Preoperative Computed Tomography Research Articles

The Coexistence of Carotico-Clinoid Foramen and Interclinoidal Osseous Bridge: An Anatomo-Radiological Study With Surgical Implications.

The coexistence of complete carotico-clinoid bridge (CCB), an ossification between the anterior (ACP) and the middle clinoid (MCP), and an interclinoidal osseous bridge (ICB), between the ACP and the posterior clinoid (PCP), represents an uncommonly reported anatomic variant. If not adequately recognized, osseous bridges may complicate open or endoscopic surgery, along with the pneumatization of the ACP, especially when performing anterior or middle clinoidectomies. According to Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews guidelines, a systematic scoping review was conducted up to June 5, 2023. PubMed, Scopus, Web of Science databases, and additional citations were searched. Two hundred high-resolution noncontrast computed tomography (CT) scans (400 sides) and 41 dry skulls (82 sides) were analyzed to identify the different morphology of sellar bridges, focusing on the coexistence of complete CCF and ICB. Two embalmed latex-injected heads with coexisting CCF and ICB were dissected step-by-step to show the anatomic relationship with the surrounding structures from an endoscopic and microscopic perspective. A total of 19 articles were included. The review identified a complete CCF and ICB rate ranging from 4.92% to 6.3%. The analysis of 200 CT scans revealed a rate of coexistence in 4% of the cases, all encountered in White women. Two different types of interclinoid bridges were identified based on the degree of bone mineralization. Both endoscopic and macroscopic step-by-step dissections highlighted variability in morphology and consistency of the sellar bridges and the close relationship with the cavernous sinus neurovascular structures. The coexistence of CCF and ICB is an anatomic variation found in 4% of cases. Preoperative knowledge of the degree of mineralization and its relationship with surrounding structures is essential to performing safe surgery and minimizing cranial nerve and vascular injuries. Preoperative high-resolution CT scans can adequately identify these anatomic variations.

Fully automated determination of robotic pedicle screw accuracy and precision utilizing computer vision algorithms

Historically, pedicle screw accuracy measurements have relied on CT and expert visual assessment of the position of pedicle screws relative to preoperative plans. Proper pedicle screw placement is necessary to avoid complications, cost and morbidity of revision procedures. The aim of this study was to determine accuracy and precision of pedicle screw insertion via a novel computer vision algorithm using preoperative and postoperative computed tomography (CT) scans. Three cadaveric specimens were utilized. Screw placement planning on preoperative CT was performed according to standard clinical practice. Two experienced surgeons performed bilateral T2–L4 instrumentation using robotic-assisted navigation. Postoperative CT scans of the instrumented levels were obtained. Automated segmentation and computer vision techniques were employed to align each preoperative vertebra with its postoperative counterpart and then compare screw positions along all three axes. Registration accuracy was assessed by preoperatively embedding spherical markers (tantalum beads) to measure discrepancies in landmark alignment. Eighty-eight pedicle screws were placed in 3 cadavers’ spines. Automated registrations between pre- and postoperative CT achieved sub-voxel accuracy. For the screw tip and tail, the mean three-dimensional errors were 1.67 mm and 1.78 mm, respectively. Mean angular deviation of screw axes from plan was 1.58°. For screw mid-pedicular accuracy, mean absolute error in the medial–lateral and superior–inferior directions were 0.75 mm and 0.60 mm, respectively. This study introduces automated algorithms for determining accuracy and precision of planned pedicle screws. Our accuracy outcomes are comparable or superior to recent robotic-assisted in vivo and cadaver studies. This computerized workflow establishes a standardized protocol for assessing pedicle screw placement accuracy and precision and provides detailed 3D translational and angular accuracy and precision for baseline comparison.

Longitudinal Assessment of Clinical Outcomes After Arthroscopic Treatment for Hip Synovial Chondromatosis and the Effect of Residual Loose Bodies: Minimum 4-Year and 8-Year Follow-up

