmented on axial computed tomography (CT) images manually, and 33 texture features and morphological CT features were assessed. Logistic regression analysis was used to confirm predictors of malignancy ( P < 0.05 was considered to be statistically significant), followed by receiver operating characteristics analysis to assess the diagnostic performance. RESULTS: Univariate logistic regression analysis revealed that morphological CT features (shape, size, and invasion of adjacent tissues) and 17 CT texture parameters had significant differences between benign and malignant lesions ( P < 0.05). Multivariate binary logistic regression demonstrated that shape, invasion of adjacent tissues, entropy, and inverse difference moment were independent factors for malignant tumors. The diagnostic accuracy values of multivariate binary logistic models based on morphological parameters, CT texture features, and a combination of both were 87.8%, 90%, and 93.3%, respectively. CONCLUSIONS: Two-phase MSCT texture analysis was conducive to differentiating between malignant and benign neoplasms in the salivary gland, especially when combined with morphological CT features.

Neumoencéfalo como complicación de bloqueo regional epidural por radiculopatía lumbosacra / Pneumocephalus as a Complication of Regional Epidural Block Due to Lumbosacral Radiculopathy

Introducción: El neumoencéfalo (sinonimia: aerocele o neumatocele intracerebral), se define como la presencia de gas dentro de cualquiera de los compartimentos intracraneales (intraventricular, intraparenquimatosa, subaracnoidea, subdural y epidural). Objetivo: Describir los hallazgos clínicos, estudios complementarios, conducta terapéutica y evolución de un caso con neumoencéfalo como complicación de bloqueo regional epidural por radiculopatía lumbosacra. Presentación de caso: Se presentó un paciente masculino de 57 años de edad que comenzó con un cuadro súbito de desorientación, excitabilidad psicomotriz y convulsiones tónico-clónicas, a partir de una inyección epidural de metilprednisolona como método analgésico. Conclusiones: El caso presentado exhibió manifestaciones neurológicas inespecíficas, la aparición súbita posterior al proceder invasivo hizo sospechar en un evento neurológico agudo o fenómeno tromboembólico. Los estudios complementarios como la tomografía axial computarizada craneal simple, permitió su diagnóstico para tener una conducta consecuente. El manejo conservador del neumoencéfalo como complicación del uso de anestesia epidural, constituyó una conducta terapéutica eficaz y repercutió en la satisfactoria evolución del paciente(AU)

Introduction: Pneumocephalus (synonym: aerocele or intracerebral pneumatocele), is defined as the presence of gas within any of the intracranial compartments (intraventricular, intraparenchymal, subarachnoid, subdural and epidural). Objective: To describe the clinical findings, complementary studies, therapeutic conduct and evolution of a case with pneumocephalus as a complication of regional epidural block due to lumbosacral radiculopathy Case presentation: A 57-year-old male patient was presented who began with a sudden episode of disorientation, psychomotor excitability and tonic-clonic seizures, following an epidural injection of methylprednisolone as an analgesic method. Conclusions: The case presented exhibited non-specific neurological manifestations, the sudden appearance after the invasive procedure raised suspicion of an acute neurological event or thromboembolic phenomenon. Complementary studies such as simple cranial computed axial tomography, allowed its diagnosis to have a consistent conduct. The conservative management of pneumocephalus as a complication of the use of epidural anesthesia constituted an effective therapeutic approach and had an impact on the patient's satisfactory evolution(AU)

Usefulness of electrocardiogram mA modulation during the electrocardiogram-gated CT scan in paediatrics with high heart rate for different helical pitch: a phantom-based assessment study.

