Preoperative CT Images Research Articles

Persistent epiphora after endonasal ENT surgery: CT dacryography findings

To analyze postoperative CT dacryography features in patients with persistent epiphora after endonasal surgery. We conducted a retrospective study of 76 patients with a history of persistent epiphora after endonasal ENT surgery who underwent CT dacryography between January 2014 and February 2020. Volume acquisition of sub-millimeter sections allowed 2D and 3D reconstructions with virtual endoscopy of the nasosinusal cavities and the lacrimal canal. The postsurgical appearance of the nasosinusal cavities revealed a middle meatal antrostomy in 37% of cases, less frequently an ethmoidectomy or an inferior meatal antrostomy, sometimes completed by a middle or inferior turbinectomy. In thirty-five patients (46%), the lacrimal canal was distant from the endonasal ENT procedure. Epiphora was related to mucosal hypertrophy, constricting all or part of the lacrimal canal. Thirty-three patients (43%) showed changes in the lacrimal canal at the surgical site. In the inferior meatus, the nasolacrimal orifice was sometimes involved in the inferior turbinectomy or meatotomy, but most of the time, in the middle meatus, resection of the uncinate process prior to ethmoidectomy or middle meatotomy was associated with a lesion of the contiguous lacrimal canal. As a rare cause of persistent tearing, involvement of the nasolacrimal duct at the edge of the endonasal ENT surgery highlights the importance of intraoperative localization of the nasolacrimal duct before resection of the uncinate process or the inferior turbinate, ideally predicted by preoperative CT imaging.

Potential serum protein biomarkers of cancer cachexia, muscle atrophy, and survival in pancreatic ductal adenocarcinoma.

545 Background: Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of death in the United States. Treatment is difficult and often complicated by the presence of cachexia, a systemic wasting condition affecting most PDAC patients at diagnosis. Skeletal muscle atrophy is a hallmark of cachexia and predicts outcomes after surgery and chemotherapy. In this study, we sought to identify possible serum biomarkers of cachexia, which correlates with changes to lean body mass and survival, using an aptamer-based platform in patients with PDAC. We hypothesize that unique proteins associate with cachexia and survival measures. Methods: Using SomaScan we measured the serum levels of 4,006 proteins in 21 patients with PDAC undergoing curative surgery. Clinical data and anthropometric measurements derived from pre-operative CT imaging were compared to protein levels with Spearman correlational analyses and logistic regression. We then queried DAVID Bioinformatics database to identify enriched functional protein categories. Results: Mean age was 66.9 ± 8.91 years, and mean body-weight loss in the six months preceding diagnosis was 12.6 ± 8.80%. Using consensus guidelines considering percent weight loss and skeletal muscle mass and radiation attenuation, 10 subjects (46.7%) were defined as “cachectic.” We found 241 proteins significantly correlated to Cancer Weight Loss Grade (a composite measure of percent body weight loss and body mass index). High IDUA, CTLA4 and USE1, in particular, predicted the worst weight loss grade with 75% sensitivity and 92% specificity (AUC = 0.8894, odds ratio: 36, p = 0.0068). Four additional proteins significantly correlated with skeletal muscle index (CK-MM, CK-MB, PCOC2 and ADH4) while 13 proteins significantly correlated with muscle radiation attenuation. Lastly, we identified 18 proteins that significantly correlated with survival quartile. Of these, we found that elevated HS6ST2 and DEPP significantly predicted early recurrence and death compared to those with lower levels (medial survival: 177 days v. 850 days, p = 0.0049). Of the correlative proteins, enriched gene ontology terms included signal peptide (28.2), cytokine (6.86), negative regulation of endopeptidase activity (3.39), and immunoglobulin domain (3.24). Conclusions: Cancer cachexia in PDAC and various gastrointestinal malignancies remains a key clinical issue. While there are no definitive biomarkers currently in use to diagnose and manage cachexia preemptively, we present several potential candidates in a small cohort of patients. Ultimately, such assays may better elucidate common cachexia-inducing pathways, a shared spectrum of biomarkers and allow for the development of more specific therapies targeting cachexia.