Background: Arthroscopic treatment is recommended for hip synovial chondromatosis. However, evidence regarding long-term clinical outcomes is limited. Purpose: To evaluate long-term patient-reported outcomes (PROs) and survival, and to determine the potential effect of residual loose bodies, as evaluated by immediate postoperative computed tomography (CT), on clinical outcomes. Study Design: Case series; Level of evidence, 4. Methods: A consecutive cohort of patients undergoing arthroscopic treatment and diagnosed with synovial chondromatosis between March 2010 and May 2015 were included in the study. Preoperative radiography, CT, and magnetic resonance imaging were performed. Preoperative, midterm (minimum of 4 years), and long-term (minimum of 8 years) PROs were collected for visual analog scale for pain, modified Harris Hip Score (mHHS), Non-Arthritic Hip Score (NAHS), and 12-item international Hip Outcome Tool (iHOT-12). The percentages achieving minimal clinically important difference (MCID) were calculated. PROs and survival were compared between patients with and without residual loose bodies evident on immediate postoperative CT scan. Results: A total of 28 patients (20% of patients were lost to follow-up) were included in the study with a mean follow-up period of 104.9 months (range, 96-139 months). PROs including visual analog scale for pain (preoperative, 3.8 ± 1.2; midterm, 0.9 ± 1.7; long-term, 0.8 ± 1.4), mHHS (preoperative, 66.4 ± 14.4; midterm, 92.8 ± 12.3; long-term, 93.5 ± 10.5), NAHS (preoperative, 45.2 ± 16.2; midterm, 81.8 ± 15.3; long-term, 83.1 ± 12.9), and iHOT-12 (preoperative, 48.4 ± 15.6; midterm, 69.3 ± 11.7; long-term, 72.7 ± 11.4) were improved at both midterm and long-term follow-up (all with P < .001). In total, 27 (96.4%), 28 (100%), and 26 (92.9%) patients achieved MCID for mHHS, NAHS and iHOT-12, respectively, at the long-term follow-up. No significant difference was found in any of the PROs and the rate of achieving MCID between midterm and long-term follow-up (all with P > .05). One patient (3.6%) underwent revision surgery. Among the 23 patients who had loose bodies on preoperative CT or radiographs, 14 patients (60.9%) with residual loose bodies evident on immediate postoperative CT demonstrated lower NAHS (P = .045) and iHOT-12 (P = .037) scores but a comparable survival (P > .05) at long-term follow-up compared with those who did not have loose bodies. Conclusion: Arthroscopic treatment for hip synovial chondromatosis achieved satisfactory long-term clinical outcomes with strong survival. Most patients maintained or improved their overall functional status between midterm and long-term follow-up. Furthermore, patients with residual loose bodies had less favorable clinical outcomes, although the survival rate was comparable.

Preoperative computed tomography semantic features in predicting lymph node metastasis of part-solid nodules in non-small cell lung cancer: a multicenter retrospective study.

Lymph node metastasis (LNM) is the most common route of metastasis for lung cancer, and it is an independent risk factor for long-term survival and recurrence in patients with non-small cell lung cancer (NSCLC). The purpose of this study was to explore the value of preoperative computed tomography (CT) semantic features in the differential diagnosis of LNM in part-solid nodules (PSNs) of NSCLC. A total of 955 patients with NSCLC confirmed by postoperative pathology were retrospectively enrolled from January 2019 to March 2023. The clinical, pathological data and preoperative CT images of these patients were investigated and statistically analyzed in order to identify the risk factors for LNM. Multivariate logistic regression was used to select independent risk factors and establish different prediction models. Ten-fold cross-validation was used for model training and validation. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated, and the Delong test was used to compare the predictive performance between the models. LNM occurred in 68 of 955 patients. After univariate analysis and adjustment for confounding factors, smoking history, pulmonary disease, solid component proportion, pleural contact type, and mean diameter were identified as the independent risk factors for LNM. The image predictors model established by the four independent factors of CT semantic features, except smoking history, showed a good diagnostic efficacy for LNM. The AUC in the validation group was 0.857, and the sensitivity, specificity, and accuracy of the model were all 77.6%. Preoperative CT semantic features have good diagnostic value for the LNM of NSCLC. The image predictors model based on pulmonary disease, solid component proportion, pleural contact type, and mean diameter demonstrated excellent diagnostic efficacy and can provide non-invasive evaluation in clinical practice.

Accuracy of patient-specific instrumentation for implant positioning in custom-made total ankle arthroplasty.

This retrospective radiological analysis aimed to assess the accuracy of implant positioning in patients with ankle arthritis undergoing custom-made total ankle arthroplasty (TAA) with patient-specific instrumentation (PSI) compared with preoperative planning. Patients who underwent custom-made TAA with PSI from January 2018 to March 2023 were retrospectively evaluated, focusing on the tibial anterior surface (TAS) angle, tibial lateral surface (TLS) angleand tibiotalar ratio (TTR). Additionally, data regarding the time from the preoperative computed tomography (CT) scan to surgery, associated proceduresand complications were recorded. No associated procedures were performed, and only one intraoperative complication, an iatrogenic lateral malleolar fracture, was recorded. In the coronal plane, custom-made TAA with PSI consistently achieved precise positioning of prosthetic components, even in cases with significant preoperative deformities or bone deficits. However, a statistically significant deviation from the planned values was observed in the sagittal plane (p = 0.007). A notable correlation was identified between the time elapsed from the preoperative CT scan to surgery and the deviation from the planned to the actual postoperative TAS angle (p < 0.001). This study underscores the efficacy of PSI systems in achieving precise positioning in the coronal plane, in accordance with preoperative planning. In contrast, sagittal plane positioning did not demonstrate the same level of accuracy, as evidenced by a statistically significant difference between the planned and postoperative TLS values. Nevertheless, all measurements remained within the recommended range according to the existing literature. Level IV.

