Sensory prediction error drives subconscious motor learning outside of the laboratory.

Sensorimotor adaptation is supported by at least two parallel learning systems: an intentionally controlled explicit strategy and an involuntary implicit learning system. Past work focused on constrained reaches or finger movements in laboratory environments has shown subconscious learning systems to be driven in part by sensory prediction error (SPE), i.e., the mismatch between the realized and expected outcome of an action. We designed a ball rolling task to explore whether SPEs can drive implicit motor adaptation during complex whole body movements that impart physical motion on external objects. After applying a visual shift, participants rapidly adapted their rolling angles to reduce the error between the ball and the target. We removed all visual feedback and told participants to aim their throw directly toward the primary target, revealing an unintentional 5.06° implicit adjustment to reach angles that decayed over time. To determine whether this implicit adaptation was driven by SPE, we gave participants a second aiming target that would "solve" the visual shift, as in the study by Mazzoni and Krakauer (Mazzoni P, Krakauer JW. J Neurosci 26: 3642-3645, 2006). Remarkably, after rapidly reducing ball-rolling error to zero (due to enhancements in strategic aiming), the additional aiming target caused rolling angles to deviate beyond the primary target by 3.15°. This involuntary overcompensation, which worsened task performance, is a hallmark of SPE-driven implicit learning. These results show that SPE-driven implicit processes, previously observed within simplified finger or planar reaching movements, actively contribute to motor adaptation in more complex naturalistic skill-based tasks.NEW & NOTEWORTHY Implicit and explicit learning systems have been detected using simple, constrained movements inside the laboratory. How these systems impact movements during complex whole body, skill-based tasks has not been established. Here, we demonstrate that sensory prediction errors significantly impact how a person updates their movements, replicating findings from the laboratory in an unconstrained ball-rolling task. This real-world validation is an important step toward explaining how subconscious learning helps humans execute common motor skills in dynamic environments.

Adaptive control of movement deceleration during saccades.

As you read this text, your eyes make saccades that guide your fovea from one word to the next. Accuracy of these movements require the brain to monitor and learn from visual errors. A current model suggests that learning is supported by two different adaptive processes, one fast (high error sensitivity, low retention), and the other slow (low error sensitivity, high retention). Here, we searched for signatures of these hypothesized processes and found that following experience of a visual error, there was an adaptive change in the motor commands of the subsequent saccade. Surprisingly, this adaptation was not uniformly expressed throughout the movement. Rather, after experience of a single error, the adaptive response in the subsequent trial was limited to the deceleration period. After repeated exposure to the same error, the acceleration period commands also adapted, and exhibited resistance to forgetting during set-breaks. In contrast, the deceleration period commands adapted more rapidly, but suffered from poor retention during these same breaks. State-space models suggested that acceleration and deceleration periods were supported by a shared adaptive state which re-aimed the saccade, as well as two separate processes which resembled a two-state model: one that learned slowly and contributed primarily via acceleration period commands, and another that learned rapidly but contributed primarily via deceleration period commands.

The Origins of Anterograde Interference in Visuomotor Adaptation.

Anterograde interference refers to the negative impact of prior learning on the propensity for future learning. There is currently no consensus on whether this phenomenon is transient or long lasting, with studies pointing to an effect in the time scale of hours to days. These inconsistencies might be caused by the method employed to quantify performance, which often confounds changes in learning rate and retention. Here, we aimed to unveil the time course of anterograde interference by tracking its impact on visuomotor adaptation at different intervals throughout a 24-h period. Our empirical and model-based approaches allowed us to measure the capacity for new learning separately from the influence of a previous memory. In agreement with previous reports, we found that prior learning persistently impaired the initial level of performance upon revisiting the task. However, despite this strong initial bias, learning capacity was impaired only when conflicting information was learned up to 1 h apart, recovering thereafter with passage of time. These findings suggest that when adapting to conflicting perturbations, impairments in performance are driven by two distinct mechanisms: a long-lasting bias that acts as a prior and hinders initial performance and a short-lasting anterograde interference that originates from a reduction in error sensitivity.

