Analysis Of Computed Tomography Scans Research Articles

Predicting pancreatic ductal adenocarcinoma using artificial intelligence analysis of pre-diagnostic computed tomography images.

Early stage diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC) is challenging due to the lack of specific diagnostic biomarkers. However, stratifying individuals at high risk of PDAC, followed by monitoring their health conditions on regular basis, has the potential to allow diagnosis at early stages. To stratify high risk individuals for PDAC by identifying predictive features in pre-diagnostic abdominal Computed Tomography (CT) scans. A set of CT features, potentially predictive of PDAC, was identified in the analysis of 4000 raw radiomic parameters extracted from pancreases in pre-diagnostic scans. The naïve Bayes classifier was then developed for automatic classification of CT scans of the pancreas with high risk for PDAC. A set of 108 retrospective CT scans (36 scans from each healthy control, pre-diagnostic, and diagnostic group) from 72 subjects was used for the study. Model development was performed on 66 multiphase CT scans, whereas external validation was performed on 42 venous-phase CT scans. The system achieved an average classification accuracy of 86% on the external dataset. Radiomic analysis of abdominal CT scans can unveil, quantify, and interpret micro-level changes in the pre-diagnostic pancreas and can efficiently assist in the stratification of high risk individuals for PDAC.

Aerobic fitness and muscle density play a vital role in postoperative complications in colorectal cancer surgery.

Background and ObjectivesTo assess the association of preoperative aerobic fitness and body composition variables with a patient's resilience to the development and impact of postoperative complications after elective colorectal cancer (CRC) surgery.MethodsPreoperative aerobic fitness was assessed by steep ramp test performance. Preoperative body composition was assessed by muscle mass and density determined from preoperative computed tomography scan analysis at the L3‐level. Complication development and severity was graded according to Clavien‐Dindo. Complication impact was assessed by the time to recovery of physical functioning after complications. Multivariable logistic regression analyses adjusted for age, sex, comorbidities and tumour location was performed.ResultsOf 238 included patients, 96 (40.3%) developed postoperative complications. Better preoperative aerobic fitness decreased the likelihood to develop complications, independent of muscle mass (odds ratio [OR]: 0.55, 95% confidence interval [CI]: 0.35−0.85) or muscle density (OR: 0.57, 95% CI: 0.36−0.89). A prolonged time to recovery following complications was associated with lower preoperative muscle density (OR: 4.14, 95% CI: 1.28−13.41), independent of aerobic fitness.ConclusionsLower aerobic fitness increases the risk of complication development, while low muscle density seems associated with a prolonged recovery from complications. Aerobic fitness and muscle density could be valuable additives to preoperative risk assessment.

An ASP approach for arteries classification in CT scans

Abstract Automated segmentation of computed tomography (CT) scans is the first step in the pipeline for the interpretation and identification of potential pathologies in human organs. Several methods based on machine learning (ML) are currently available, even if their precision is still outperformed by medical doctors. In this field there are some intrinsic limitations to ML approaches, such as the following: cost and time to acquire high-quality annotated scans for training; and a remarkable high variability of organ morphology due to age, conditions, genetics and acquisition. This paper outlines a new methodology based on Answer Set Programming, which returns reliable, easy-to-program and explainable interpretations. In particular, we focus on the CT scan analysis and retrieval of tree-like structure, corresponding to main blood vessels (arteries) arrangement. The structure is compared to the knowledge base of vessels contained in anatomy textbooks. The mapping of vessel names is computed by an Answer Set Programming program. This preliminary step produces a robust input to a reasoner for the multi-organ labelling and localization problem.

Computed tomography-based radiomic model predicts radiological response following stereotactic body radiation therapy in early-stage non-small-cell lung cancer and pulmonary oligo-metastases