The role of the right atrial appendage and right atrium in post-radiofrequency ablation recurrence in different types of atrial fibrillation

To quantitatively evaluate the relationship between the anatomical parameters of the right atrium and the recurrence of atrial fibrillation (AF) after radiofrequency ablation, considering different types of AF, utilizing 256-slice spiral computed tomography (CT). A total of 297 patients with AF who underwent initial radiofrequency ablation were enrolled, divided into the paroxysmal atrial fibrillation (PaAF) group (n=230) and the persistent atrial fibrillation (PeAF) group (n=67). Subsequently, patients in each group were further stratified into recurrent and non-recurrent subgroups. In addition, 100 healthy outpatients were selected as the normal group. All patients underwent preoperative cardiac CT (CCT) examination. The volumes of the right atrium (RA), right atrial appendage (RAA), and left atrial (LA), RAA height, the length, short diameter, perimeter, and area of the RAA base, anteroposterior diameter of the RA, tricuspid annulus diameter, crista terminalis, and inferior vena cavotricuspid isthmus (CTI) on CCT images were measured. In both the PaAF group and the PeAF group, except for the crista terminalis thickness, the other measured parameters were greater than those in the normal group, and recurrent patients exhibited larger RAA base, crista terminalis and LA volume. Recurrent patients with PeAF presented larger RAVI, while recurrent patients with PaAF did not. The short diameter of the RAA base was an independent predictor of recurrence in patients with PaAF (p=0.001), while the height of the RAA, thickness of the crista terminalis, and hypertension were independent predictors of recurrence in PeAF (p<0.05). The ROC curve was used to analysis the predictive model in PaAF and PeAF group, the corresponding sensitivity and specificity were 0.604 and 0.864 in PaAF group, respectively (AUC=0.840, P=0.001), in PeAF group, the corresponding sensitivity and specificity were 0.967 and 0.892, respectively (AUC=0.959, P=0.001). The short diameter of RAA base > 22.15 mm had the highest predictive value for recurrence in PaAF patients, with a sensitivity of 0.887, and a specificity of 0.520 (AUC: 0.743, p=0.001). The RAA height > 28.95 mm has the highest predictive value for recurrence in PeAF, with a sensitivity of 0.633, and a specificity of 0.865 (AUC: 0.816, p=0.001). Recurrent patients both in the PaAF and PeAF groups demonstrated larger RAA base and RA structural parameters. Compared to patients with PaAF, recurrent patients with PeAF presented larger RA volume.

Computed tomography radiomics study of invasion and instability of lung adenocarcinoma manifesting as ground glass nodule.

Ground-glass nodule (GGN) is the most common manifestation of lung adenocarcinoma on computed tomography (CT). Clinically, the success rate of preoperative diagnosis of GGN by puncture biopsy and other means is still low. The aim of this study is to investigate the clinical and radiomics characteristics of lung adenocarcinoma presenting as GGN on CT images using radiomics analysis methods, establish a radiomics model, and predict the classification of pathological tissue and instability of GGN type lung adenocarcinoma. This study retrospectively collected 249 patients with 298 GGN lesions who were pathologically confirmed of having lung adenocarcinoma. The images were imported into the Siemens scientific research prototype software to outline the region of interest and extract the radiomics features. Logistic model A (a radiomics model to identify the infiltration of lung adenocarcinoma manifesting as GGNs) was established using features after the dimensionality reduction process. The receiver operating characteristic (ROC) curve of the model on training set and the verification set was drawn, and the area under the curve (AUC) was calculated. Second, a total of 112 lesions were selected from 298 lesions originating from CT images of at least two occasions, and the time between the first CT and the preoperative CT was defined as not less than 90 days. The mass doubling time (MDT) of all lesions was calculated. According to the different MDT diagnostic thresholds instability was predicted. Finally, their AUCs were calculated and compared. There were statistically significant differences in age and lesion location distribution between the "noninvasive" lesion group and the invasive lesion group (P<0.05), but there were no statistically significant differences in sex (P>0.05). Model A had an AUC of 0.89, sensitivity of 0.75, and specificity of 0.86 in the training set and an AUC of 0.87, sensitivity of 0.63, and specificity of 0.90 in the validation set. There was no significant difference statistically in MDT between "noninvasive" lesions and invasive lesions (P>0.05). The AUCs of radiomics models B1, B2 and B3 were 0.89, 0.80, and 0.81, respectively; the sensitivities were 0.71, 0.54, and 0.76, respectively; the specificities were 0.83, 0.77, and 0.60, respectively; and the accuracies were 0.78, 0.65, and 0.69, respectively. There were statistically significant differences in age and location of lesions between the "noninvasive" lesion group and the invasive lesion group. The radiomics model can predict the invasiveness of lung adenocarcinoma manifesting as GGNs. There was no significant difference in MDT between "noninvasive" lesions and invasive lesions. The radiomics model can predict the instability of lung adenocarcinoma manifesting as GGN. When the threshold of MDT was set at 813 days, the model had higher specificity, accuracy, and diagnostic efficiency.

Diagnostic Benefits and Surgical Implications of Methods for Tumor Localization in Sigmoid and Rectum Tumors.