We investigated the effect of electrocardiographic (ECG) mA-modulation of ECG-gated scans of computed tomography (CTA) on radiation dose and image noise at high heart rates (HR) above 100 bpm between helical pitches (HP) 0.16 and 0.24. ECG mA-modulation range during ECG-gated CTA is 50-100 mA, the phase setting is 40-60% and the scan range is 90 mm for clinical data during HR for 90, 120 and 150 bpm. Radiation dose and image noise in Housfield units are measured for CT equipment during HR for 90, 120 and 150 bpm between HP 0.16 and 0.24. ECG mA-modulation, dose reduction ratio for HR 90, 120 and 150 bpm are 19.1, 13.4 and 8.7% at HP 0.16 and 17.1, 13.3 and 7.7% at HP 0.24, respectively. No significant differences were observed in image noise between both HP. Dose reductions of 8-24% are achieved with ECG mA-modulation during ECG-gated CCTA scan, which is beneficial even in high HR more than 100 bpm.

Benign-malignant classification of pulmonary nodules by low-dose spiral computerized tomography and clinical data with machine learning in opportunistic screening.

BACKGROUND: Many people were found with pulmonary nodules during physical examinations. It is of great practical significance to discriminate benign and malignant nodules by using data mining technology. METHODS: The subjects' demographic data, baseline examination results, and annual follow-up low-dose spiral computerized tomography (LDCT) results were recorded. The findings from annual physical examinations of positive nodules, including highly suspicious nodules and clinically tentative benign nodules, was analyzed. The extreme gradient boosting (XGBoost) model was constructed and the Grid Search CV method was used to select the super parameters. External unit data were used as an external validation set to evaluate the generalization performance of the model. RESULTS: A total of 135,503 physical examinees were enrolled. Baseline testing found that 27,636 (20.40%) participants had clinically tentative benign nodules and 611 (0.45%) participants had highly suspicious nodules. The proportion of highly suspicious nodules in participants with negative baseline was about 0.12%-0.46%, which was lower than the baseline level except the follow-up of >5 years. In the 27,636 participants with clinically tentative benign nodules, only in the first year of LDCT re-examination was the proportion of highly suspicious nodules (1.40%) significantly greater than that of baseline screening (0.45%) (p < 0.001), and the proportion of highly suspicious nodules was not different between the baseline screening and other follow-up years (p > 0.05). Furthermore, 322 cases with benign nodules and 196 patients with malignant nodules confirmed by surgery and pathology were compared. A model and the top 15 most important clinical variables were determined by XGBoost algorithm. The area under the curve (AUC) of the model was 0.76 [95% CI: 0.67-0.84], and the accuracy was 0.75. The sensitivity and specificity of the model under this threshold were 0.78 and 0.73, respectively. In the validation of model using external data, the AUC was 0.87 and the accuracy was 0.80. The sensitivity and specificity were 0.83 and 0.77, respectively. CONCLUSIONS: It is important that pulmonary nodules could be more accurately identified at the first LDCT examination. A model with 15 variables which are routinely measured in the clinic could be helpful to distinguish benign and malignant nodules. It could help the radiological team issue a more accurate report; and it may guide the clinical team regarding LDCT follow-up.

ASSESSMENT OF OVERRANGING AS A FUNCTION OF PITCH, COLLIMATION AND ROTATION TIME FOR THREE OF THE MOST RECENT AND WIDESPREAD CT SCANS IN FRANCE.

PURPOSE: to assess overranging (OR) as a function of pitch, collimation and rotation time for three commonly used CT models in France. METHODS: OR was measured using XR-SP2 Gafchromic films (Ashland, USA) and computed from exposure data for three widely used CT models in France. The impact of collimation, pitch and rotation time on OR was analyzed while comparing the three CT models. RESULTS: for a typical head protocol, measured OR was found to be equal to 1.64 cm for CT scan A, 0.5 cm for CT scan B and 3.44 cm for CT scan C. OR values were respectively of 4.47, 3.24 and 7.81 cm for the typical chest protocol and the 3 CT models. OR was lowest at pitch values <1 for CT scan A, while it linearly increased with pitch for CT scan B and was lowest for high pitch values for CT scan C. Additionally, OR increase with collimation (24 mm to 38.4 mm) was most pronounced for CT scan B (factor of 2.2 for low pitch (0.5) and 2.8 for high pitch (1.2)) while it increased linearly regardless of the pitch for CT scans A and C. Rotation time also proved to slightly affect OR mainly for CT scan B (up to 2.2 mm). CONCLUSION: the present study shows that overranging remains an issue in modern CT scanners with large disparities across the vendors.