비소세포폐암 환자의 재발 예측을 위한 흉부 CT 영상 패치 기반 CNN 분류 및 시각화

Non-small cell lung cancer (NSCLC) accounts for a high proportion of 85% among all lung cancer and has a significantly higher mortality rate (22.7%) compared to other cancers. Therefore, it is very important to predict the prognosis after surgery in patients with non-small cell lung cancer. In this study, the types of preoperative chest CT image patches for non-small cell lung cancer patients with tumor as a region of interest are diversified into five types according to tumor-related information, and performance of single classifier model, ensemble classifier model with soft-voting method, and ensemble classifier model using 3 input channels for combination of three different patches using pre-trained ResNet and EfficientNet CNN networks are analyzed through misclassification cases and Grad-CAM visualization. As a result of the experiment, the ResNet152 single model and the EfficientNet-b7 single model trained on the peritumoral patch showed accuracy of 87.93% and 81.03%, respectively. In addition, ResNet152 ensemble model using the image, peritumoral, and shape-focused intratumoral patches which were placed in each input channels showed stable performance with an accuracy of 87.93%. Also, EfficientNet-b7 ensemble classifier model with soft-voting method using the image and peritumoral patches showed accuracy of 84.48%.

Augmented Features Synergize Radiomics in Post-Operative Survival Prediction and Adjuvant Therapy Recommendation for Non-Small Cell Lung Cancer.

BackgroundOwing to the cytotoxic effect, it is challenging for clinicians to decide whether post-operative adjuvant therapy is appropriate for a non-small cell lung cancer (NSCLC) patient. Radiomics has proven its promising ability in predicting survival but research on its actionable model, particularly for supporting the decision of adjuvant therapy, is limited.MethodsPre-operative contrast-enhanced CT images of 123 NSCLC cases were collected, including 76, 13, 16, and 18 cases from R01 and AMC cohorts of The Cancer Imaging Archive (TCIA), Jiangxi Cancer Hospital and Guangdong Provincial People’s Hospital respectively. From each tumor region, 851 radiomic features were extracted and two augmented features were derived therewith to estimate the likelihood of adjuvant therapy. Both Cox regression and machine learning models with the selected main and interaction effects of 853 features were trained using 76 cases from R01 cohort, and their test performances on survival prediction were compared using 47 cases from the AMC cohort and two hospitals. For those cases where adjuvant therapy was unnecessary, recommendations on adjuvant therapy were made again by the outperforming model and compared with those by IBM Watson for Oncology (WFO).ResultsThe Cox model outperformed the machine learning model in predicting survival on the test set (C-Index: 0.765 vs. 0.675). The Cox model consists of 5 predictors, interestingly 4 of which are interactions with augmented features facilitating the modulation of adjuvant therapy option. While WFO recommended no adjuvant therapy for only 13.6% of cases that received unnecessary adjuvant therapy, the same recommendations by the identified Cox model were extended to 54.5% of cases (McNemar’s test p = 0.0003).ConclusionsA Cox model with radiomic and augmented features could predict survival accurately and support the decision of adjuvant therapy for bettering the benefit of NSCLC patients.

CT-based radiomics model for preoperative prediction of hepatic encephalopathy after transjugular intrahepatic portosystemic shunt.

To develop and evaluate a machine learning-based CT radiomics model for the prediction of hepatic encephalopathy (HE) after transjugular intrahepatic portosystemic shunt (TIPS). A total of 106 patients who underwent TIPS placement were consecutively enrolled in this retrospective study. Regions of interest (ROIs) were drawn on unenhanced, arterial phase, and portal venous phase CT images, and radiomics features were extracted, respectively. A radiomics model was established to predict the occurrence of HE after TIPS by using random forest algorithm and 10-fold cross-validation. Receiver operating characteristic (ROC) curves were performed to validate the capability of the radiomics model and clinical model on the training, test and original data sets, respectively. The radiomics model showed favorable discriminatory ability in the training cohort with an area under the curve (AUC) of 0.899 (95% CI, 0.848 to 0.951), while in the test cohort, it was confirmed with an AUC of 0.887 (95% CI, 0.760 to 1.00). After applying this model to original data set, it had an AUC of 0.955 (95% CI, 0.896 to 1.00). A clinical model was also built with an AUC of 0.649 (95% CI, 0.530 to 0.767) in the original data set, and a Delong test demonstrated its relative lower efficiency when compared with the radiomics model (p < 0.05). Machine learning-based CT radiomics model performed better than traditional clinical parameter-based models in the prediction of post-TIPS HE. Radiomics model for the prediction of post-TIPS HE was built based on feature extraction from routine acquired pre-operative CT images and feature selection by random forest algorithm, which showed satisfied performance and proved the advantages of machine learning in this field.