(1) Background: In our study, we aimed to determine the accuracy rates of imaging methods for sigmoid, rectosigmoid colon, and rectum cancer. (2) Methods: Patients with tumors located in the rectosigmoid colon, sigmoid colon, and rectum who were operated on were included. Upon admission, we examined the patients' first diagnostic colonoscopies and their preoperative repeat control colonoscopies and computed tomography (CT) report. (3) Results: In this study, 23 patients (57.5%) were male. The overall accuracy rates were 80.0% (32/40) in colonoscopy, 65.0% (26/40) in preoperative CT, and 87.5% (35/40) in retro CT, and the differences among the examination methods were statistically significant (p = 0.049). The sensitivity levels decreased to 50.0% for colonoscopy and preoperative CT and 75.0% for retro CT in rectosigmoid colon tumors. In rectal tumors, the sensitivity levels were 75.0% in colonoscopy, 60.0% in preoperative CT, and 80.0% in retro CT. In two patients, the tumor location was given incorrectly, and postoperative pathological evaluations indicated T3N0 tumors; the initially planned treatment was thus changed to include radiotherapy in addition to chemotherapy in the postoperative period because the tumor was located in the middle rectum. (4) Conclusions: Accuracy in tumor localization in sigmoid, rectosigmoid, and rectum tumors still needs to be improved, which could be accomplished with prospective studies. CT evaluations for cancer localization in this patient group should be re-evaluated by a radiologist.

125I seed implantation for lymph node metastasis from radioactive iodine-refractory differentiated thyroid carcinoma: a study on short-term efficacy and dosimetry.

To investigate the feasibility and evaluate the safety and effectiveness of Computed Tomography (CT) guided125I radioactive particle implantation for treating lymph node metastases in radioiodine-refractory differentiated thyroid cancer (RAIR-DTC). To verify the accuracy of the computerized three-dimensional treatment planning system (TPS) in treating lymph node metastasis using125I particle implantation at the dosimetric level. A retrospective analysis was conducted on 42 patients with RAIR-DTC and lymph node metastases who were admitted to the General Hospital of the Northern Theater Command between December 2016 and January 2019. During this analysis, physicians utilized preoperative CT images to design an intraoperative plan using TPS. The dosimetric parameters of the postoperative plan were then compared to the preoperative plan. Additionally, this study examined the changes in tumor size and tumor-related marker Thyroglobulin (Tg) values in patients at 2, 6, and 12 months after the operation. The number of125I radioactive particles implanted in 42 patients was 226, with an average of 14.5 (range 2.0-30.0) particles implanted per lesion. The local remission rates were 97.62% (41/42), 88.10% (37/42), and 85.71% (36/42) at 2, 6, and 12 months postoperatively, respectively. The volume of the lesions was (4.44 ± 1.57) cm3, (4.20 ± 1.70) cm3, and (4.23 ± 1.77) cm3at 2, 6, and 12 months after treatment, respectively, which significantly decreased from the preoperative baseline level of (6.87 ± 1.67) cm3(t-values: 9.466, 9.923, 7.566, all P<0.05). The Tg levels were 15.95 (5.45, 73.93) μg/L, 8.90 (2.20, 39.21) μg/L, and 6.00 (1.93, 14.18) μg/L at 2, 6, and 12 months after treatment, respectively, which were significantly lower than the preoperative baseline levels of 53.50 (20.94, 222.92) μg/L (Z values: -5.258, -5.009, -4.987, all P < 0.001). Postoperatively, Delivered to 90% of the GTV(D90) was slightly lower than the prescribed dose in 95.23% (40/42) of patients, but the difference was not statistically significant [(12,378.8 ± 3,182.0), (12,497.8 ± 1,686.4) cGy; t=0.251, P>0.05], and postoperative dose parameters delivered to 100% of the gross tumor volume (GTV)(D100) (6,881.5 ± 1,381.8) cGy, the volume percentages of GTV receiving 150% of the prescribed dose(V150) (58.5 ± 18.40)%) were lower than the preoperative plan D100 (8,085.8 ± 2,330.0) cGy, V150 (66.5 ± 17.70)%; t-value=8.913 and 3.032, both P<0.05; the remaining indicators were not significantly different from the preoperative plan (the differences in the number of implanted particles, Planning Target Volume(PTV), the volume percentages of GTV receiving 100% of the prescribed dose(V100), Homogeneity Index(HI)were not statistically significant (t/Z = -0.593, -1.604, 1.493, -0.663, all P>0.05). Referring to the TPS preoperative plan, the125I particle implantation therapy for RAIR-DTC lymph node metastasis can achieve the expected dose distribution, ensuring precise short-term local tumor control efficacy.

Accuracy of Phantomless Calibration of Routine Computed Tomography Scans for Opportunistic Osteoporosis Screening in the Spine Clinic.