PurposeRadiomic models elaborate geometric and texture features of tumors extracted from imaging to develop predictors for clinical outcomes. Stereotactic body radiation therapy (SBRT) has been increasingly applied in the ablative treatment of thoracic tumors. This study aims to identify predictors of treatment responses in patients affected by early stage non-small cell lung cancer (NSCLC) or pulmonary oligo-metastases treated with SBRT and to develop an accurate machine learning model to predict radiological response to SBRT.Materials and MethodsComputed tomography (CT) images of 85 tumors (stage I–II NSCLC and pulmonary oligo-metastases) from 69 patients treated with SBRT were analyzed. Gross tumor volumes (GTV) were contoured on CT images. Patients that achieved complete response (CR) or partial response (PR) were defined as responders. One hundred ten radiomic features were extracted using PyRadiomics module based on the GTV. The association of features with response to SBRT was evaluated. A model using support vector machine (SVM) was then trained to predict response based solely on the extracted radiomics features. Receiver operating characteristic curves were constructed to evaluate model performance of the identified radiomic predictors.ResultsSixty-nine patients receiving thoracic SBRT from 2008 to 2018 were retrospectively enrolled. Skewness and root mean squared were identified as radiomic predictors of response to SBRT. The SVM machine learning model developed had an accuracy of 74.8%. The area under curves for CR, PR, and non-responder prediction were 0.86 (95% confidence interval [CI], 0.794–0.921), 0.946 (95% CI, 0.873–0.978), and 0.857 (95% CI, 0.789–0.915), respectively.ConclusionRadiomic analysis of pre-treatment CT scan is a promising tool that can predict tumor response to SBRT.

Four-Dimensional Computed Tomography Scan Analysis of Liver Tumor Motion Treated With Abdominal Compression During Stereotactic Treatment of Liver

To explore the motion and influencing factors of implanted gold markers in guiding liver stereotactic body radiation therapy using abdominal compression.Twenty patients with oligometastatic colorectal cancer or primary hepatocellular carcinoma from January 2016 to December 2019 were included. All patients were treated with stereotactic body radiation therapy (SBRT) under abdominal compression, with 1-3 gold markers implanted within 2cm of the lesion before positioning, meanwhile four-dimensional computed tomography (4DCT) scan used for treatment planning. The respiratory cycle was divided into 0%-90% respiratory phase image based on the respiratory signal, which were reconstructed by the system as well as CBCT validation images before radiation exposure daily. The liver volume was divided into 3 parts: within 2 cm of the main hepatic portal vein, 2-5 cm of the main hepatic portal vein, and 5 cm outside of the main hepatic portal vein, for evaluating the motion of different tumor locations.The average intrafractional motion amplitude (mean ± standard deviation) was 2.63 ± 2.81 mm in the cranial-caudal (CC), 1.35 ± 1.23 mm in the anterior-posterior (AP), and 0.76 ± 0.88 mm in the left-right (LR) direction, respectively. Meanwhile the average interfractional motion amplitude was 3.45 ± 3.06 mm, 2.64 ± 2.60 mm, and 2.23 ± 2.07 mm, respectively. Whether intra- or interfraction, the motion amplitude showed CC > AP > LR direction (P < 0.001). The motion varied at different tumor location, the further away from the main hepatic portal vein, the larger of the intrafractional motion. To cover the 95% population-based confidence interval, internal target volume was suggested to include the expansion of 3.9 mm, 5.2 mm and 7.9 mm in the LR, AP, and CC direction, while 4.3 mm, 4.4 mm, and 6.1 mm within 2 cm of the main hepatic portal vein, 3.5 mm, 7.3 mm, and 9.7 mm outside 5 cm of the main hepatic portal vein, respectively. The expansion varied significantly depending on tumor location, but motion in CC direction showed the largest no matter where the tumor was. Among the 3 parts of liver volume, while the further of tumor away from the main portal vein, the larger expansion in CC direction, and tumor in 5 cm outside of the main portal vein moved more than other inner parts in AP direction.Different tumor locations of liver require external expansion of internal target volume individually.Y. Zhao: None. Y. Tang: None. W. Liu: None. N. Li: None. Y. Song: None. S. Wang: None. Y. Liu: None. H. Fang: None. N. Lu: None. Y. Tang: None. S. Qi: None. Y. Yang: None. B. Chen: None. Y. LI: None. J. Jin: None.

Initial Management of Orbital Trauma: Is an Ophthalmologic Evaluation Necessary?