Diagnostic Value Comparison between Multislice Spiral Computerized Tomography and Magnetic Resonance Imaging under Artificial Intelligence Algorithm in Diagnosing Occult Fractures of the Knee Joint.

The aim of this study was to explore the application value of multislice spiral computerized tomography (MSCT) and magnetic resonance imaging (MRI) under intelligent algorithm in the diagnosis of occult fractures of the knee joint (OFKJ). 47 patients with negative X-ray examination and suspected fracture were included for this research. According to the examination methods, the patients were divided into the MSCT group and MRI group. The diagnostic results of the two methods were compared, and then compared with the traditional algorithm to explore their superiorities. The results demonstrated that the algorithm applied in this study had a clearer segmentation than traditional algorithms, and it run significantly faster than other algorithms. The results of MSCT, MRI, and pathological examination were all different, but which was of no statistical significance, P > 0.05. The specificity, accuracy, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) of MSCT were 83%, 96%, 94%, and 98%, respectively; and its coincidence rate, missed diagnosis rate, and misdiagnosis rate were 98.20%, 1.60%, and 0.20%, respectively. Compared with MRI, the differences were significant statistically, P < 0.05. The segmentation effect of MSCT was closer to the standard segmentation, with the higher efficiency. MSCT under the intelligent algorithm produced the better diagnostic performance and the higher detection rate than MRI in diagnosing OFKJ. It could be used for clinical auxiliary diagnosis and evaluation of OFKJ, deserving an application value.

Spiral CT Image Characteristics and Differential Diagnosis Secondary Pulmonary Tuberculosis and Lung Cancer Based on Visual Sensors.

Helical CT plain scan has high spatial and area resolution, which is beneficial to the extraction of CT features of pulmonary nodules, and is of great significance for the diagnosis and differential diagnosis of pulmonary diseases. In order to deeply study the role of visual sensor image algorithm in CT image, this paper adopts clinical simulation method, data fusion method, and image acquisition method to collect images, analyze CT image features, and simplify the algorithm and create a CT model that can better diagnose secondary tuberculosis and lung cancer. We selected 45 patients with lung disease in this group, with an average age of 38 years. At the same time, the consistency analysis results of the diameter and plain CT value data of the five groups of cases measured by two observers are between 0.82 and 0.88, which has a good consistency. We could find that the nodule diameters of the five groups of cases were different (F =16.99, P < 0.01), and the difference was statistically significant (P < 0.06), indicating that our data are not only accurate but also very reliable. ROC was used to analyze the precise value of CT values in the pulmonary tuberculosis group and lung cancer group, intrapulmonary lymph node group, and pulmonary hamartoma group to determine the cutoff value. The results showed that the AUC values of the pulmonary tuberculosis group and the lung cancer group were 0.788, and the middle was the largest, indicating that the values were guaranteed. The basic realization starts with visual sensor technology and designs a clinical model that can more accurately identify CT images and differential diagnosis.

Clinical Application of Spiral CT Reconstruction Imaging in Patients with Tracheal Stenosis before Anesthesia.

In order to solve the problem of CT reconstruction imaging, this paper presents a study on the clinical application of preanesthesia in patients with tracheal stenosis. Patients with tracheal stenosis and multislice spiral CT virtual endoscopy (CTVE) were diagnosed, and their application effects were analyzed. Methods. 60 patients with tracheal stenosis were selected for clinical observation. The patients were given tracheal stenosis examination and multislice spiral CT virtual endoscopy. The examination results of the two groups were compared and analyzed by statistical methods. Results. There was no significant difference in the detection rate, sensitivity, accuracy, and specificity between the two groups (P > 0.05). Conclusion. Multislice spiral CT virtual endoscopy combined with a fiberoptic bronchoscope for clinical diagnosis of tracheal stenosis can complement each other. Combined use can effectively improve the detection consistency, and is safe and reliable. It can be used as an effective means for the diagnosis of tracheal stenosis.