Diagnostic accuracy study. To establish a simple method of phantomless bone mineral density (BMD) measurement by using preoperative lumbar Computed Tomography (CT) scans, and compare the accuracy of reference tissue combinations to diagnose low BMD against uncalibrated Hounsfield units (HUs). HUs are used as a measure of BMD; however, associations between HU and T-scores vary widely. Quantitative CT (qCT) scans are more accurate, but they require density calibration with an object of known density (phantom), which limits feasibility. As an emerging technique, phantomless (internal) calibration of routine CT scans may provide a good opportunity for screening. Patients who were scheduled to undergo lumbar surgery, with a preoperative CT scan, and a dual-energy x-ray absorptiometry (DXA) scan within six months were included. Four tissues were selected for calibration: subcutaneous adipose (A), erector spinae (ES), psoas (P) and aortic blood (AB). The HUs of these tissues were used in linear regression against ground-truth values. Calibrations were performed by using two different internal tissues at a time to maintain simplicity and in-office applicability.Volumetric bone mineral densities (vBMD) derived from internally calibrated CT scans were analyzed for new threshold values for low bone density. Areas under the curve (AUC) were calculated with 95% confidence intervals (CI). 45 patients were included (M/F=10/35, mean age:63.3). Calibrated vBMDs had stronger correlations with DXA T-scores when compared with HUs, with L2 exhibiting the highest coefficients. Calibration by using A and ES with the threshold of 162mg/cm3 had a sensitivity of 90% in detecting low BMD (AUC=0.671). This novel method allows simple, in-office calibration of routine preoperative CT scans without the use of a phantom. Calibration using adipose and erector spinae with a threshold of 162mg/cm3 is proposed for low bone density screening with high sensitivity (90%). Level III.

Association of computed tomography-derived muscle mass and quality with delayed acquisition independent walking after cardiovascular surgery.

In the context of cardiovascular surgery, the foremost concern lies in delayed functional recovery, as typified by the acquisition of independent walking after surgery, among older patients with decline in skeletal muscle mass and quality. Computed tomography (CT), which is typically employed for the preoperative assessment of pathological conditions in patients undergoing cardiovascular surgery, is also suitable for screening for potential decline in skeletal muscle mass and quality. The aim of this study was to examine the predictive capabilities of CT-derived parameters such as muscle mass and muscle quality for the delayed acquisition of independent walking in the postoperative period. This retrospective study enrolled consecutive Japanese patients who underwent elective cardiovascular surgery between May 2020 and January 2023. In total, 139 patients were included in the analyses. Based on the preoperative CT image, the psoas muscle volume index (PMVI) and psoas muscle attenuation (PMA) were calculated. Information on patient characteristics, including preoperative physical fitness such as handgrip strength/body mass index (GS/BMI), short physical performance battery (SPPB), and 6-min walking distance (6MWD), were obtained from the medical records. We defined delayed acquisition of independent walking after surgery as the inability to walk 100m within 4days after surgery. The median age of the patients was 72 (interquartile: 64-78) years, and 74.8% (104/139) were men; 47.5% corresponded to the delayed group. The areas under the curves of SPPB, GS/BMI, 6MWD, PMVI, and PMA against delayed acquisition of independent walking after surgery were 0.68 [95% confidence interval (CI): 0.59 to 0.77], 0.72 (95% CI: 0.63 to 0.80), 0.73 (95% CI: 0.65 to 0.82), 0.69 (95% CI: 0.60 to 0.78), and 0.78 (95% CI: 0.70 to 0.85), respectively. In the multivariate logistic regression analysis, low PMA was significantly associated with delayed acquisition of independent walking even after adjustment for patient characteristics including physical fitness [model 1: SPPB (OR, 1.14; 95% CI: 1.03-1.25), model 2: GS/BMI (OR, 1.13; 95% CI: 1.03-1.25), and model 3: 6MWD (OR, 1.14; 95% CI: 1.03-1.25)], but PMVI was not. Our study revealed a strong association between PMA, a marker of CT-derived muscle quality, and the postoperative delay in achieving independent walking in patients who underwent cardiovascular surgery. The technique to obtain information on muscle quality during the time period before surgery may be an option for timely therapeutic intervention in patients who may have delayed acquisition of independent walking after surgery.

IMG-32. USER EVALUATION OF AN AI-POWERED WEB APPLICATION TO SUPPORT RADIOGRAPHIC INTERPRETATION OF PATIENTS WITH ADAMANTINOMATOUS CRANIOPHARYNGIOMA

Abstract BACKGROUND In neuro-oncology, accurately interpreting radiographic images, especially for diagnosing central nervous system (CNS) tumors like Adamantinomatous Craniopharyngioma (ACP), presents formidable challenges. Even with advanced imaging technologies such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), pinpointing features related to ACP invasiveness remains daunting. METHODS We introduced an interactive web application that utilizes a custom AI model to analyze preoperative MRI and CT images of 50 patients with ACP. This application can predict a 12-point radiographic feature profile and rank patients based on similarity, aiming to support clinicians in making more precise diagnoses. We deployed our application on a hospital-grade radiographic reading terminal. Our application’s utility and user-friendliness were evaluated through a user study involving four neurosurgeons and two neuroradiologists, who constructed 12-point radiographic feature profiles for ten patients within a 30-minute timeframe given patient MRI and CT images. RESULTS Our study subjects reported high self-assessed numeracy (SNS scores ranging from 4 to 5.25) despite varied preferences in engaging with numerical data. Subjects could efficiently learn to navigate our software interface, with an average task completion time of approximately 3 minutes and 25 seconds per patient. Introducing AI into the task workflow resulted in a slight, statistically non-significant increase in completion time, indicating that while AI modifies interaction dynamics, it does not significantly hinder efficiency in task performance. We observed distinct agreement patterns between clinicians and AI prediction, utilizing Fleiss’ Kappa for categorization. AI assistance subtly boosted clinicians’ confidence and slightly lessened the perceived difficulty of interpreting radiographic images. However, these benefits were not statistically significant. CONCLUSIONS Our study highlights the promise of AI in improving neuro-oncology diagnostics, showing that clinicians quickly adapted to an AI-enhanced application, which subtly influenced their radiographic interpretation. This finding underscores the potential for AI to enhance decision-making accuracy in challenging cases like ACP.