Development and validation of a CT-based nomogram to predict spread through air space (STAS) in peripheral stage IA lung adenocarcinoma.

To develop and validate a simple-to-use nomogram based on preoperative CT to predict spread through air space (STAS) status of stage IA lung adenocarcinoma (ADC). In this retrospective study, 434 patients with pathological proven periphery stage IA lung adenocarcinoma were included, which consisted of 349 patients from center I for training group and 85 patients from Center II for test group. STAS was identified in 53 patients (40 patient in the training group and 13 patients in the test group). On the basis of preoperative CT images, 19 morphological characteristics were analyzed. Univariable analysis was used to explore the association between clinical and CT characteristics and STAS status in the training group (P < 0.002). Independent risk factors for STAS were identified using multivariable logistic regression analysis and then used to build a nomogram for preoperative predicting STAS status. Type of nodules, diameter of solid component, lobulation and percentage of the solid component (PSC) were associated with STAS status of peripheral stage IA lung ADCs statistical significantly. Multivariate logistics regression analysis revealed that PSC and lobulation were independent risk factors for STAS. The nomogram based on these factors achieved good predictive performance for STAS with a C-index of 0.803 in the training group and a well-fitted calibration curve. Using a cut-off value which was obtained from Youden index of the receiver operating characteristic (ROC) curve, a diagnosis accuracy of 70.6% was obtained in the test group with sensitivity, specificity, positive prediction value (PPV) and negative prediction value (NPV) of 92.3%, 66.7%, 33.3% and 98.0%, respectively. The nomogram based on preoperative CT images could achieve good predictive performance for STAS status of lung adenocarcinomas. This simple-to-used model can facilitate surgeons for a rational operation pattern choice at bedside.

Computed Tomography-Based Radiomic Analysis for Preoperatively Predicting the Macrovesicular Steatosis Grade in Cadaveric Donor Liver Transplantation

This study is aimed at determining the ability of computed tomography- (CT-) based radiomic analysis to distinguish between grade 0/1 and grade 2/3 macrovesicular steatosis (MaS) in cadaveric donor liver transplantation cases. Preoperative noncontrast-enhanced CT images of 150 patients with biopsy-confirmed MaS were analyzed retrospectively; these patients were classified into the low-grade MaS (n = 100, grade 0 or 1) and high-grade MaS (n = 50, grade 2 or 3) groups. Three-dimensional spherical regions of interest of 40 pixel (2.5 cm) in diameter were placed in the right anterior and left lateral segments of the liver. Thereafter, 300 regions of interest (ROIs) were segmented and randomly assigned to the training and testing groups at a ratio of 7 : 3. A total of 402 radiomic features were extracted from each ROI. For MaS classification, a radiomic model was established using multivariate logistic regression analysis. Clinical data, including age, sex, and liver function, were collected to establish the clinical model at the patient level. The performances of the radiomic and clinical models, i.e., the diagnostic discrimination, calibration, and clinical utilities, were evaluated. The radiomic model, with seven selected features, depicted a good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.907 (95% confidence interval (CI): 0.869–0.940) in the training cohort and 0.906 (95% CI: 0.843–0.959) in the testing cohort. The calibration curve revealed good agreement between the predicted and observed probabilities in the training and testing cohorts (both P > 0.05 in the H-L test). Decision curve analysis revealed that the radiomic model was more beneficial than the treat-all or treat-none schemes for predicting the MaS grade. Alanine transaminase and gamma-glutamyl transferase were used for building the clinical model, and the AUC was 0.784 in the total cohort. The CT-based radiomic model outperforming the conventional clinical model could provide an important reference for MaS grading in cadaveric liver donors.