BACKGROUND: Orbital fractures may be associated with globe injuries, resulting in delayed ophthalmic complications and visual disturbance. The debate regarding the necessity of ophthalmologic evaluation in the initial management of orbital trauma continues. Therefore, there is a need to establish the rate of ocular injuries associated with orbital fractures. METHODS: A retrospective review of patients with orbital fractures who received ophthalmologic consultation and computed tomography scan analysis at a level 1 trauma center, from 2014 to 2020 was performed. The inclusion criteria were patients 18 years or older with confirmed computed tomography scan diagnosis of orbital fracture and ophthalmology consultation. Patient demographics, injuries, comorbidities, and surgical outcomes were collected. RESULTS: A total of 201 patients with 224 orbital fractures (11.4% bilateral) were included. The mean age at injury was 50.5 ± 25.2 years; 21.9% of patients had an associated neurologic injury at the time of ED evaluation. The most common mechanisms of injury were mechanical fall (41%), occupational injuries (26.9%), and motor vehicle accident (25%). The posterior segment of the eye was most affected (16.1%), followed by the anterior segment (13.4%) and ocular adnexa (13.4%). A significant ocular injury was present in 21.9% of orbital fractures. These included choroidal hemorrhage (6.1%), hyphema (5.4%), retinal hemorrhage (4.5%), retrobulbar hematoma (4%), globe rupture (3.6%), choroidal hemorrhage (1.4%), retinal detachment (1.3%), corneal laceration (0.9%), choroidal rupture (0.4%), macular hemorrhage (0.6%), and retinal tear (0.4%). The mechanism of injury was not associated with an increased risk for a serious ocular injury. The most common ophthalmologic findings on examination were diplopia (30.4%), reduced extraocular movement (9.8%), and periorbital laceration (8.9%). Of all patients, 53.1% presented with one orbital wall fracture, of which, the orbital floor was the most commonly involved (44.2%). Associated facial fractures were found in 68.8% of patients. computed tomography scans showed displaced fracture in 44.6% of orbits, comminution in 45.3% and herniation of orbital contents in 42.9%. On multiple variable analysis, motor vehicle accident (OR = 2.5 [1.4–4.7], P = 0.003) and injury to the posterior segment (OR = 2.6 [1.2–5.8], P = 0.045) were associated with the need of surgical treatment. However, injury to the anterior segment (OR = 3.4 [1.5–8.0], P = 0.028) and ocular adnexa (4.0 [1.6–10.1], P = 0.002) were associated with the need of medical treatment alone. CONCLUSIONS: Our retrospective series demonstrated a 22% incidence of ocular trauma in orbital fractures. There were no association between mechanism of injury and serious ocular trauma. This emphasizes that the management of orbital traumas requires a multidisciplinary approach, including the facial trauma team and ophthalmology.

Non-small-cell lung cancer classification via RNA-Seq and histology imaging probability fusion

BackgroundAdenocarcinoma and squamous cell carcinoma are the two most prevalent lung cancer types, and their distinction requires different screenings, such as the visual inspection of histology slides by an expert pathologist, the analysis of gene expression or computer tomography scans, among others. In recent years, there has been an increasing gathering of biological data for decision support systems in the diagnosis (e.g. histology imaging, next-generation sequencing technologies data, clinical information, etc.). Using all these sources to design integrative classification approaches may improve the final diagnosis of a patient, in the same way that doctors can use multiple types of screenings to reach a final decision on the diagnosis. In this work, we present a late fusion classification model using histology and RNA-Seq data for adenocarcinoma, squamous-cell carcinoma and healthy lung tissue.ResultsThe classification model improves results over using each source of information separately, being able to reduce the diagnosis error rate up to a 64% over the isolate histology classifier and a 24% over the isolate gene expression classifier, reaching a mean F1-Score of 95.19% and a mean AUC of 0.991.ConclusionsThese findings suggest that a classification model using a late fusion methodology can considerably help clinicians in the diagnosis between the aforementioned lung cancer cancer subtypes over using each source of information separately. This approach can also be applied to any cancer type or disease with heterogeneous sources of information.

Role of 3D Volumetric and Perfusion Imaging for Detecting Early Changes in Pancreatic Adenocarcinoma.

PurposeThere is a major shortage of reliable early detection methods for pancreatic cancer in high-risk groups. The focus of this preliminary study was to use Time Intensity-Density Curve (TIDC) and Marley Equation analyses, in conjunction with 3D volumetric and perfusion imaging to demonstrate their potential as imaging biomarkers to assist in the early detection of Pancreatic Ductal Adenocarcinoma (PDAC).Experimental DesignsA quantitative retrospective and prospective study was done by analyzing multi-phase Computed Tomography (CT) images of 28 patients undergoing treatment at different stages of pancreatic adenocarcinoma using advanced 3D imaging software to identify the perfusion and radio density of tumors.ResultsTIDC and the Marley Equation proved useful in quantifying tumor aggressiveness. Perfusion delays in the venous phase can be linked to Vascular Endothelial Growth Factor (VEGF)-related activity which represents the active part of the tumor. 3D volume analysis of the multiphase CT scan of the patient showed clear changes in arterial and venous perfusion indicating the aggressive state of the tumor.ConclusionTIDC and 3D volumetric analysis can play a significant role in defining the response of the tumor to treatment and identifying early-stage aggressiveness.