Advanced Gastric Cancer: CT Radiomics Prediction of Lymph Modes Metastasis After Neoadjuvant Chemotherapy.

This study aims to create and assess machine learning models for predicting lymph node metastases following neoadjuvant treatment in advanced gastric cancer (AGC) using baseline and restaging computed tomography (CT). We evaluated CT images and pathological data from 158 patients with resected stomach cancer from two institutions in this retrospective analysis. Patients were eligible for inclusion if they had histologically proven gastric cancer. They had received neoadjuvant chemotherapy, with at least 15 lymph nodes removed. All patients received baseline and preoperative abdominal CT and had complete clinicopathological reports. They were divided into two cohorts: (a) the primary cohort (n = 125) for model creation and (b) the testing cohort (n = 33) for evaluating models' capacity to predict the existence of lymph node metastases. The diagnostic ability of the radiomics-model for lymph node metastasis was compared to traditional CT morphological diagnosis by radiologist. The radiomics model based on the baseline and preoperative CT images produced encouraging results in the training group (AUC 0.846) and testing cohort (AUC 0.843). In the training cohort, the sensitivity and specificity were 81.3% and 77.8%, respectively, whereas in the testing cohort, they were 84% and 75%. The diagnostic sensitivity and specificity of the radiologist were 70% and 42.2% (using baseline CT) and 46.3% and 62.2% (using preoperative CT). In particular, the specificity of radiomics model was higher than that of conventional CT in diagnosing N0 cases (no lymph node metastasis). The CT-based radiomics model could assess lymph node metastasis more accurately than traditional CT imaging in AGC patients following neoadjuvant chemotherapy.

Does timely reporting of preoperative CT scans influence outcomes for patients following emergency laparotomy?

Timely preoperative computed tomography (CT) scans are important for patients requiring emergency laparotomy. United Kingdom guidelines state that a CT scan should be reported within 1h for 'critical' patients (will alter management at the time) and within 12h for 'urgent' patients (will alter management but not necessarily that day). An observational study included patients who were added to the National Emergency Laparotomy Audit (NELA) at a National Health Service trust from 2014 to 2021. The association of compliance with timings guidance and mortality was investigated. Multivariable logistic regression was used to determine the odds ratio of adherence to guidelines according to age, gender, night time admission, American Society of Anesthesiology (ASA) score, NELA mortality risk and category of scan. Further models determined the influence of adherence to guidelines on mortality, also adjusted for these variables. There were 1,299 patients (48% 'critical' and 52% 'urgent' CT scans). Only 360/1,299 (28%) of scans were undertaken with adherence to the timing guidelines. Critical scans were less likely to adhere to guidelines. Although univariable analysis suggested that adherence to guidelines was associated with reduced mortality, this was not the case in the multivariable model: only age, ASA and NELA mortality risk remained significantly associated with mortality. A minority of patients met the recommended preoperative CT report timings, and this was less likely for scans designated 'critical'. This did not appear to affect mortality when adjusted for key variables of risk. This illustrates the phenomenon of guideline adherence appearing to affect patient outcomes as a product of selection bias rather than causality.

Effect of clinician's experience and expertise on the inter- and intra-observer reliability of the computed tomography-based classification systems in posterior malleolus fractures.

Three computed tomography (CT)-based classifications, including Haraguchi, Bartoníček-Rammelt, and Mason-Molloy systems, have been developed to better determine the characteristics of posterior malleolus fractures (PMFs). The aims of this study were (1) to determine the intra- and inter-observer reliability of the computed tomography-based classification systems and (2) to investigate the clinical experience and expertise on their reliabilities. Sixty-seven preoperative ankle CT scans of 67 adult patients with "ankle fracture with the involvement of the posterior malleolus"'' were retrospectively identified. CT images were assessed by 10 observers with different levels of clinical experience from 2 different specialties, including orthopedics and radiology. The observers were asked to classify PMFs according to 3 CT-based classifications on 2 separate occasions with a 4-week interval. Cohen's κ values were measured for 2 raters and Fleiss' κ values were measured for 3 raters and more. Overall, each classification had moderate to very good intraobserver reliability (κ=0.41 to 0.95, P < .01) as well as moderate interobserver reliability for each of the 2 separate assessments (κ=0.41 to 0.60, P < .01 for the first occasion; κ=0.44 to 0.59, P < .01 for the second occasion). Interobserver agreement among the foot and ankle surgeons regarding the Haraguchi and Bartoníček classifications was substantial for both assessment periods, whereas there was a moderate agreement for the Mason classification. Orthopedic residents showed moderate interobserver agreement in each period for both Bartoníček and Mason classifications. Radiology experts illustrated slight and fair agreements in the 2 assessments for Mason classification, moderate agreement in both assessments for Haraguchi classification, and substantial to moderate agreement in the first and second assessments for Bartoníček classification, respectively. Computed tomography-based classification system for PMFs demonstrated moderate interobserver reliability as well as moderate to very good intraobserver reliability. Moreover, foot and ankle specialists exhibit enhanced K values for both inter and intraobserver reliability for each classification system, consistency seems to increase as the interest in the field condenses.