Estimating properties of the fast and slow adaptive processes during sensorimotor adaptation.

Experience of a prediction error recruits multiple motor learning processes, some that learn strongly from error but have weak retention and some that learn weakly from error but exhibit strong retention. These processes are not generally observable but are inferred from their collective influence on behavior. Is there a robust way to uncover the hidden processes? A standard approach is to consider a state space model where the hidden states change following experience of error and then fit the model to the measured data by minimizing the squared error between measurement and model prediction. We found that this least-squares algorithm (LMSE) often yielded unrealistic predictions about the hidden states, possibly because of its neglect of the stochastic nature of error-based learning. We found that behavioral data during adaptation was better explained by a system in which both error-based learning and movement production were stochastic processes. To uncover the hidden states of learning, we developed a generalized expectation maximization (EM) algorithm. In simulation, we found that although LMSE tracked the measured data marginally better than EM, EM was far more accurate in unmasking the time courses and properties of the hidden states of learning. In a power analysis designed to measure the effect of an intervention on sensorimotor learning, EM significantly reduced the number of subjects that were required for effective hypothesis testing. In summary, we developed a new approach for analysis of data in sensorimotor experiments. The new algorithm improved the ability to uncover the multiple processes that contribute to learning from error. NEW & NOTEWORTHY Motor learning is supported by multiple adaptive processes, each with distinct error sensitivity and forgetting rates. We developed a generalized expectation maximization algorithm that uncovers these hidden processes in the context of modern sensorimotor learning experiments that include error-clamp trials and set breaks. The resulting toolbox may improve the ability to identify the properties of these hidden processes and reduce the number of subjects needed to test the effectiveness of interventions on sensorimotor learning.

The Neural Feedback Response to Error As a Teaching Signal for the Motor Learning System.

UNLABELLED: When we experience an error during a movement, we update our motor commands to partially correct for this error on the next trial. How does experience of error produce the improvement in the subsequent motor commands? During the course of an erroneous reaching movement, proprioceptive and visual sensory pathways not only sense the error, but also engage feedback mechanisms, resulting in corrective motor responses that continue until the hand arrives at its goal. One possibility is that this feedback response is co-opted by the learning system and used as a template to improve performance on the next attempt. Here we used electromyography (EMG) to compare neural correlates of learning and feedback to test the hypothesis that the feedback response to error acts as a template for learning. We designed a task in which mixtures of error-clamp and force-field perturbation trials were used to deconstruct EMG time courses into error-feedback and learning components. We observed that the error-feedback response was composed of excitation of some muscles, and inhibition of others, producing a complex activation/deactivation pattern during the reach. Despite this complexity, across muscles the learning response was consistently a scaled version of the error-feedback response, but shifted 125 ms earlier in time. Across people, individuals who produced a greater feedback response to error, also learned more from error. This suggests that the feedback response to error serves as a teaching signal for the brain. Individuals who learn faster have a better teacher in their feedback control system. SIGNIFICANCE STATEMENT: Our sensory organs transduce errors in behavior. To improve performance, we must generate better motor commands. How does the nervous system transform an error in sensory coordinates into better motor commands in muscle coordinates? Here we show that when an error occurs during a movement, the reflexes transform the sensory representation of error into motor commands. To learn from error, the nervous system scales this feedback response and then shifts it earlier in time, adding it to the previously generated motor commands. This addition serves as an update to the motor commands, constituting the learning signal. Therefore, by providing a coordinate transformation, the feedback system generates a template for learning from error.

Classification of Indeterminate Melanocytic Lesions by MicroRNA Profiling.