PD41-02 RADIOMIC-BASED “VIRTUAL BIOPSY” RELIABLY DIFFERENTIATES BENIGN FROM MALIGNANT RENAL MASSES

You have accessJournal of UrologySurgical Technology & Simulation: Instrumentation & Technology II (PD41)1 Sep 2021PD41-02 RADIOMIC-BASED “VIRTUAL BIOPSY” RELIABLY DIFFERENTIATES BENIGN FROM MALIGNANT RENAL MASSES Nima Nassiri, Marissa Maas, Giovanni Cacciamani, Bino Varghese, Darryl Hwang, Assad Oberai, Xiaomeng Lei, Mihir Desai, Monish Aron, Steven Cen, Vinay Duddalwar, and Inderbir Gill Nima NassiriNima Nassiri More articles by this author , Marissa MaasMarissa Maas More articles by this author , Giovanni CacciamaniGiovanni Cacciamani More articles by this author , Bino VargheseBino Varghese More articles by this author , Darryl HwangDarryl Hwang More articles by this author , Assad OberaiAssad Oberai More articles by this author , Xiaomeng LeiXiaomeng Lei More articles by this author , Mihir DesaiMihir Desai More articles by this author , Monish AronMonish Aron More articles by this author , Steven CenSteven Cen More articles by this author , Vinay DuddalwarVinay Duddalwar More articles by this author , and Inderbir GillInderbir Gill More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002051.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: A substantial proportion of patients undergo treatment for renal masses where active surveillance or observation may be more appropriate. We sought to determine whether a radiomic-based artificial intelligence (AI) platform that incorporates clinical variables can accurately differentiate benign renal masses from renal cell carcinoma (RCC). METHODS: We performed a cross-sectional analysis of a prospectively collected and maintained registry of patients with renal masses in accordance with the STROBE Statement for observational studies. All participants had a clinically-localized renal mass visualized with multiphase computed-tomography (CT) before robotic, laparoscopic, or open partial or radical nephrectomy. Radiomic analysis of pre-operative CT scans, specifically CT shape and texture analysis, was performed. 10-fold cross-validation was performed to overcome heterogeneities in radiomic analysis. Clinical and radiomic variables of interest (VOIs) were identified through decision tree analysis and incorporated into machine-learning Random Forest and REAL Adaboost predictive models. The primary outcome was the diagnostic capacity of the predictive model to discriminate benign renal masses from RCC. Secondary outcomes included a subanalysis for small renal masses (SRMs) and for patients who underwent percutaneous renal mass biopsy. RESULTS: 684 patients with a renal mass identified on CT imaging underwent radical or partial nephrectomy. Of the patients, 76% had RCC; 57% had an SRM, of which 73% were malignant. REAL Adaboost predictive modeling differentiated benign pathology from RCC with an AUC of 0.84 (95% C.I. 0.79-0.9) (Figure 1A). In SRMs, radiomic analysis yielded a discriminatory AUC of 0.77 (95%. C.I. 0.69-0.85) (Figure 1B). When negative and non-diagnostic biopsies were supplemented with the results of radiomic analysis, accuracy increased from 83.3% to 93.4%. CONCLUSIONS: Radiomic-based predictive modeling produces a “virtual biopsy” that may discriminate benign renal masses from RCC. Enhanced diagnostic predictability may preclude surgical intervention and increase the utility of active surveillance protocols. Source of Funding: no disclosures © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e680-e681 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Nima Nassiri More articles by this author Marissa Maas More articles by this author Giovanni Cacciamani More articles by this author Bino Varghese More articles by this author Darryl Hwang More articles by this author Assad Oberai More articles by this author Xiaomeng Lei More articles by this author Mihir Desai More articles by this author Monish Aron More articles by this author Steven Cen More articles by this author Vinay Duddalwar More articles by this author Inderbir Gill More articles by this author Expand All Advertisement Loading ...