Deep learning model utilizing clinical data alone outperforms image-based model for hernia recurrence following abdominal wall reconstruction with long-term follow up

BackgroundDeep learning models (DLMs) using preoperative computed tomography (CT) imaging have shown promise in predicting outcomes following abdominal wall reconstruction (AWR), including component separation, wound complications, and pulmonary failure. This study aimed to apply these methods in predicting hernia recurrence and to evaluate if incorporating additional clinical data would improve the DLM’s predictive ability.MethodsPatients were identified from a prospectively maintained single-institution database. Those who underwent AWR with available preoperative CTs were included, and those with < 18 months of follow up were excluded. Patients were separated into a training (80%) set and a testing (20%) set. A DLM was trained on the images only, and another DLM was trained on demographics only: age, sex, BMI, diabetes, and history of tobacco use. A mixed-value DLM incorporated data from both. The DLMs were evaluated by the area under the curve (AUC) in predicting recurrence.ResultsThe models evaluated data from 190 AWR patients with a 14.7% recurrence rate after an average follow up of more than 7 years (mean ± SD: 86 ± 39 months; median [Q1, Q3]: 85.4 [56.1, 113.1]). Patients had a mean age of 57.5 ± 12.3 years and were majority (65.8%) female with a BMI of 34.2 ± 7.9 kg/m2. There were 28.9% with diabetes and 16.8% with a history of tobacco use. The AUCs for the imaging DLM, clinical DLM, and combined DLM were 0.500, 0.667, and 0.604, respectively.ConclusionsThe clinical-only DLM outperformed both the image-only DLM and the mixed-value DLM in predicting recurrence. While all three models were poorly predictive of recurrence, the clinical-only DLM was the most predictive. These findings may indicate that imaging characteristics are not as useful for predicting recurrence as they have been for other AWR outcomes. Further research should focus on understanding the imaging characteristics that are identified by these DLMs and expanding the demographic information incorporated in the clinical-only DLM to further enhance the predictive ability of this model.

Correlation of CT features of lung adenocarcinoma with sex and age

This study aimed to retrospectively examine the computed tomography (CT) features of lung adenocarcinoma across different demographic groups. Preoperative chest CT findings from 1266 surgically resected lung adenocarcinoma cases were retrospectively analyzed. Lung adenocarcinomas were categorized based on CT characteristics into pure ground glass (pGGO), nodule-containing ground glass opacity (mGGO), and pure solid without containing ground glass opacity (pSD). These categories were correlated with sex, age, EGFR status, and five histopathological subtypes. The diameters of pGGO, mGGO, and pSD significantly increased across all patient groups (P < 0.05). Males exhibited a significantly higher proportion of pSD than females (P = 0.002). The mean diameters of pGGO and pSD were significantly larger in males than in females (P = 0.0017 and P = 0.043, respectively). The frequency of pGGO was higher in the younger age group (≤ 60 years) compared to the older group (> 60 years) for both males (P = 0.002) and females (P = 0.027). The frequency of pSD was higher in the older age group for both sexes. A linear correlation between age and diameter was observed in the entire cohort as well as in the male and female groups (P < 0.0001 for all groups). EGFR mutations were less frequent in pSD compared to pGGO (P = 0.0002) and mGGO (P < 0.0001). The frequency of lesions containing micropapillary components increased from pGGO to mGGO and pSD (P < 0.0001 for all). The frequency of lesions containing solid components also increased from pGGO to mGGO and pSD (P = 0.045, P < 0.0001, and P < 0.0001, respectively). The CT features of lung adenocarcinoma exhibit differences across genders and age groups. Male gender and older age are risk factors for lung adenocarcinoma growth.

International Multi-Specialty Expert Physician Preoperative Identification of Extranodal Extension n Oropharyngeal Cancer Patients using Computed Tomography: Prospective Blinded Human Inter-Observer Performance Evaluation.