PURPOSE: Identification of indeterminate melanocytic skin lesions capable of neoplastic progression is suboptimal and may potentially result in unnecessary morbidity from surgery. MicroRNAs (miRs) may be useful in classifying indeterminate Spitz tumors as having high or low risk for malignant behavior. METHODS: RNA was extracted from paraffin-embedded tissues of benign nevi, benign Spitz tumors, indeterminate Spitz tumors, and Spitzoid melanomas in adults (n = 62) and children (n = 28). The expression profile of 12 miRs in adults (6 miRs in children) was analyzed by real-time polymerase chain reaction. RESULTS: Benign Spitz lesions were characterized by decreased expression of miR-125b and miR-211, and upregulation of miR-22, compared with benign nevi (p < 0.05). A comparison of Spitzoid melanomas to benign nevi revealed overexpression of miR-21, miR-150, and miR-155 in the malignant primaries (p < 0.05). In adults, Spitzoid melanomas exhibited upregulation of miR-21, miR-150, and miR-155 compared with indeterminate Spitz lesions. Indeterminate Spitz lesions with low-risk pathologic features had lower miR-21 and miR-155 expression compared with Spitzoid melanoma tumors in adults (p < 0.05), while pathologic high-risk indeterminate Spitz lesions had increased levels of miR-200c expression compared with low-risk indeterminate lesions (p < 0.05). Pediatric Spitzoid melanomas exhibited increased miR-21 expression compared with indeterminate Spitz lesions (p < 0.05). Moreover, miR-155 expression was increased in indeterminate lesions with mitotic counts >1 and depth of invasion >1 mm, suggesting miR-155 expression is associated with histological characteristics. CONCLUSIONS: miR expression profiles can be measured in indeterminate Spitz tumors and correlate with markers of malignant potential.

An indeterminate nodule in the cirrhotic liver discovered by surveillance imaging is a prelude to malignancy.

BACKGROUND: Surveillance imaging often shows indeterminate lesions in the cirrhotic liver, which may represent early hepatocellular carcinoma (HCC), dysplastic or regenerative nodules, or vascular shunts. The risk of HCC after identification of an indeterminate nodule is not well described. METHODS: We identified 252 patients with cirrhosis and at least one indeterminate nodule discovered on surveillance imaging over a 4-year period. The incidence of HCC development within 2 years of nodule identification was measured along with baseline risk factors associated with developing HCC. RESULTS: The incidence of HCC in this population was 21% (53 of 252), and risk factors associated with HCC included chronic viral hepatitis, male gender, and low platelet count. The median time from identification of an indeterminate nodule to diagnosis of HCC was 2.7 months. Patients with indeterminate nodules who developed HCC were more likely have to have an indeterminate nodule with arterial enhancement. CONCLUSIONS: The 2-year incidence of HCC in the setting of cirrhosis and an indeterminate nodule discovered by surveillance imaging may be as high as one in five persons. Early follow-up imaging, biopsy, or empiric treatment should be considered for those at higher risk. Further, this population is well suited for early detection biomarker and chemoprevention studies.

A software tool for at-home measurement of sensorimotor adaptation.

Sensorimotor adaptation is traditionally studied in well-controlled laboratory settings with specialized equipment. However, recent public health concerns such as the COVID-19 pandemic, as well as a desire to recruit a more diverse study population, have led the motor control community to consider at-home study designs. At-home motor control experiments are still rare because of the requirement to write software that can be easily used by anyone on any platform. To this end, we developed software that runs locally on a personal computer. The software provides audiovisual instructions and measures the ability of the subject to control the cursor in the context of visuomotor perturbations. We tested the software on a group of at-home participants and asked whether the adaptation principles inferred from in-lab measurements were reproducible in the at-home setting. For example, we manipulated the perturbations to test whether there were changes in adaptation rates (savings and interference), whether adaptation was associated with multiple timescales of memory (spontaneous recovery), and whether we could selectively suppress subconscious learning (delayed feedback, perturbation variability) or explicit strategies (limited reaction time). We found remarkable similarity between in-lab and at-home behaviors across these experimental conditions. Thus, we developed a software tool that can be used by research teams with little or no programming experience to study mechanisms of adaptation in an at-home setting.

