Preoperative prediction of microsatellite instability status in colorectal cancer based on a multiphasic enhanced CT radiomics nomogram model.

BACKGROUND: To investigate the value of a nomogram model based on the combination of clinical-CT features and multiphasic enhanced CT radiomics for the preoperative prediction of the microsatellite instability (MSI) status in colorectal cancer (CRC) patients. METHODS: A total of 347 patients with a pathological diagnosis of colorectal adenocarcinoma, including 276 microsatellite stabilized (MSS) patients and 71 MSI patients (243 training and 104 testing), were included. Univariate and multivariate regression analyses were used to identify the clinical-CT features of CRC patients linked with MSI status to build a clinical model. Radiomics features were extracted from arterial phase (AP), venous phase (VP), and delayed phase (DP) CT images. Different radiomics models for the single phase and multiphase (three-phase combination) were developed to determine the optimal phase. A nomogram model that combines clinical-CT features and the optimal phasic radscore was also created. RESULTS: Platelet (PLT), systemic immune inflammation index (SII), tumour location, enhancement pattern, and AP contrast ratio (ACR) were independent predictors of MSI status in CRC patients. Among the AP, VP, DP, and three-phase combination models, the three-phase combination model was selected as the best radiomics model. The best MSI prediction efficacy was demonstrated by the nomogram model built from the combination of clinical-CT features and the three-phase combination model, with AUCs of 0.894 and 0.839 in the training and testing datasets, respectively. CONCLUSION: The nomogram model based on the combination of clinical-CT features and three-phase combination radiomics features can be used as an auxiliary tool for the preoperative prediction of the MSI status in CRC patients.

Lung Recruitment Assessed by Electrical Impedance Tomography (RECRUIT): A Multicenter Study of COVID-19 Acute Respiratory Distress Syndrome.

Rationale: Defining lung recruitability is needed for safe positive end-expiratory pressure (PEEP) selection in mechanically ventilated patients. However, there is no simple bedside method including both assessment of recruitability and risks of overdistension as well as personalized PEEP titration. Objectives: To describe the range of recruitability using electrical impedance tomography (EIT), effects of PEEP on recruitability, respiratory mechanics and gas exchange, and a method to select optimal EIT-based PEEP. Methods: This is the analysis of patients with coronavirus disease (COVID-19) from an ongoing multicenter prospective physiological study including patients with moderate-severe acute respiratory distress syndrome of different causes. EIT, ventilator data, hemodynamics, and arterial blood gases were obtained during PEEP titration maneuvers. EIT-based optimal PEEP was defined as the crossing point of the overdistension and collapse curves during a decremental PEEP trial. Recruitability was defined as the amount of modifiable collapse when increasing PEEP from 6 to 24 cm H2O (ΔCollapse24-6). Patients were classified as low, medium, or high recruiters on the basis of tertiles of ΔCollapse24-6. Measurements and Main Results: In 108 patients with COVID-19, recruitability varied from 0.3% to 66.9% and was unrelated to acute respiratory distress syndrome severity. Median EIT-based PEEP differed between groups: 10 versus 13.5 versus 15.5 cm H2O for low versus medium versus high recruitability (P < 0.05). This approach assigned a different PEEP level from the highest compliance approach in 81% of patients. The protocol was well tolerated; in four patients, the PEEP level did not reach 24 cm H2O because of hemodynamic instability. Conclusions: Recruitability varies widely among patients with COVID-19. EIT allows personalizing PEEP setting as a compromise between recruitability and overdistension. Clinical trial registered with www.clinicaltrials.gov (NCT04460859).

Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer.