Extranodal extension (pENE) is a critical prognostic factor in oropharyngeal cancer (OPC) that drives therapeutic disposition. Determination of pENE from radiological imaging has been associated with high inter-observer variability. However, the impact of clinician specialty on human observer performance of imaging-detected extranodal extension (iENE) remains poorly understood. To characterize the impact of clinician specialty on the accuracy of pre-operative iENE in human papillomavirus-positive (HPV+) OPC using computed tomography (CT) images. This prospective observational human performance study analyzed pre-therapy CT images from 24 HPV+ OPC patients, with duplication of 6 scans (n=30) of which 21 were pathologically confirmed pENE. Thirty-four expert observers, including 11 radiologists, 12 surgeons, and 11 radiation oncologists, independently assessed these scans for iENE and reported human-detected radiologic criteria and observer confidence. The primary outcomes included accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and Brier score for each physician, compared to ground-truth pENE. The significance of radiographic signs for prediction of pENE were determined through logistic regression analysis. Fleiss' kappa measured interobserver agreement, and Hanley-MacNeil AUC discrimination testing. Median accuracy across all specialties was 0.57 (95%CI 0.39 to 0.73), with no specialty showing discriminate performance greater than random estimation (median AUC 0.64, 95%CI 0.44 to 0.83). Significant differences between radiologists and surgeons in Brier scores (0.33 vs. 0.26, p < 0.01), radiation oncologists and surgeons in sensitivity (0.48 vs. 0.69, p > 0.1), and radiation oncologists and radiologists/surgeons in specificity (0.89 vs. 0.56, p > 0.1). Indistinct capsular contour and nodal necrosis were significant predictors of correct pENE status among all specialties. Interobserver agreement was weak for all the radiographic criteria, regardless of specialty (κ<0.6). Multiobserver testing shows physician discrimination of HPV+OPC pENE on pre-operative CT remains non-different than blind guessing, with high interrater variability and low diagnostic accuracy, regardless of clinician specialty. While minor differences in diagnostic performance among specialties are noted, they do not significantly affect the overall poor agreement and discrimination rates observed. The findings underscore the need for further research into automated detection systems or enhanced imaging techniques to improve the accuracy and reliability of iENE assessments in clinical practice.

Radiomics model based on contrast-enhanced computed tomography imaging for early recurrence monitoring after radical resection of AFP-negative hepatocellular carcinoma

BackgroundAlthough radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. Emerging radiomics can reveal subtle structural changes in tumors by analyzing preoperative contrast-enhanced computer tomography (CECT) imaging data and may provide new ways to predict early recurrence (recurrence within 2 years) in AFP-negative HCC. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC.Patients and methodsPatients with AFP-negative HCC who underwent radical resection were included in this study. A computerized tool was used to extract radiomic features from the tumor region of interest (ROI), select the best radiographic features associated with patient’s postoperative recurrence, and use them to construct the radiomics score (RadScore), which was then combined with clinical and follow-up information to comprehensively evaluate the reliability of the model.ResultsA total of 148 patients with AFP-negative HCC were enrolled in this study, and 1,977 radiographic features were extracted from CECT, 2 of which were the features most associated with recurrence in AFP-negative HCC. They had good predictive ability in both the training and validation cohorts, with an area under the ROC curve (AUC) of 0.709 and 0.764, respectively. Tumor number, microvascular invasion (MVI), AGPR and radiomic features were independent risk factors for early postoperative recurrence in patients with AFP-negative HCC. The AUCs of the integrated model in the training and validation cohorts were 0.793 and 0.791, respectively. The integrated model possessed the clinical value of predicting early postoperative recurrence in patients with AFP-negative HCC according to decision curve analysis, which allowed the classification of patients into subgroups of high-risk and low-risk for early recurrence.ConclusionThe nomogram constructed by combining clinical and imaging features has favorable performance in predicting the probability of early postoperative recurrence in AFP-negative HCC patients, which can help optimize the therapeutic decision-making and prognostic assessment of AFP-negative HCC patients.

Predictors of pulmonary metastases on chest computed tomography in children and adolescents with osteosarcoma—tips for qualifying patients for thoracotomy

BackgroundOsteosarcoma is the most common primary malignant bone tumour in children and adolescents. Lungs are the most frequent and often the only site of metastatic disease. The presence of pulmonary metastases is a significant unfavourable prognostic factor. Thoracotomy is strongly recommended in these patients, while computed tomography (CT) remains the gold imaging standard. The purpose of our study was to create tools for the CT-based qualification for thoracotomy in osteosarcoma patients in order to reduce the rate of useless thoracotomies.MethodsSixty-four osteosarcoma paediatric patients suspected of lung metastases on CT and their first-time thoracotomies (n = 100) were included in this retrospective analysis. All CT scans were analysed using a compartmental evaluation method based on the number and size of nodules. Calcification and location of lung lesions were also analysed. Inter-observer reliability between two experienced radiologists was assessed. The CT findings were then correlated with the histopathological results of thoracotomies. Various multivariate predictive models (logistic regression, classification tree and random forest) were built and predictors of lung metastases were identified.ResultsAll applied models proved that calcified nodules on the preoperative CT scan best predict the presence of pulmonary metastases. The rating of the operated lung on the preoperative CT scan, dependent on the number and size of nodules, and the total number of nodules on this scan were also found to be important predictors. All three models achieved a relatively high sensitivity (72–92%), positive predictive value (81–90%) and accuracy (74–79%). The positive predictive value of each model was higher than of the qualification for thoracotomy performed at the time of treatment. Inter-observer reliability was at least substantial for qualitative variables and excellent for quantitative variables.ConclusionsThe multivariate models built and tested in our study may be useful in the qualification of osteosarcoma patients for metastasectomy through thoracotomy and may contribute to reducing the rate of unnecessary invasive procedures in the future.