Transverse sinus thrombosis after internal jugular vein ligation.

BACKGROUND: Cerebral vein and dural sinus thrombosis is a rare condition with a wide range of causes and a highly variable presentation. It can lead to significant morbidity, but scant literature is available describing diagnosis and treatment when this occurs after ligation of the internal jugular vein. OBJECTIVES: To discuss potential risk factors for cerebral vein and dural sinus thrombosis after ligation of the internal jugular vein, and present current options for diagnosis and treatment. CASE REPORT: A 23-year-old male construction worker was brought to the Emergency Department by Emergency Medical Services after sustaining a severe neck laceration from a hand-held grinder. He was treated with ligation of the left internal jugular vein, but subsequently developed severe headaches and symptoms of increased intracranial pressure. A magnetic resonance venogram of the head revealed a left transverse sinus thrombosis requiring treatment with anticoagulation. The placement of a lumboperitoneal shunt was ultimately needed for relief of his symptoms. CONCLUSIONS: Early diagnosis and aggressive therapeutic interventions are critical to prevent further morbidity in patients who develop cerebral vein and dural sinus thrombosis after ligation of the internal jugular vein.

Competition between parallel sensorimotor learning systems.

Sensorimotor learning is supported by at least two parallel systems: a strategic process that benefits from explicit knowledge and an implicit process that adapts subconsciously. How do these systems interact? Does one system's contributions suppress the other, or do they operate independently? Here, we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system's response siphons away resources that are needed for implicit adaptation, thus reducing its learning. As a result, steady-state implicit learning can vary across experimental conditions, due to changes in strategy. Furthermore, strategies can mask changes in implicit learning properties, such as its error sensitivity. These ideas, however, become more complex in conditions where subjects adapt using multiple visual landmarks, a situation which introduces learning from sensory prediction errors in addition to target errors. These two types of implicit errors can oppose each other, leading to another type of competition. Thus, during sensorimotor adaptation, implicit and explicit learning systems compete for a common resource: error.

A clinically applicable porcine model of septic and ischemia/reperfusion-induced shock and multiple organ injury.

BACKGROUND: Although many sepsis treatments have shown efficacy in acute animal models, at present only activated protein C is effective in humans. The likely reason for this discrepancy is that most of the animal models used for preclinical testing do not accurately replicate the complex pathogenesis of human sepsis. Our objective in this study was to develop a clinically applicable model of severe sepsis and gut ischemia/reperfusion (I/R) that would cause multiple organ injury over a period of 48 h. MATERIALS AND METHODS: Anesthetized, instrumented, and ventilated pigs were subjected to a "two-hit" injury by placement of a fecal clot through a laparotomy and by clamping the superior mesenteric artery (SMA) for 30 min. The animals were monitored for 48 h. Wide spectrum antibiotics and intravenous fluids were given to maintain hemodynamic status. FiO(2) was increased in response to oxygen desaturation. Twelve hours following injury, a drain was placed in the laparotomy wound. Extensive hemodynamic, lung, kidney, liver, and renal function measurements and serial measurements of arterial and mixed venous blood gases were made. Bladder pressure was measured as a surrogate for intra-peritoneal pressure to identify the development of the abdominal compartment syndrome (ACS). Plasma and peritoneal ascites cytokine concentration were measured at regular intervals. Tissues were harvested and fixed at necropsy for detailed morphometric analysis. RESULTS: Polymicrobial sepsis developed in all animals. There was a progressive deterioration of organ function over the 48 h. The lung, kidney, liver, and intestine all demonstrated clinical and histopathologic injury. Acute lung injury (ALI) and ACS developed by consensus definitions. Increases in multiple cytokines in serum and peritoneal fluid paralleled the dysfunction found in major organs. CONCLUSION: This animal model of Sepsis+I/R replicates the systemic inflammation and dysfunction of the major organ systems that is typically seen in human sepsis and trauma patients. The model should be useful in deciphering the complex pathophysiology of septic shock as it transitions to end-organ injury thus allowing sophisticated preclinical studies on potential treatments.