Detection of Intraorbital Foreign Bodies Using Magnetic Resonance Imaging and Computed Tomography

ABSTRACT Purpose We analyze the detectability of intraorbital foreign bodies (OrbFBs) of various types and sizes using computed tomography (CT) and magnetic resonance imaging using a three-Tesla machine (MRI 3 T). Methods An ex vivo model of sheep eyes with preserved extraocular muscles and orbital fat tissue placed in the orbital cavity of the human skull was created for this study. Foreign bodies made of four different materials – plastic, bottle glass, stone and wood – each in three different sizes (large, intermediate and small) were inserted into the soft tissue of the orbit in the extraocular space. Each orbit was scanned by CT and MRI. Images were analyzed by a senior radiologist and underwent masked review by three oculoplastic surgeons. Results Analysis of MRI and CT scans identified distinguishing characteristics for each of the four materials. This information was further integrated into a clinical algorithm. CT allowed easier identification of most of the embedded materials compared to MRI. Smaller OrbFB size was associated with lower detectability. Review of CT yielded 94.4% agreement between oculoplastic specialists in detecting OrbFbs using CT scans and allowed detection of most OrbFBs. In contrast, the overall agreement with MRI was lower: 66.7% with T1 MPRAGE, 50% with T1TSE, 88.9% with T2 TSE and 72.2% with T2 TSE FS. Plastic was the most difficult material to detect in all size categories. Conclusions CT offers a clear advantage over MRI for detecting and localizing nonmetallic OrbFBs of all sizes, except for plastic. Plastic OrbFBs can be detected with CT depending on size but are more visible in MRI scans.

Cross-sectional analysis of follow-up chest MRI and chest CT scans in patients previously affected by COVID-19

PurposeThe aim of the study was to prospectively evaluate the agreement between chest magnetic resonance imaging (MRI) and computed tomography (CT) and to assess the diagnostic performance of chest MRI relative to that of CT during the follow-up of patients recovered from coronavirus disease 2019.Materials and methodsFifty-two patients underwent both follow-up chest CT and MRI scans, evaluated for ground-glass opacities (GGOs), consolidation, interlobular septal thickening, fibrosis, pleural indentation, vessel enlargement, bronchiolar ectasia, and changes compared to prior CT scans. DWI/ADC was evaluated for signal abnormalities suspicious for inflammation. Agreement between CT and MRI was assessed with Cohen’s k and weighted k. Measures of diagnostic accuracy of MRI were calculated.ResultsThe agreement between CT and MRI was almost perfect for consolidation (k = 1.00) and change from prior CT (k = 0.857); substantial for predominant pattern (k = 0.764) and interlobular septal thickening (k = 0.734); and poor for GGOs (k = 0.339), fibrosis (k = 0.224), pleural indentation (k = 0.231), and vessel enlargement (k = 0.339). Meanwhile, the sensitivity of MRI was high for GGOs (1.00), interlobular septal thickening (1.00), and consolidation (1.00) but poor for fibrotic changes (0.18), pleural indentation (0.23), and vessel enlargement (0.50) and the specificity was overall high. DWI was positive in 46.0% of cases.ConclusionsThe agreement between MRI and CT was overall good. MRI was very sensitive for GGOs, consolidation and interlobular septal thickening and overall specific for most findings. DWI could be a reputable imaging biomarker of inflammatory activity.

Diagnosis of COVID-19 using 3D CT scans and vaccination for COVID-19

PurposeFor the first time in a decade, a new form of pneumonia virus, coronavirus, COVID-19, appeared in Wuhan, China. To date, it has affected millions of people, killed thousands and resulted in thousands of deaths around the world. To stop the spread of this virus, isolate the infected people. Computed tomography (CT) imaging is very accurate in revealing the details of the lungs and allows oncologists to detect COVID. However, the analysis of CT scans, which can include hundreds of images, may cause delays in hospitals. The use of artificial intelligence (AI) in radiology could help to COVID-19-positive cancer in this manner is the main purpose of the work.Design/methodology/approachCT scans are a medical imaging procedure that gives a three-dimensional (3D) representation of the lungs for clinical purposes. The volumetric 3D data sets can be regarded as axial, coronal and transverse data sets. By using AI, we can diagnose the virus presence.FindingsThe paper discusses the use of an AI for COVID-19, and CT classification issue and vaccination details of COVID-19 have been detailed in this paper.Originality/valueOriginality of the work is, all the data can be collected genuinely and did research work doneown methodology.