BACKGROUND: Preoperative assessment of lymphovascular invasion(LVI) of rectal cancer has very important clinical significance. However, accurate preoperative imaging evaluation of LVI is highly challenging because the resolution of MRI is still limited. Relatively few studies have focused on prediction of LVI of rectal cancer with the tool of radiomics, especially in patients with negative statue of MRI-based extramural vascular invasion (mrEMVI).The purpose of this study was to explore the preoperative predictive value of biparametric MRI-based radiomics features for LVI of rectal cancer in patients with the negative statue of mrEMVI. METHODS: The data of 146 cases of rectal adenocarcinoma confirmed by postoperative pathology were retrospectively collected. In the cases, 38 had positive status of LVI. All patients were examined by MRI before the operation. The biparametric MRI protocols included T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI). We used whole-volume three-dimensional method and two feature selection methods, minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO), to extract and select the features. Logistics regression was used to construct models. The area under the receiver operating characteristic curve (AUC) and DeLong's test were used to evaluate the diagnostic performance of the radiomics based on T2WI and DWI and the combined models. RESULTS: Radiomics models based on T2WI and DWI had good predictive performance for LVI of rectal cancer in both the training cohort and the validation cohort. The AUCs of the T2WI model were 0.87 and 0.87, and the AUCs of the DWI model were 0.94 and 0.92. The combined model was better than the T2WI model, with AUCs of 0.97 and 0.95. The predictive performance of the DWI model was comparable to that of the combined model. CONCLUSIONS: The radiomics model based on biparametric MRI, especially DWI, had good predictive value for LVI of rectal cancer. This model has the potential to facilitate the clinical recognition of LVI in rectal cancer preoperatively.

The value of diffusion kurtosis imaging and intravoxel incoherent motion quantitative parameters in predicting synchronous distant metastasis of rectal cancer.

BACKGROUND: The incidence and mortality rate of rectal cancer are still high, the metastasis of rectal cancer are main causes of death. The control of the distant metastasis is one of the main concerns in the treatment of locally advanced rectal cancer, but there are few studies on predicting synchronous distant metastasis (SDM) of rectal cancer. METHOD: The data of patients with rectal adenocarcinoma confirmed by endoscopic biopsy or postoperative pathology from September 2015 to May 2020 in hospital A (center 1) and hospital B (center 2) were analyzed retrospectively, including age, sex, carcinoembryonic antigen, carbohydrate antigen 19-9, tumor location, tumor length, image staging and characteristics. The average age of the 169 patients consisting of 105 males and 64 females in study is 61.2 years. All patients underwent rectal routine rectal MRI, DKI and IVIM examinations on a 3.0-T scanner. Two radiologists sketched regions of interest (ROIs) on b = 1000 s/mm2 DKI and IVIM images to obtain quantitative parameters with FireVoxel manually. We evaluated the difference of histogram analysis, clinical and image data between SDM group and non-SDM group, and evaluated the efficacy of each index in predicting SDM of rectal cancer. RESULTS: The 90th percentile of f values in the SDM group is lower than that in the non-SDM group (29.4 ± 8.4% vs. 35 ± 17.8%, P = 0.005). CA19-9 in the SDM group is higher than that in the non-SDM group (P = 0.003). Low and high rectal cancer are more likely to develop SDM than middle rectal cancer (P = 0.05 and P = 0.047). The combination of these three indexes has a greater area under the curve (AUC) than any one index (0.801 vs. 0.685 (f (90th percentile)) and 0.627 (CA19-9), P = 0.0075 and 0.0058, respectively), and its specificity and sensitivity are 80.0% and 71.6%, respectively. When this combination is incorporated into the predictive nomogram model, the c-index is 0.801 (95% confidence interval (CI): 0.730-0.871). CONCLUSIONS: IVIM quantitative parameters combine with CA19-9 and tumor location can better predict the risk of SDM of rectal cancer.

Duration of diaphragmatic inactivity after endotracheal intubation of critically ill patients.