An investigation of the efficiency of pedicle screw simulator software in thoracic

Aim: Fennell et al. describe a simple, effective freehand technique for thoracic pedicle screw insertion. In this study, we aimed to compare the patients undergoing upper thoracic pedicle screw insertion with the Fennell technique simulated on Pedicle Screw Simulator (PSS) and those recruited to the same procedure utilizing C-arm fluoroscopy.&#x0D; Material and Method: First, we uploaded pre-operative CT images of 12 patients to the PSS module, which was used in our study to calculate the screw angle and visualize the pedicle screw entry point and trajectories. Then, we created three-dimensional vertebral models of the patients to simulate screw placement using visualization tool kit (VTK), open-source software for 3D computer graphics and visualization, available free of charge as part of 3D Slicer. Next, we placed pedicle screws through pre-determined anatomic regions. C-arm fluoroscopy-guided pedicle screws were placed in the patients in the control group. The amount of bleeding, operation times and correct screw placement data were recorded in both groups.&#x0D; Results: 24 patients were included in the study. The mean age of the patients was 32.3±4.1 years. We applied 80 pedicle screws to Group 1 and 72 to Group 2. According to the malposition classification by Rao et al. on postoperative CTs, 68 patients in Group 1 were classified as Grade 0, 8 as Grade 1, 4 as Grade 2. Yet, there were no statistical differences between the groups by Rao et al.’s classification (p&gt;0.05). While the mean operation time of Group 1 was 138±34 minutes, it was 162±44 minutes in Group 2. The groups significantly differed by operation time (p

Clinical application of virtual imaging guided Robot-assisted partial nephrectomy.

Objectives : To evaluate whether virtual partial nephrectomy images could help surgeons identify vascular and collecting system around tumors during actual surgery. Materials & methods : We retrospectively analyzed 36 patients who underwent robot-assisted partial nephrectomy (RAPN) between 2016 and 2017. Virtual partial nephrectomy images were created from preoperative CT images using computer software, and then analyzed. For analysis, blood vessels and collecting system portions within a 5-mm-thick safety margin around the tumor were examined. During analysis, we predicted whether targeted vasculature around the tumor would require clipping or suturing during surgery, and also whether the collecting system would require opening during resection. Surgical outcomes for virtual partial nephrectomy analyses and actual RAPNs were compared and analyzed for sensitivity and specificity. Results : In 36 cases, 119 arteries and 100 veins were targeted on virtual partial nephrectomy images. Arterial suturing or clipping for hemostasis showed a sensitivity and specificity of 83.3% and 84.5%, respectively. For veins, the sensitivity and specificity were 39.1% and 92.2%, respectively. Collecting system opening prediction sensitivity was 85.7%, and specificity was 65.2%. Conclusion : Virtual partial nephrectomy imaging is useful for RAPN planning, particularly regarding arteries and the collecting system. It is hoped that techniques for visualizing veins will improve. J. Med. Invest. 69 : 237-243, August, 2022.

特異値分解による術中X線投影動画から時間濃度曲線の推定手法の開発

It is a challenge in clinical practice to estimate Time Enhancement Curves (TEC) of a Region Of Interest ( ROI ) in real time from intraoperative X-ray projection movies. In the past, TEC was estimated by obtaining the Standard Linear Attenuation Coefficient Distribution (SLACD) from a preoperative contrast-enhanced CT and combining it with an intraoperative X-ray projection movie. However, in actual clinical practice, the SLACD is often uncertain due to the unavailability of preoperative contrast-enhanced CT images and the patient's respiratory motion. We developed a method for estimating TECs at a newly defined Node Of Interest (NOIs) by applying Singular Value Decomposition ( SVD ) and prior information to intraoperative X-ray projection movies only. To validate the effectiveness of this method, twin numerical experiments were conducted using a simulated blood vessel model, and the estimation results were compared. The estimation results show that the method is able to accurately estimate the rise time of TECs and the frame of maximum concentration.

Incidence, Risk Factors and Outcomes of Jejunal Varix of the Afferent Loop after Pancreatoduodenectomy