Delivering computationally-intensive digital patient applications to the clinic: An exemplar solution to predict femoral bone strength from CT data

Background and objective:Whilst fragility hip fractures commonly affect elderly people, often causing permanent disability or death, they are rarely addressed in advance through preventive techniques. Quantification of bone strength can help to identify subjects at risk, thus reducing the incidence of fractures in the population. In recent years, researchers have shown that finite element models (FEMs) of the hip joint, derived from computed tomography (CT) images, can predict bone strength more accurately than other techniques currently used in the clinic. The specialised hardware and trained personnel required to perform such analyses, however, limits the widespread adoption of FEMs in clinical contexts. In this manuscript we present CT2S (Computed Tomography To Strength), a system developed in collaboration between The University of Sheffield and Sheffield Teaching Hospitals, designed to streamline access to this complex workflow for clinical end-users. Methods:The system relies on XNAT and makes use of custom apps based on open source software. Available through a website, it allows doctors in the healthcare environment to benefit from FE based bone strength estimation without being exposed to the technical aspects, which are concealed behind a user-friendly interface. Clinicians request the analysis of CT scans of a patient through the website. Using XNAT functionality, the anonymised images are automatically transferred to the University research facility, where an operator processes them and estimates the bone strength through FEM using a combination of open source and commercial software. Following the analysis, the doctor is provided with the results in a structured report. Results:The platform, currently available for research purposes, has been deployed and fully tested in Sheffield, UK. The entire analysis requires processing times ranging from 3.5 to 8 h, depending on the available computational power. Conclusions:The short processing time makes the system compatible with current clinical workflows. The use of open source software and the accurate description of the workflow given here facilitates the deployment in other centres.

The degree and appropriateness of computed tomography utilization for diagnosis of headaches in Ghana

IntroductionHeadache is a common and sometimes debilitating medical condition. Patients presenting with no neurologic anomaly, nontraumatic primary headache require careful evaluation before neuroimaging. National Guidelines standardizing exploitation of Computed Tomography (CT), the most utilized imaging modality in this clinical scenario, has not been established in Ghana, a developing country with limited healthcare resources. The country has not also adopted existing guidelines such as the National Institute for Health and Care Excellence (NICE) of the United Kingdom or the Appropriateness Criteria (AC) of the American College of Radiologists (ACR). The purpose of this review was to analyze the propensity of CT utilization for diagnosing headaches against the AC of the ACR and discuss some of the socio-economic inferences thereof. MethodsThis study retrospectively reviewed CT imaging records and clinical data of all patients referred for head CT scans between 1st January 2016 and 31st December 2018 at five major health facilities (four tertiary government hospitals and one private hospital) across Ghana. We isolated all head CT scans performed for the diagnosis of headache for analysis. We analyzed the type of presenting headache, CT findings, gender distribution, pattern of referrals, and head CT appropriateness against the AC of the ACR. ResultsA total of 44,218 patients were referred to the five facilities for head CT secondary to diverse indications for the period. All non-trauma cases were 41.7%; trauma cases were 31.6%, the majority (72.3%) were from road traffic accidents. The majority (64.9%) of trauma casualties were males. A total of 11,806 (26.7%) patients were referred for a head CT scan for the diagnosis of headache. The private hospital recorded the highest referrals for head CT scan for diagnosis of headache. The gender distribution of all headache patients was 57.6% females, and 42.4% were males. The age distribution showed 19.3% were children, 71.2% were adults, and the aged constituted 9.4%. The results showed 2.8% significant cranial CT findings of all reviewed headache patients. Pathological findings among the cohort of children were 0.6%.The sources and pattern of referrals showed 57.3% were from the Outpatient Department, 26.6% from the Emergency Department, in-patients’ referrals were 9.4%, and specialist consultation was 7.1%. Analysis of CT scans performed against the AC of the ACR, showed 69.0% of headache patients were likely scanned inappropriately. ConclusionsThere is a need to implement international best practice guidelines or develop a national neuroimaging policy to protect patients. Unjustified CT utilization for diagnosis of headaches exposes patients to unnecessary ionizing radiation that can instigate cancer and unnecessary expenditure. Head CT scan for some headache patients with normal neurologic findings may be unnecessary in an emerging country like Ghana. Clinicians must, therefore, be discerning in CT scan requests for the diagnosis of headache.

The Feasibility Study of C1 Posterior Arch Crossing Screw Fixation in Adult Thai Population: A Computed Tomographic Morphometric Analysis Study