BACKGROUND: In patients intubated for mechanical ventilation, prolonged diaphragm inactivity could lead to weakness and poor outcome. Time to resume a minimal diaphragm activity may be related to sedation practice and patient severity. METHODS: Prospective observational study in critically ill patients. Diaphragm electrical activity (EAdi) was continuously recorded after intubation looking for resumption of a minimal level of diaphragm activity (beginning of the first 24 h period with median EAdi > 7 µV, a threshold based on literature and correlations with diaphragm thickening fraction). Recordings were collected until full spontaneous breathing, extubation, death or 120 h. A 1 h waveform recording was collected daily to identify reverse triggering. RESULTS: Seventy-five patients were enrolled and 69 analyzed (mean age ± standard deviation 63 ± 16 years). Reasons for ventilation were respiratory (55%), hemodynamic (19%) and neurologic (20%). Eight catheter disconnections occurred. The median time for resumption of EAdi was 22 h (interquartile range 0-50 h); 35/69 (51%) of patients resumed activity within 24 h while 4 had no recovery after 5 days. Late recovery was associated with use of sedative agents, cumulative doses of propofol and fentanyl, controlled ventilation and age (older patients receiving less sedation). Severity of illness, oxygenation, renal and hepatic function, reason for intubation were not associated with EAdi resumption. At least 20% of patients initiated EAdi with reverse triggering. CONCLUSION: Low levels of diaphragm electrical activity are common in the early course of mechanical ventilation: 50% of patients do not recover diaphragmatic activity within one day. Sedatives are the main factors accounting for this delay independently from lung or general severity. Trial Registration ClinicalTrials.gov (NCT02434016). Registered on April 27, 2015. First patients enrolled June 2015.

The impact of tracheostomy timing on clinical outcomes and adverse events in intubated patients with infratentorial lesions: early versus late tracheostomy.

We evaluated the association between the timing of tracheostomy and clinical outcomes in patients with infratentorial lesions. We performed a retrospective observational cohort study in a neurosurgical intensive care unit (ICU) at a tertiary academic medical center from January 2014 to December 2018. Consecutive adult patients admitted to the ICU who underwent resection of infratentorial lesions as well as tracheostomy were included for analysis. Early tracheostomy was defined as performed on postoperative days 1-10 and late tracheostomy on days 10-20 after operation. Univariate and multivariate analyses were used to compare the characteristics and outcomes between both cohorts. A total of 143 patients were identified, and 96 patients received early tracheostomy. Multivariable analysis identified early tracheostomy as an independent variable associated with lower occurrence of pneumonia (odds ratio, 0.25; 95% CI, 0.09-0.73; p = 0.011), shorter stays in ICUs (hazard ratio, 0.4; 95% CI, 0.3-0.6; p = 0.03), and earlier decannulation (hazard ratio, 0.5; 95% CI, 0.4-0.8; p = 0.003). However, no significant differences were observed between the early and late tracheostomy groups regarding hospital mortality (p > 0.999) and the modified Rankin scale after 6 months (p = 0.543). We also identified postoperative brainstem deficits, including cough, swallowing attempts, and extended tongue as well as GCS < 8 at ICU admission as the risk factors independently associated with patients underwent tracheostomy. There is a significant association between early tracheostomy and beneficial clinical outcomes or reduced adverse event occurrence in patients with infratentorial lesions.

Correlation Between Quantitative Assessment of Chest Computed Tomography (CT) Imaging and Prognosis of COVID-19 Patients.

BACKGROUND The aim of our work was to evaluate the correlation between the quantitative parameters of the peak lesion to 25% improvement time (PIT25) and the prognosis of new coronavirus pneumonia (COVID-19) patients by analyzing the changes of chest CT imaging. MATERIAL AND METHODS This retrospective analysis included 68 patients with COVID-19 in the Fifth People's Hospital of Suzhou City. Three radiologists performed a blind evaluation of 4 chest CT images that included the initial scans, the lesion peak, the lesion decreased to 25% of the peak, and the final scan. The score of chest CT lesion, the imaging characteristics of the lesion, the time of the appearance of symptoms related to the CT examination, quantitative assessment of PIT25, and the absorption of the lesion in last CT image were analyzed. Patients were divided into an obvious absorption group and a non-obvious absorption group according to the reduction of the lesion area by greater than 50% or less than 50%. RESULTS In the peak time, the most common images of CT were ground-glass opacities (94.1%), consolidation (85.3%) and reticulation (88.2%), multifocal (97.1%), center and subpleural (54.4%), subpleural distribution (45.6%), and pleural thickening (79.4%). The PIT25 with the prognosis (r=0.53, p=0.00) was significantly relevant. PIT25 was 4.3±0.7 days for the obvious absorption group and 6.8±1.4 days for the non-obvious absorption group. CONCLUSIONS The features of CT image are specific at the peak. The quantitative parameter PIT25 could be used to predict the prognosis of the patients with COVID-19, as COVID-19 patients with a shorter PIT25 have a better prognosis and vice versa.