[Low-dose Spiral Computed Tomography in Lung Cancer Screening].

Lung cancer is one of the malignant tumors with the highest morbidity and mortality in the world. The low early diagnosis rate and poor prognosis of patients have caused serious social burden. Regular screening of high-risk population by low-dose spiral computed tomography (LDCT) can significantly improve the early diagnosis rate of lung cancer and bring new opportunities for the diagnosis and treatment of lung cancer. In recent years, LDCT lung cancer screening programs have been carried out in many countries around the world and achieved good results, but there are still some controversies in the selection of screening subjects, screening frequency, cost effectiveness and other aspects. In this paper, the key factors of LDCT lung cancer screening, screening effect, pulmonary nodule management and artificial intelligence contribution to the development of LDCT will be reviewed, and the application progress of LDCT in lung cancer screening will be discussed.
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Clinical implementation of kVCT-guided tomotherapy with ClearRT.

A helical fan-beam kilovoltage computed tomography (kVCT) was recently introduced into Tomotherapy units. This study aims to share the initial experience of kVCT in clinical workflow, compare its performance with that of the existing megavoltage computed tomography (MVCT), and explore its potential in adaptive planning. We retrospectively enrolled 23 patients who underwent both MVCT and kVCT scans. The clinical performance data regarding image acquisition time, nominal dose length product (DLP), registration time and registration corrections were extracted and compared. Image quality was scored by six experienced radiation therapists and quantified based on phantom measurements. CT number stability and the implementation of adaptive radiotherapy were dosimetrically evaluated by performing the dose recalculation on kVCT. Compared to MVCT, kVCT significantly reduced DLP (except the highest kVp protocol), image acquisition and registration time. KVCT obtained higher scores than MVCT on all criteria except artifacts. Phantom measurements also revealed a better image performance characterization of kVCT except for image uniformity. The CT number variation could lead to a dose difference of 0.5% for D95% of target and Dmean of organ-at-risk. For the treatment planning with kVCT, a systematic dose difference (> 1%) in PTV dose metrics was observed at regions with large longitudinal density discontinuities compared to the reference plans. The new kVCT imaging provides enhanced soft-tissue visualization. The improved efficiency with kVCT-guided treatment will allow more patients to be treated each day. In most cases, the dose calculation accuracy of kVCT images is acceptable except for regions with severe artifacts.

Clinical assessment of image quality, usability and patient comfort in dedicated spiral breast computed tomography.

OBJECTIVE: To investigate aspects of image quality, feasibility and patient comfort in dedicated spiral breast computed tomography (B-CT) in a large patient cohort. METHODS: This retrospective study was approved by the institutional review board. 2418 B-CT scans from 1222 women examined between 04/16/2019 and 04/13/2022 were analyzed. Patients evaluated their comfort during the examination, radiographers carrying out the scans evaluated the patient's mobility and usability of the B-CT device, whereas radiologists assessed lesion contrast, detectability of calcifications, breast coverage and overall image quality. For semi-quantitative assessment, a Likert-Scale was used and statistical significance and correlations were calculated using ANOVAs and Spearman tests. RESULTS: Comfort, mobility and usability of the B-CT were rated each with either "no" or "negligible" complaints in >99%. Image quality was rated with "no" or "negligible complaints" in 96.7%. Lesion contrast and detectability of calcifications were rated either "optimal" or "good" in 92.6% and 98.4%. "Complete" and "almost complete" breast coverage were reported in 41.9%, while the pectoral muscle was found not to be covered in 56.0%. Major parts of the breast were not covered in 2.1%. Some variables were significantly correlated, such as age with comfort (ρ = -0.168, p < .001) and mobility (ρ = -0.172, p < .001) as well as patient weight with lesion contrast (ρ = 0.172, p < .001) and breast coverage (ρ = -0.109, p < .001). CONCLUSIONS: B-CT provides high image quality and contrast of soft tissue lesions as well as calcifications, while covering the pre-pectoral areas of the breast remains challenging. B-CT is easy to operate for the radiographer and comfortable for the majority of women.