Objective: Atlantoaxial instability can be caused by various etiologies and surgical fixation is often required. Various methods have been described for atlantoaxial fixation. Screw fixation is associated with an increased risk of vertebral artery injury especially in patients with an anomalous vertebral artery location or abnormal bony anomalies. A new C1 posterior arch crossing screw fixation technique was proposed to reduce the risk of vertebral artery injury. The present study aimed to assess morphometric CT analysis of atlas for C1 posterior arch crossing screw fixation in Thai people. Materials and Methods: The present research was an observational study that reviewed 150 computed tomography (CT) scans of the patients who had neck trauma or any other complaint requiring craniocervical investigations. Atlantoaxial articulation deformities due to trauma, infections, neoplasm, congenital anomaly, inflammatory disease, incomplete CT scan analysis, and history of surgical intervention of the cervical spine were excluded. All the images were measured for the height of the posterior tubercle, the width of the posterior arch was measured bilaterally in three parts on the axial plane, part 1: medial of the VA groove, where the arch transforms into the VA groove, part 2: the middle part between the posterior tubercle and medial of the VA, and part 3: posterior tubercle, length of the screw, and the screw projection angle was calculated. Results: Out of the 139 CT scans analyzed, the mean measurement of posterior arch height was 7.45±1.03 mm, wherein 73.3% exceed 7 mm. The mean width of the left posterior arch in part 1, 2, and 3 was 4.50±0.70 mm, 4.90±0.70 mm, and 5.70±0.80 mm, respectively, and the width of the right posterior arch in part 1, 2, and 3 was 4.50±0.70 mm, 4.80±0.70 mm, and 5.60±0.80 mm, respectively. The mean crossing screw length of the Left and Right was 17.02±3.04 mm and 17.37±2.75 mm, respectively. The mean angle of screw of the Left and Right was 24.62±3.38 degrees and 24.78±3.57 degrees, respectively. There were no significant differences in these variables between gender or sides (p&gt;0.05) except the mean angle of the screw between gender (p&lt;0.05). Conclusion: C1 posterior arch screw fixation is feasible in the adult Thai population. Preoperative thin-cut CT is essential for planning successful posterior arch crossing screws placement. Keywords: C1 posterior arch, Computed tomography, Crossing screw fixation

Three-Dimensional Computed Tomography Scan Analysis of Secondary Labial Deformities in Patients With Unilateral Cleft Lip/Cleft Palate After Revisional Surgery.

Surgical reconstruction of secondary labial deformities associated with isolated unilateral cleft lip (UCL) and/or UCL and palate (UCLP) is challenging. There have been few studies in the literature looking at labial soft tissues quantitatively to assess surgical results. To apply a novel computer-aided, 3-dimensional reconstruction technique based on CT scan images to conduct quantitative preoperative and postoperative assessments in patients with UCL/UCLP undergoing surgical revision of secondary labial deformities. Preoperative and postoperative spiral computed tomographic (CT) scans of the face were performed in 21 randomly selected UCL or UCLP patients, who underwent secondary lip revision surgery. The data was then imported to the SimPlant 11.04 software system. Fixed point-to-point, linear distance, and angles were measured, statistically analyzed and used to assess the effect of the surgery. Preoperative measurements showed that the thickness of the upper vermilion at the apex of the Cupid's bow on the affected side was greater than that on the unaffected side. The distance from the apex of the Cupid's bow to the ipsilateral subnasal point of the affected side was smaller than that of the unaffected side (P < 0.05). After surgery, the subjects were rescanned at an average of 9 months, and the curative effects were evaluated. The statistically significant preoperative differences between the affected and unaffected sides were not found postoperatively indicating surgical success. This study demonstrates the utility of a novel method to measure and assess results in the surgical revision of UCL/UCLP patients with secondary lip deformities. This knowledge can aid the surgeon in selection of treatment techniques.

Paravalvular leak prediction after transcatheter aortic valve replacement with self-expandable prosthesis based on quantitative aortic calcification analysis.

Paravalvular leak (PVL) is one of the most common complications of transcatheter aortic valve replacement (TAVR) and affects short- and long-term outcomes. The aim of this study was to identify the computed tomography (CT) imaging biomarkers that allow PVL after TAVR to be predicted. Patients were included who had severe aortic valve stenosis, had undergone TAVR with a self-expanding valve, and had undergone a pre-procedural CT scan. Data on baseline characteristics, procedural and long-term outcomes were collected retrospectively. We used MATLAB software with a self-developed algorithm for CT scan analysis and found parameters that quantified aortic valve calcifications (AVC) in detail. Fifty patients were included. The identified CT-derived parameters included AVC size, volume, thickness and density, as well as calcium radial distribution. The volume of the largest calcium block, calcium perimeter and calcium size (assessed by Feret's diameter) showed a strong association with PVL occurrence after TAVR (P=0.012, P=0.001 and P=0.045, respectively). The prognostic model showed that a 10 mm2 increase in the local AVC amount in each valve section was associated with a 9.8% (95% CI: 2-18%; P=0.019) increase in the risk of PVL occurrence in the corresponding area after TAVR. ROC analysis revealed that the cut-off point of the AVC area was 96.5 mm2 in the polar coordinate system presentation. Kaplan-Meier curves showed worse PVL-free survival in patients with more than 96.5 mm2 of calcium area (P=0.013; log-rank). Quantitative AVC assessment for PVL prediction may play an important role in screening before TAVR. In future, the use of quantitative AVC assessment as an imaging biomarker in TAVR candidates and the creation and extension of an online database containing quantitative AVC parameters may help to identify high PVL risk patients.