Use of the Bispectral Index to Predict Recovery of Consciousness in Patients with Spontaneous Intracerebral Hemorrhage After Surgical Hematoma Evacuation: A Prospective Cohort Study.

BACKGROUND Our study aimed to test the predictive value of the bispectral index (BIS) for the post-operational consciousness recovery in patients undergone hematoma evacuation due to spontaneous intracerebral hemorrhage (ICH). MATERIAL AND METHODS In this prospective cohort study, we enrolled adult spontaneous ICH patients after surgical hematoma evacuation who did not recover consciousness on the first postoperative day. After patient enrollment, the BIS was continuously monitored for 12 hours, and the motor response on the Glasgow Coma Scale (GCS-M) was evaluated. The patients were followed up for 30 days and divided into a consciousness recovery group and a nonrecovery group. Receiver operating characteristic curve analysis was performed to investigate the predictive values of the BIS, GCS-M and ICH score on the consciousness recovery. The area under the curve (AUC) and 95% confidence interval (95%CI) were calculated. During the 12-hour monitoring period, the peak BIS value after GCS-M stimulation was used for ROC analysis. RESULTS Of the 55 enrolled patients, 19 patients recovered consciousness, and 36 patients did not. The BIS value of the consciousness recovery group was significantly higher than that of the nonrecovery group (P<0.001). For consciousness recovery prediction, the AUC (95%CI) of the BIS values after external stimulation was 0.97 (0.91-1.00), which was superior to the GCS-M (0.75 [0.59-0.91]) and ICH score (0.57 [0.41-0.73]). CONCLUSIONS Our study demonstrates that BIS might be a potential tool for predicting the consciousness recovery in ICH patients undergone surgical hematoma evacuation.

Effect of High-Flow Nasal Cannula Oxygen Therapy Versus Conventional Oxygen Therapy and Noninvasive Ventilation on Reintubation Rate in Adult Patients After Extubation: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

PURPOSE: We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the effect of high-flow nasal cannula (HFNC) on reintubation in adult patients. PROCEDURES: Ovid Medline, Embase, and Cochrane Database of Systematic Reviews were searched up to November 1, 2016, for RCTs comparing HFNC versus conventional oxygen therapy (COT) or noninvasive ventilation (NIV) in adult patients after extubation. The primary outcome was reintubation rate, and the secondary outcomes included complications, tolerance and comfort, time to reintubation, length of stay, and mortality. Dichotomous outcomes were presented as risk ratio (RR) with 95% confidence intervals (CIs) and continuous outcomes as weighted mean difference and 95% CIs. The random effects model was used for data pooling. FINDINGS: Seven RCTs involving 2781 patients were included in the analysis. The HFNC had a similar reintubation rate compared to either COT (RR, 0.58; 95% CI, 0.21-1.60; P = .29; 5 RCTs, n = 1347) or NIV (RR, 1.11; 95% CI, 0.88-1.40; P = .37; 2 RCTs, n = 1434). In subgroup of critically ill patients, the HFNC group had a significantly lower reintubation rate compared to the COT group (RR, 0.35; 95% CI, 0.19-0.64; P = .0007; 2 RCTs, n = 632; interaction P = .07 compared to postoperative subgroup). Qualitative analysis suggested that HFNC might be associated with less complications and improved patient's tolerance and comfort. The HFNC might not delay reintubation. Trial sequential analysis on the primary outcome showed that required information size was not reached. CONCLUSION: The evidence suggests that COT may still be the first-line therapy in postoperative patients without acute respiratory failure. However, in critically ill patients, HFNC may be a potential alternative respiratory support to COT and NIV, with the latter often associating with patient intolerance and requiring a monitored setting. Because required information size was not reached, further high-quality studies are required to confirm these results.