Introduction: Jejunal varices is a worrisome late complication after PD due to recurrent and intractable bleeding. The objective of this study was to determine the incidence, risk factors, and outcomes of jejunal varices after pancreatoduodenectomy (PD). Methods: A total of 709 patients who underwent PD from 2007 to 2017 were enrolled in the study. Preoperative and postoperative follow-up CT images were reviewed to evaluate the development of portal vein (PV) stenosis(³50%) and jejunal varices, which was defined as engorged dilated veins >3mm. Results: Jejunal varices developed in 83 (11.7%) patients after a median duration of 12 (5-21) months after PD. Among those patients, 18 (21.7%) experienced variceal bleeding. PV stenosis (P<0.001; OR 33.234, 95% CI 15.568-66.666) and PV/SMV resection (P=0.028; OR 2.261, 95% CI 1.090-4.687) were identified as independent predicting factors for jejunal varices. None of 9 patients who underwent stent placement for PV stenosis before the formation of jejunal varices experienced variceal bleeding, whereas 18 (27.3%) of 135 patients who did not receive PV stent placement experienced at least one episode of variceal bleeding. Among 20 patients with PV stent placement, variceal bleeding occurred in 4 of 9 patients with stent thrombosis, but not in 11 patients without stent thrombosis. Conclusions: The results revealed that the incidence of jejunal varices was not low after PD and PV stenosis was a strong risk factor for jejunal varices. Early placement of PV stent and maintenance of stent patency could reduce the risk of variceal bleeding in patients with PV stenosis.

Diagnostic Accuracy of CT for Evaluating Circumferential Resection Margin Status in Resectable or Borderline Resectable Pancreatic Head Cancer: A Prospective Study Using Axially Sliced Surgical Pathologic Correlation

ObjectiveCT plays a central role in determining the resectability of pancreatic cancer, which directs the use of neoadjuvant therapy. This study aimed to assess the diagnostic accuracy of CT in predicting circumferential resection margin (CRM) involvement in patients with resectable or borderline resectable pancreatic head cancer.Materials and MethodsSeventy-seven patients who were scheduled for upfront surgery for resectable or borderline resectable pancreatic head cancer were prospectively enrolled, and 75 patients (38 male and 37 female; mean age ± standard deviation, 68 ± 11 years) were finally analyzed. The CRM status was evaluated separately for the superior mesenteric artery (SMA) and posterior and superior mesenteric vein/portal vein (SMV/PV) margins. Three independent radiologists reviewed the preoperative CT images and evaluated the resection margin status. The reference standard for CRM status was pathologic examination of pancreaticoduodenectomy specimens in an axial plane perpendicular to the axis of the second portion of the duodenum. The diagnostic accuracy of CT was assessed for overall CRM involvement, defined as involvement of the SMA or posterior margins (per-patient analysis), and involvement of each of the three resection margins (per-margin analysis). The data were pooled using a crossed random effects model.ResultsForty patients had pathologically confirmed overall CRM involvement in pancreatic cancer, while CRM involvement was not seen in 35 patients. For overall CRM involvement, the pooled sensitivity and specificity were 15% (95% confidence interval: 7%–49%) and 99% (96%–100%), respectively. For each of the resection margins, the pooled sensitivity and specificity were 14% (9%–54%) and 99% (38%–100%) for the SMA margin, 12% (8%–46%) and 99% (97%–100%) for the posterior margin; and 37% (29%–53%) and 96% (31%–100%) for the SMV/PV margin, respectively.ConclusionCT showed very high specificity but low sensitivity in predicting pathological CRM involvement in pancreatic cancer.

Deep Learning to Predict EGFR Mutation and PD-L1 Expression Status in Non-Small-Cell Lung Cancer on Computed Tomography Images.

Objective The detection of epidermal growth factor receptor (EGFR) mutation and programmed death ligand-1 (PD-L1) expression status is crucial to determine the treatment strategies for patients with non-small-cell lung cancer (NSCLC). Recently, the rapid development of radiomics including but not limited to deep learning techniques has indicated the potential role of medical images in the diagnosis and treatment of diseases. Methods Eligible patients diagnosed/treated at the West China Hospital of Sichuan University from January 2013 to April 2019 were identified retrospectively. The preoperative CT images were obtained, as well as the gene status regarding EGFR mutation and PD-L1 expression. Tumor region of interest (ROI) was delineated manually by experienced respiratory specialists. We used 3D convolutional neural network (CNN) with ROI information as input to construct a classification model and established a prognostic model combining deep learning features and clinical features to stratify survival risk of lung cancer patients. Results The whole cohort (N = 1262) was divided into a training set (N = 882, 70%), validation set (N = 125, 10%), and test set (N = 255, 20%). We used a 3D convolutional neural network (CNN) to construct a prediction model, with AUCs of 0.96 (95% CI: 0.94–0.98), 0.80 (95% CI: 0.72–0.88), and 0.73 (95% CI: 0.63–0.83) in the training, validation, and test cohorts, respectively. The combined prognostic model showed a good performance on survival prediction in NSCLC patients (C-index: 0.71). Conclusion In this study, a noninvasive and effective model was proposed to predict EGFR mutation and PD-L1 expression status as a clinical decision support tool. Additionally, the combination of deep learning features with clinical features demonstrated great stratification capabilities in the prognostic model. Our team would continue to explore the application of imaging markers for treatment selection of lung cancer patients.