Tomographic Analysis of Positioning of Reverse Baseplates Positioning.

ObjectiveTo verify whether reverse baseplate positioning without the support of intraoperative three-dimensional technology is within the acceptable parameters in the literature and whether glenoid bone deformity (GBD) compromises this positioning. MethodsSixty-nine reverse shoulder arthroplasties were evaluated with volumetric computed tomography (CT). Two radiologists performed blinded CT scan analysis and evaluated baseplate position within 2mm of the inferior glenoid; the inclination and version of the baseplate in relation to the Friedman line; and upper and lower screw and baseplate metallic peg end point positionings. The patients were divided according to the presence of GBD for statistical analyses.ResultsThe two radiologists concurred reasonably in their interpretations of the following analyzed parameters: baseplate position within 2mm of the inferior glenoid rim (97.1% and 95.7%), baseplate inclination (82.6% and 81.2%), baseplate version (69.6% and 56.5%), the upper screw reaching the base of the coracoid process (71% and 79.7%), the inferior screw remaining inside the scapula (88.4% and 84.1%), and the metallic peg of the baseplate considered intraosseous (88.4% and 72.5%). ConclusionReverse baseplate positioning without intraoperative three-dimensional technology is within the acceptable parameters of the literature, except for baseplate version and upper screw position. GBD did not interfere with baseplate positioning in reverse shoulder arthroplasty.

Pre and Postoperative Muscle Wastage and Sarcopenia Using CT Scans in Patients Undergoing Pelvic Exenteration Surgery

Background: Sarcopenia is associated with poor postoperative outcomes in oncology patients. Computed tomography (CT) scans can be used to identify muscle wasting and sarcopenia. This study aimed to investigate if pelvic exenteration surgery leads to muscle wastage and thus, induction or exacerbation of sarcopenia. Methods: This is a retrospective review involving the analysis of CT scans before and after pelvic exenteration surgery to determine skeletal muscle index and diagnose sarcopenia. Other clinical and nutritional factors were collected. Results: A total of 34 patients met the inclusion criteria. Postoperative skeletal muscle index was significantly lower compared to preoperative skeletal muscle index (p=0.008). The incidence of sarcopenia was 62% preoperatively and rose to 74% postoperatively (p=0.073). Postoperative sarcopenia was not significantly associated with complications or mortality. Conclusion: The skeletal muscle index significantly decreased postoperatively, indicating that pelvic exenteration surgery leads to muscle wastage. The use of CT scans to recognise sarcopenia would allow focusing of resources for those at risk.

Outcomes of urgent aortic wrapping for acute type A aortic dissection

ObjectiveStandard surgical repair of acute type A aortic dissection is associated with high mortality rates, especially in high-risk patients. In an attempt to improve survival in frail patients, we evaluated the outcomes after ascending aorta wrapping in a high-risk patient cohort. MethodsThis single-center retrospective cohort study included all consecutive patients treated using ascending aorta wrapping for an acute type A aortic dissection from 2008 to 2019. The primary end points included 30-day mortality, survival during follow-up, and dissection-related mortality. Secondary end points included assessment of aortic remodeling after ascending aorta wrapping. Patients with an aortic anatomy suitable for adjunctive endografting of the ascending aorta were also identified. ResultsThirty-five consecutive patients who underwent ascending aorta wrapping were included. Their median age was 77 years (range, 46-96 years). The 30-day all-cause mortality rate was 9%. Major complications occurred in 7 patients (21%), including early reinterventions in 11 (31%). Median follow-up was 36 months (range, 2.4-106.6; interquartile range, 72). The actuarial survival at 36 months was 82%. The dissection-related mortality was 11.4%. The median aortic growth of the nonwrapped descending thoracic aorta was 3.4 mm. Computed tomography scan analysis depicted that 88% of survivors were theoretical candidates for an additional endovascular procedure to exclude the primary entry tear. ConclusionsAortic wrapping is associated with favorable early outcomes and a low rate of aortic events during follow-up. This therapeutic option should be considered for patients considered too fragile for standard surgical repair.