Effort to Breathe with Various Spontaneous Breathing Trial Techniques. A Physiologic Meta-analysis.

RATIONALE: Spontaneous breathing trials (SBTs) are designed to simulate conditions after extubation, and it is essential to understand the physiologic impact of different methods. OBJECTIVES: We conducted a systematic review and pooled measures reflecting patient respiratory effort among studies comparing SBT methods in a meta-analysis. METHODS: We searched Medline, Excerpta Medica Database, and Web of Science from inception to January 2016 to identify randomized and nonrandomized clinical trials reporting physiologic measurements of respiratory effort (pressure-time product) or work of breathing during at least two SBT techniques. Secondary outcomes included the rapid shallow breathing index (RSBI), and effort measured before and after extubation. The quality of physiologic measurement and research design was appraised for each study. Outcomes were analyzed using ratio of means. MEASUREMENTS AND MAIN RESULTS: Among 4,138 citations, 16 studies (n = 239) were included. Compared with T-piece, pressure support ventilation significantly reduced work by 30% (ratio of means [RoM], 0.70; 95% confidence interval [CI], 0.57-0.86), effort by 30% (RoM, 0.70; 95% CI, 0.60-0.82), and RSBI by 20% (RoM, 0.80; 95% CI, 0.75-0.86). Continuous positive airway pressure had significantly lower pressure-time product by 18% (RoM, 0.82; 95% CI, 0.68-0.999) compared with T-piece, and reduced RSBI by 16% (RoM, 0.84; 95% CI, 0.74-0.95). Studies comparing SBTs with the postextubation period demonstrated that pressure support induced significantly lower effort and RSBI; T-piece reduced effort, but not the work, compared with postextubation. Work, effort, and RSBI measured while intubated on the ventilator with continuous positive airway pressure of 0 cm H2O were no different than extubation. CONCLUSIONS: Pressure support reduces respiratory effort compared with T-piece. Continuous positive airway pressure of 0 cm H2O and T-piece more accurately reflect the physiologic conditions after extubation.

Use of esophageal balloon pressure-volume curve analysis to determine esophageal wall elastance and calibrate raw esophageal pressure: a bench experiment and clinical study.

BACKGROUND: Accurate measurement of esophageal pressure (Pes) depends on proper filling of the balloon. Esophageal wall elastance (Ees) may also influence the measurement. We examined the estimation of balloon-surrounding elastance in a bench model and investigated a simplified calibrating procedure of Pes in a balloon with relatively small volume. METHODS: The Cooper balloon catheter (geometric volume of 2.8 ml) was used in the present study. The balloon was progressively inflated in different gas-tight glass chambers with different inner volumes. Chamber elastance was measured by the fitting of chamber pressure and balloon volume. Balloon pressure-volume (P-V) curves were obtained, and the slope of the intermediate linear section was defined as the estimated chamber elastance. Balloon volume tests were also performed in 40 patients under controlled ventilation. The slope of the intermediate linear section on the end-expiratory esophageal P-V curve was calculated as the Ees. The balloon volume with the largest Pes tidal swing was defined as the best volume. Pressure generated by the esophageal wall during balloon inflation (Pew) was estimated as the product of Ees and best volume. Because the clinical intermediate linear section enclosed filling volume of 0.6 to 1.4 ml in each of the patient, we simplified the estimation of Ees by only using parameters at these two filling volumes. RESULTS: In the bench experiment, bias (lower and upper limits of agreement) was 0.5 (0.2 to 0.8) cmH2O/ml between the estimated and measured chamber elastance. The intermediate linear section on the clinical and bench P-V curves resembled each other. Median (interquartile range) Ees was 3.3 (2.5-4.1) cmH2O/ml. Clinical best volume was 1.0 (0.8-1.2) ml and ranged from 0.6 to 1.4 ml. Estimated Pew at the best volume was 2.8 (2.5-3.5) cmH2O with a maximum value of 5.2 cmH2O. Compared with the conventional method, bias (lower and upper limits of agreement) of Ees estimated by the simple method was - 0.1 (- 0.7 to 0.6) cmH2O/ml. CONCLUSIONS: The slope of the intermediate linear section on the balloon P-V curve correlated with the balloon-surrounding elastance. The estimation of Ees and calibration of Pes were feasible for a small-volume-balloon. TRIAL REGISTRATION: Identifier NCT02976844 . Retrospectively registered on 29 November 2016.