Can Shunt Response in Patients with Idiopathic Normal Pressure Hydrocephalus Be Predicted from Preoperative Brain Imaging? A Retrospective Study of the Diagnostic Use of the Normal Pressure Hydrocephalus Radscale in 119 Patients.

The Normal Pressure Hydrocephalus Radscale is a combined scoring of 7 different structural imaging markers on preoperative brain CT or MR imaging in patients with idiopathic normal pressure hydrocephalus: callosal angle, Evans Index, Sylvian fissure dilation, apical sulcal narrowing, mean temporal horn diameter, periventricular WM lesions, and focal sulcal dilation. The purpose of this retrospective study was to assess the performance of the Normal Pressure Hydrocephalus Radscale in distinguishing idiopathic normal pressure hydrocephalus shunt responders from nonresponders. The preoperative MR imaging and CT scans of 119 patients with idiopathic normal pressure hydrocephalus were scored using the Normal Pressure Hydrocephalus Radscale. A summary shunt-response score assessed within 6 months from ventriculoperitoneal shunt surgery, combining the effect on cognition, gait, and urinary incontinence, was used as a reference. The difference between the mean Normal Pressure Hydrocephalus Radscale for responders and nonresponders was tested using the Student t test. The area under the curve was calculated for the Normal Pressure Hydrocephalus Radscale to assess shunt response. To ascertain reproducibility, we assessed the interobserver agreement between the 2 independent observers as intraclass correlation coefficients for the Normal Pressure Hydrocephalus Radscale for 74 MR imaging scans and 19 CT scans. Ninety-four (79%) of 119 patients were shunt responders. The mean Normal Pressure Hydrocephalus Radscale score for shunt responders was 8.35 (SD, 1.53), and for nonresponders, 7.48 (SD, 1.53) (P = .02). The area under the curve for the Normal Pressure Hydrocephalus Radscale was 0.66 (range, 0.54-0.78). The intraclass correlation coefficient for the Normal Pressure Hydrocephalus Radscale was 0.86 for MR imaging and 0.82 for CT. The Normal Pressure Hydrocephalus Radscale showed moderate discrimination for shunt response but cannot, on its own, be used for selecting patients with idiopathic normal pressure hydrocephalus for shunt surgery.

Clinical, computed tomographic, surgical findings and outcome in dogs with sublumbar abscessation: 16 cases (2013-2019).

To describe the clinical presentation, CT imaging findings, surgical treatment and long-term outcome in dogs with sublumbar abscessation. Medical records of dogs treated for sublumbar abscessation between 2013 and 2019 were retrieved. Criteria for inclusion were a diagnosis of sublumbar abscessation, complete patient history, pre-operative CT imaging, blood work, bacteriology results, record of the surgical treatment, post-operative care and outcome. Sixteen dogs were included in this study with a median follow-up period of 36 months (15/16). Clinicals signs included flank or lumbar soft tissue swelling (12/16), lumbar pain (11/16), hyperthermia (8/16), a cutaneous discharging sinus (5/16) and lethargy (5/16). CT findings were: abscesses of varying size localised in the psoas muscles (16/16), spondylitis (12/16), vertebral osteomyelitis (6/16), discospondylitis (2/16) and epidural inflammation (8/16). Thoracic lesions were present in eight of 12 dogs. Exploratory surgery was performed in 16 dogs via a midline celiotomy in 15 of 16 and a lateral approach in one of 16 cases. The surgical approach was selected based on the location of the draining tracts detected on CT imaging. Vertebral body curettage was performed in five of 16 cases with lesions identified on CT. Vegetal foreign material was found in seven of 16 dogs. Of the 15 animals with long-term follow-up, 13 had no signs of recurrence. Surgical treatment of sublumbar abscessation resulted in a good long-term outcome when CT was used to guide the surgical approach and to plan the procedure. Our study highlights common vertebral and epidural lesions associated with sublumbar abscesses with a prevalence of 87.5%.