Application Value of MRI Combined with MSCT in Diagnosis and Staging of Colon Carcinoma.

Objective: To clarify the application value of magnetic resonance imaging (MRI) combined with multislice spiral computed tomography (MSCT) in the diagnosis and staging of colon carcinoma (CC). Methods: A total of 103 patients with histopathologically diagnosed CC were enrolled. Patient clinical and imaging data were collected, and MRI and MSCT images were analyzed to assess the accuracy of MRI, MSCT, and their combination in diagnosing tumor (T) staging of CC. Results: Among the 103 cases of histopathologically diagnosed CC, 26 cases (25.24) were in stage T1-2, 72 cases (69.90) were in stage T3, and 5 cases (4.85) were in stage T4. The accuracy of MRI in diagnosing stage T1-2, T3, and T4 was 80.77%, 88.89%, and 60.00%, respectively, with an average of 76.55%. The accuracy rates of MSCT in diagnosing T1-2, T3, and T4 stages were 73.08%, 90.27%, and 60.00%, respectively, with an average of 74.45%. The accuracy rates of MRI+MSCT in diagnosing T1-2, T3, and T4 were 88.46%, 95.83%, and 80.00%, respectively, with an average of 88.10%. Conclusions: Compared with single use of MRI or MSCT, MRI+MSCT provides accurate imaging data with higher accuracy, which is more helpful for the T-staging evaluation of CC.

Diagnosis of Liver Cirrhosis and Liver Fibrosis by Artificial Intelligence Algorithm-Based Multislice Spiral Computed Tomography.

This research was aimed at investigating the artificial intelligence (AI) segmentation algorithm-based multislice spiral computed tomography (MSCT) in the diagnosis of liver cirrhosis and liver fibrosis. Besides, it was aimed at providing new methods for the diagnosis of liver cirrhosis and liver fibrosis. All patients were divided into the control group, mild liver fibrosis group, and significant liver fibrosis group. A total of 112 patients were included, with 40 cases in the mild liver fibrosis group, 48 cases in the significant liver fibrosis group, and 24 cases who underwent computed tomography (CT) examination in the control group. In the research, deconvolution algorithm of AI segmentation algorithm was adopted to process the images. The average hepatic arterial fraction (HAF) values of patients in the control group, mild liver fibrosis group, and severe liver fibrosis group were 17.59 ± 10.03%, 18.23 ± 5.57%, and 20.98 ± 6.63%, respectively. The average MTT values of patients in the control group, mild liver fibrosis group, and severe liver fibrosis group were 12.69 ± 1.78S, 12.53 ± 2.05S, and 12.04 ± 1.57S, respectively. The average blood flow (BF) values of patients in the control group, mild liver fibrosis group, and severe liver fibrosis group were 105.68 ± 15.57 mL 100 g-1·min-1, 116.07 ± 16.5 mL·100 g-1·min-1, and 110.39 ± 16.32 mL·100 g-1·min-1, respectively. Besides, the average blood volume (BV) values of patients in the control group, mild liver fibrosis group, and significant liver fibrosis group were 15.69 ± 4.35 mL·log-1, 16.97 ± 2.68 mL·log-1, and 16.11 ± 4.87 mL·100 g-1, respectively. According to statistics, the differences among the average HAF, MTT, BF, and BV values showed no statistical meaning. AI segmentation algorithm-based MSCT imaging could promote the diagnosis of liver cirrhosis and liver fibrosis effectively and offer new methods to clinical diagnosis of liver cirrhosis and liver fibrosis.