Active contours driven by edge entropy fitting energy for image segmentation.

Active contour models have been widely used for image segmentation purposes. However, they may fail to delineate objects of interest depicted on images with intensity inhomogeneity. To resolve this issue, a novel image feature, termed as local edge entropy, is proposed in this study to reduce the negative impact of inhomogeneity on image segmentation. An active contour model is developed on the basis of this feature, where an edge entropy fitting (EEF) energy is defined with the combination of a redesigned regularization term. Minimizing the energy in a variational level set formulation can successfully drive the motion of an initial contour curve towards optimal object boundaries. Experiments on a number of test images demonstrate that the proposed model has the capability of handling intensity inhomogeneity with reasonable segmentation accuracy.

Implementing a bedside assessment of respiratory mechanics in patients with acute respiratory distress syndrome.

BACKGROUND: Despite their potential interest for clinical management, measurements of respiratory mechanics in patients with acute respiratory distress syndrome (ARDS) are seldom performed in routine practice. We introduced a systematic assessment of respiratory mechanics in our clinical practice. After the first year of clinical use, we retrospectively assessed whether these measurements had any influence on clinical management and physiological parameters associated with clinical outcomes by comparing their value before and after performing the test. METHODS: The respiratory mechanics assessment constituted a set of bedside measurements to determine passive lung and chest wall mechanics, response to positive end-expiratory pressure, and alveolar derecruitment. It was obtained early after ARDS diagnosis. The results were provided to the clinical team to be used at their own discretion. We compared ventilator settings and physiological variables before and after the test. The physiological endpoints were oxygenation index, dead space, and plateau and driving pressures. RESULTS: Sixty-one consecutive patients with ARDS were enrolled. Esophageal pressure was measured in 53 patients (86.9%). In 41 patients (67.2%), ventilator settings were changed after the measurements, often by reducing positive end-expiratory pressure or by switching pressure-targeted mode to volume-targeted mode. Following changes, the oxygenation index, airway plateau, and driving pressures were significantly improved, whereas the dead-space fraction remained unchanged. The oxygenation index continued to improve in the next 48 h. CONCLUSIONS: Implementing a systematic respiratory mechanics test leads to frequent individual adaptations of ventilator settings and allows improvement in oxygenation indexes and reduction of the risk of overdistention at the same time. TRIAL REGISTRATION: The present study involves data from our ongoing registry for respiratory mechanics (ClinicalTrials.gov identifier: NCT02623192 . Registered 30 July 2015).

A UPLC-MS/MS method for analysis of vancomycin in human cerebrospinal fluid and comparison with the chemiluminescence immunoassay.

Vancomycin (VCM) is clinically used in treating patients with postoperative intracranial infections. The cerebrospinal fluid (CSF) concentration of VCM varies greatly among patients. To guide the dosage regimens, monitoring of VCM in CSF is needed. However a method for analysis of VCM in human CSF is lacking. An ultraperformance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was developed and validated for analysis of VCM in human CSF, and the agreement of UPLC-MS/MS and chemiluminescence immunoassay (CLIA) in the analysis of CSF VCM was evaluated. The ion transitions were m/z 725.5 > 144.1 for VCM and m/z 455.2 > 308.2 for methotrexate (internal standard). The agreement between UPLC-MS/MS and CLIA was evaluated by Bland-Altman plot in 179 samples. The calibration range of the UPLC-MS/MS method was 1-400 mg/L. The inaccuracy and imprecision were -0.69-10.80% and <4.95%. The internal standard normalized recovery and matrix factor were 86.14-99.31 and 85.84-92.07%, respectively. The measurements of CLIA and UPLC-MS/MS were strongly correlated (r > 0.98). The 95% limit of agreement of the ratio of CLIA to UPLC-MS/MS was 61.66-107.40%. Further studies are warranted to confirm the results.