O48 PREOPERATIVE CT IMAGING IN PATIENTS WITH STRANGULATED ABDOMINAL WALL HERNIAS DELAYS SURGERY AND INCREASE RISK OF BOWEL RESECTION: A RETROSPECTIVE RECORD BASED STUDY

Abstract Aim “To investigate whether preoperative CT imaging in acute symptomatic hernia was associated with either surgical delays or increase risks of bowel ischemia and the need for resection.” Material and Methods “The data was collected retrospectively for patients who had emergency hernia surgeries in the period between June 2003 till January 2021. We studied the role of preoperative CT scan in delaying surgical intervention and its impaction on intra-operative surgical intervention, postoperative complication, HDU admission and hospital length of stay.” Results “Data analysis was performed for 505 patients, 191 had preoperative CT scan. Hernia types included inguinal in 164 patients (32.5%); umbilical in 164 (32.5%); femoral in 69 (13.7%); incisional in 69 (13.7%); epigastric in 30 (5.9%); Spigelian in 9 (1.8%). Preoperative CT scan was associated with surgery delay (22.0 hours vs 13.0 hours, P 9.77e-16). Delayed surgery had an impact on increasing postoperative complications (5.2% vs 3.5%, P 0.4741), longer mean postoperative hospital lengths of stay (9.23 days vs 5.12 days, P 2.2e-16), and increase HDU admission (11.0% vs 4.8%, P 0.01408). Increase bowel resection (12% vs 6.4%, P 0.04032) with surgery delay (20.0 hours vs 12.0 hours, P 0.003448) and also increase omentum resection (7.3% vs 5.4%, P 0.4974) with surgery delay (22.5 hours vs 13.5 hours, P 0.02083) were noted.” Conclusions “Pre-operative CT scan for emergent hernias leads to delay in surgical intervention. Surgery delay leads to more aggressive intra-operative intervention and worse postoperative outcomes.”

Reconstructing the nasal septum from instrument motion during septoplasty surgery

Purpose: Surgery involves modifying anatomy to achieve a goal. Reconstructing anatomy can facilitate surgical care through surgical planning, real-time decision support, or anticipating outcomes. Tool motion is a rich source of data that can be used to quantify anatomy. Our work develops and validates a method for reconstructing the nasal septum from unstructured motion of the Cottle elevator during the elevation phase of septoplasty surgery, without need to explicitly delineate the surface of the septum. Approach: The proposed method uses iterative closest point registration to initially register a template septum to the tool motion. Subsequently, statistical shape modeling with iterative most likely oriented point registration is used to fit the reconstructed septum to Cottle tip position and orientation during flap elevation. Regularization of the shape model and transformation is incorporated. The proposed methods were validated on 10 septoplasty surgeries performed on cadavers by operators of varying experience level. Preoperative CT images of the cadaver septums were segmented as ground truth. Results: We estimated reconstruction error as the difference between the projections of the Cottle tip onto the surface of the reconstructed septum and the ground-truth septum segmented from the CT image. We found translational differences of and a rotational differences of between the reconstructed septum and the ground-truth septum [median (interquartile range)], given the optimal regularization parameters. Conclusions: Accurate reconstruction of the nasal septum can be achieved from tool tracking data during septoplasty surgery on cadavers. This enables understanding of the septal anatomy without need for traditional medical imaging. This result may be used to facilitate surgical planning, intraoperative care, or skills assessment.

Use of a standardized reporting template: can we improve report quality in pancreatic and peri-ampullary malignancy?