Post-craniotomy intracranial infection in patients with brain tumors: a retrospective analysis of 5723 consecutive patients.

AIM: To determine the risk factors for and the incidence, outcomes, and causative pathogens of post-craniotomy intracranial infection (PCII) in patients with brain tumors. METHODS: A retrospective study was performed of 5723 patients with brain tumors who were surgically treated between January 2012 and December 2013 in Beijing Tiantan Hospital. The patients' demographics, pathohistological diagnoses, surgical procedures, postoperative variables, causative pathogens, and outcomes were evaluated. RESULTS: The overall incidence of PCII was 6.8%, and 82.1% of all cases were diagnosed within two weeks after the craniotomy. Postoperative administration of antibiotics reduced the incidence of PCII. Independent risk factors included clean-contaminated craniotomy, prolonged operation (> 7 h), external cerebrospinal fluid (CSF) drainage/monitoring device placement, and postoperative CSF leakage. Patients ≤ 45 years old were more susceptible to infection. Compared with supratentorial tumors, tumors located in the infratentorial or intraventricular regions were more vulnerable to PCII. Gram-positive bacteria were the most common causative pathogens isolated from the CSF samples, accounting for 82.0% of the PCII cases. CONCLUSIONS: Risk factors for PCII can be identified early in the perioperative period. These findings raise the possibility of improving the clinical outcomes of patients with brain tumors who undergo craniotomy.

CT imaging-based determination and classification of anatomic variations of left gastric vein.

BACKGROUND: Precise determination and classification of left gastric vein (LGV) anatomy are helpful in planning for gastric surgery, in particular, for resection of gastric cancer. However, the anatomy of LGV is highly variable. A systematic classification of its variations is still to be proposed. We aimed to investigate the anatomical variations in LGV using CT imaging and develop a new nomenclature system. METHOD: We reviewed CT images and tracked the course of LGV in 825 adults. The frequencies of common and variable LGV anatomical courses were recorded. Anatomic variations of LGV were proposed and classified into different types mainly based on its courses. The inflow sites of LGV into the portal system were also considered if common hepatic artery (CHA) or splenic artery (SA) could not be used as a frame of reference due to variations. RESULTS: Detailed anatomy and courses of LGV were depicted on CT images. Using CHA and SA as the frames of reference, the routes of LGV were divided into six types (i.e., PreS, RetroS, Mid, PreCH, RetroCH, and Supra). The inflow sites were classified into four types (i.e., PV, SV, PSV, and LPV). The new classification was mainly based on the courses of LGV, which was validated with MDCT in the 805 cases with an identifiable LGV, namely type I, RetroCH, 49.8 % (401/805); type II, PreS, 20.6 % (166/805); type III, Mid, 20.0 % (161/805); type IV, RetroS, 7.3 % (59/805); type V, Supra, 1.5 % (12/805); and type VI, PreCH, 0.7 % (6/805). Type VII, designated to the cases in which SA and CHA could not be used as frames of reference, was not observed in this series. CONCLUSIONS: Detailed depiction of the anatomy and courses of LGV on CT images allowed us to evaluate and develop a new classification and nomenclature system for the anatomical variations of LGV.

Absence of the superior mesenteric artery in an adult and a new classification method for superior-inferior mesenteric arterial variations.

PURPOSE: This paper aims to report the complete absence of the superior mesenteric artery (SMA) in an adult and to propose a new classification method for the superior-inferior mesenteric arterial variations (SIMAV). METHODS: A 69-year-old female was referred for abdominal pain and change of stool habits and characteristics. Multi-detector computed tomography (MDCT) was performed. Based on the CT findings of the patient and previous reports on the abnormalities of the superior-inferior mesenteric arteries, attempt was made to propose a new classification method for SIMAV. RESULTS: MDCT with enhancement revealed complete absence of SMA and compensatory dilation of the inferior mesenteric artery (IMA). Aneurysm of the splenic artery and both inferior phrenic arteries aberrantly arising from the aorta at the same level of the celiac trunk were also noted. Based on our case and literature reports, we were able to propose a new classification method for SIMAV. Without considering the relationship with the celiac arteries, SIMAV can be divided into 4 types. Type I is the normal type or "textbook" type. In type II, SMA is defective and in type III, IMA is defective. In type IV, there is an aberrant middle mesenteric artery (MMA). CONCLUSIONS: Complete absence of SMA is extremely rare. However, awareness of such a variation is of great importance during operations for rectal and sigmoid cancer. In such patients, ligation of the trunk of IMA, which is the only artery for the entire intestine, will lead to disastrous consequence. The new classification method may be helpful in the scientific and systematic description of SIMAV.