Accurate pancreatic and periampullary cancer staging with resectability assessment is vital to optimize surgical management and improve patient outcomes. The aim of this study is to assess the usefulness of a standardized reporting template. Retrospective review of all surgically managed patients with pancreatic or periampullary malignancy between January 2018 and June 2019. Pre-operative CT imaging report was anonymised and audited against a modified NCCN reporting template. The same imaging studies were re-reported by two experienced GI radiologists using the same template. Fifty-nine patients (37 male) with median age of 68 years (36-83) underwent surgery for suspected pancreatic/peri-ampullary malignancy. The median time between pre-operative CT scan and surgery was 56.5 days (14-225). The use of reporting template resulted in significant increase in number of reported key features (p <0.005), interobserver agreed features (p< 0.005) and overall k-value assessed interobserver agreement (p< 0.005). Template reports correlated closely with key intraoperative findings whilst primary free text reports did not (k-value 0.85-0.96 versus 0.20-0.46, p< 0.05). The use of a reporting template resulted in a more complete and accurate pancreatic/peri-ampullary tumour evaluation, improved inter-observer relatability and correlation with intraoperative findings.

Impact of Muscle Mass Depletion on Surgical Outcomes in Patients with Primary High-grade Serous Ovarian Cancer Undergoing CRS and HIPEC.

To investigate the effect of sarcopenia on surgical outcomes in patients with primary high-grade serous ovarian cancer undergoing cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS and HIPEC). Descriptive study. Department of Surgical Oncology, Faculty of Medicine, Ankara University Ankara, Turkey, from January 2013 to January 2020. Forty patients, who underwent CRS and HIPEC with the diagnosis of primary high-grade serous ovarian cancer and peritoneal carcinomatosis were included in the study. Preoperative staging CT images were used to determine total psoas ındex values by measuring psoas muscle area at the level of L3 vertebra. Patients with total psoas ındex values below the cut-off levels were considered sarcopenic. Demographic, clinicopathological and perioperative results were compared between sarcopenic and non-sarcopenic patients. Serious postoperative complications (36.4% vs. 6.9%, p=0.039) and infective (54.5% vs. 17.2%, p=0.042) and pulmonary (72.7% vs. 34.5%, p=0.040 complications were significantly higher in sarcopenic patients. Hospital stay [20(12-25) vs. 12(9-16.5) days, p=0.017] and ICU stay [4(2-6) vs. 2(1-2.5) days, p=0.013)] were found to be longer in sarcopenic patients. In univariate analysis, advanced age (OR: 1.40 95% CI: 1.07-1.84; p=0.021) and sarcopenia (OR: 7.71% 95 CI: 1.17-51.06; p=0.039) were significantly associated with serious postoperative complications. The presence of sarcopenia (OR: 0.050 95% CI: 0.004-0.675; p=0.024) was found to be independent predictor of serious postoperative complications. Sarcopenia can easily be diagnosed without additional cost or radiation exposure with routine preoperative staging CT images. Identification of sarcopenic ovarian cancer patients in preoperative period may affect patient selection, predictability of possible serious complications, elective operation preparation process with a combination of nutrition and exercise therapy, thus postoperative complication rates may be reduced and short-term results may be improved. Key Words: Cytoreductive surgery, Ovarian cancer, Sarcopenia.

EP.FRI.204 Does Sarcopenia Increase the Risk of Needing a Stoma During Emergency Laparotomy?

Abstract Aims Sarcopenia is a multisystem disorder which can be diagnosed clinically and radiologically. It is associated with impaired functional status and inferior perioperative outcomes, in particular increased mortality following emergency laparotomy. This study aimed to show whether sarcopenia, as defined by low psoas muscle area (PMA) on pre-operative CT, was associated with increased need for stoma formation. Methods A retrospective analysis of consecutive emergency general surgical laparotomies over a 3-year period. PMA was measured on a single pre-operative CT image at L3 and normalized to vertebral body area to create a psoas muscle index (PMI). New stoma formation and perioperative outcomes were recorded from patient records. Cases were split by the median value into high “non-sarcopenic” and low “sarcopenic” PMI groups. Results 299 patients underwent emergency laparotomy between 01/01/2016 and 31/12/2018. 46 patients (30.67%) in the low psoas index group required a stoma compared with 37 (24.83%) in the higher group (p = 0.159). Survival was inferior in the sarcopenic group with a mean survival of 42 months compared to 48 months in the non-sarcopenic group (p = 0.032). Median follow-up was 43 months. Patients in the sarcopenic group were significantly older (Mean age 68 compared to 54 in the non-sarcopenic group, p = &amp;lt;0.001) but there was no difference in other baseline variables. Conclusions Sarcopenia does not significantly increase the risk of requiring a stoma during emergency laparotomy but does reduce survival.