A nomogram prediction model based on clinicopathological combined radiological features for metachronous liver metastasis of colorectal cancer.

Objective: To establish a nomogram prediction model (based on clinicopathological and radiological features) for the development of metachronous liver metastasis (MLM) in patients with colorectal cancer (CRC). Methods: This retrospective study included patients with CRC who underwent surgery at Changshu No.1 People's Hospital and the Second Affiliated Hospital of Soochow University between January 2016 and December 2018. The clinical, pathological, and radiological features of each patient were investigated. Risk factors for MLM were identified by univariable and multivariable analyses. The predictive nomogram for MLM development was constructed. The predictive performance of the nomogram was estimated by the receiver operating characteristics curve, calibration curve, and decision curve analysis. Results: This study included 161 patients with CRC [median age: 66 (range, 33-87) years]. Fifty-nine developed MLM after a median of 12 (range, 2-52) months after surgery. The multivariable logistic regression analysis showed that age >66 years (OR=3.471, 95% CI: 1.272-9.473, P=0.015), N2 stage (OR=6.534, 95% CI: 1.456-29.317, P=0.014), positive vascular invasion (OR=2.995, 95% CI: 1.132-7.926, P=0.027), positive tumor deposit (OR=4.451, 95% CI: 1.153-17.179, P=0.030), and linear (OR=6.774, 95% CI: 1.306-35.135, P=0.023) and nodal pericolic fat infiltration patterns (OR=8.762, 95% CI: 1.521-50.457, P=0.015) were independently associated with MLM. These five factors were used to create a nomogram. The area under the receiver operating characteristics curve of the nomogram was 0.866 (95% CI: 0.803-0.914), indicating favorable prediction performance. The calibration curve of the nomogram showed a satisfactory agreement between the predicted and actual probabilities. Conclusions: A nomogram prediction model based on five clinicopathological and radiological features might have favorable prediction performance for MLM in patients who underwent surgery for CRC. Hence, the present study proposes a nomogram that can easily be used to predict MLM after CRC surgery based on readily available features.

Uncertain prediction of deformable image registration on lung CT using multi-category features and supervised learning.

The assessment of deformable registration uncertainty is an important task for the safety and reliability of registration methods in clinical applications. However, it is typically done by a manual and time-consuming procedure. We propose a novel automatic method to predict registration uncertainty based on multi-category features and supervised learning. Three types of features, including deformation field statistical features, deformation field physiologically realistic features, and image similarity features, are introduced and calculated to train the random forest regressor for local registration uncertain prediction. Deformation field statistical features represent the numerical stability of registration optimization, which are correlated to the uncertainty of deformation fields; deformation field physiologically realistic features represent the biomechanical properties of organ motions, which mathematically reflect the physiological reality of deformation; image similarity features reflect the similarity between the warped image and fixed image. The multi-category features comprehensively reflect the registration uncertainty. The strategy of spatial adaptive random perturbations is also introduced to accurately simulate spatial distribution of registration uncertainty, which makes deformation field statistical features more discriminative to the uncertainty of deformation fields. Experiments were conducted on three publicly available thoracic CT image datasets. Seventeen randomly selected image pairs are used to train the random forest model, and 9 image pairs are used to evaluate the prediction model. The quantitative experiments on lung CT images show that the proposed method outperforms the baseline method for uncertain prediction of classical iterative optimization-based registration and deep learning-based registration with different registration qualities. The proposed method achieves good performance for registration uncertain prediction, which has great potential in improving the accuracy of registration uncertain prediction.