Comparison of "open lung" modes with low tidal volumes in a porcine lung injury model.

BACKGROUND: Ventilator strategies that maintain an "open lung" have shown promise in treating hypoxemic patients. We compared three "open lung" strategies with standard of care low tidal volume ventilation and hypothesized that each would diminish physiologic and histopathologic evidence of ventilator induced lung injury (VILI). MATERIALS AND METHODS: Acute lung injury (ALI) was induced in 22 pigs via 5% Tween and 30-min of injurious ventilation. Animals were separated into four groups: (1) low tidal volume ventilation (LowVt -6 mL/kg); (2) high-frequency oscillatory ventilation (HFOV); (3) airway pressure release ventilation (APRV); or (4) recruitment and decremental positive-end expiratory pressure (PEEP) titration (RM+OP) and followed for 6 h. Lung and hemodynamic function was assessed on the half-hour. Bronchoalveolar lavage fluid (BALF) was analyzed for cytokines. Lung tissue was harvested for histologic analysis. RESULTS: APRV and HFOV increased PaO(2)/FiO(2) ratio and improved ventilation. APRV reduced BALF TNF-α and IL-8. HFOV caused an increase in airway hemorrhage. RM+OP decreased SvO(2), increased PaCO(2), with increased inflammation of lung tissue. CONCLUSION: None of the "open lung" techniques were definitively superior to LowVt with respect to VILI; however, APRV oxygenated and ventilated more effectively and reduced cytokine concentration compared with LowVt with nearly indistinguishable histopathology. These data suggest that APRV may be of potential benefit to critically ill patients but other "open lung" strategies may exacerbate injury.

An implicit memory of errors limits human sensorimotor adaptation.

During extended motor adaptation, learning appears to saturate despite persistence of residual errors. This adaptation limit is not fixed but varies with perturbation variance; when variance is high, residual errors become larger. These changes in total adaptation could relate to either implicit or explicit learning systems. Here, we found that when adaptation relied solely on the explicit system, residual errors disappeared and learning was unaltered by perturbation variability. In contrast, when learning depended entirely, or in part, on implicit learning, residual errors reappeared. Total implicit adaptation decreased in the high-variance environment due to changes in error sensitivity, not in forgetting. These observations suggest a model in which the implicit system becomes more sensitive to errors when they occur in a consistent direction. Thus, residual errors in motor adaptation are at least in part caused by an implicit learning system that modulates its error sensitivity in response to the consistency of past errors.

Titration of mean airway pressure and FiO2 during high frequency oscillatory ventilation in a porcine model of acute lung injury.

BACKGROUND: High frequency oscillatory ventilation (HFOV) is frequently utilized for patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). However, precise criteria to titrate mean airway pressure (mPaw) and FiO(2) as the patient's condition improves are lacking. We hypothesized that reducing mPaw and FiO(2) too quickly after reaching target arterial oxygen saturation levels would promote ventilator induced lung injury (VILI). MATERIALS AND METHODS: ALI was induced by instilling 3% Tween 20. Pigs were placed supine and received 30 min of nonprotective ventilation. Pigs were separated into two groups: HFOV constant (HFOVC, n = 3) = constant mPaw and FiO(2) for the duration; HFOV titrated (HFOVT, n = 4) = FiO(2) and/or mPaw were reduced every 30 min if the oxygen saturation remained between 88%-95%. Hemodynamic and pulmonary measurements were made at baseline, after lung injury, and every 30 min during the 6-h study. Lung histopathology was determined by quantifying alveolar hyperdistension, fibrin, congestion, atelectasis, and polymorphonuclear leukocyte (PMN) infiltration. RESULTS: Oxygenation was significantly lower in the HFOVT group compared to the HFOVC group after 6 h. Lung histopathology was significantly increased in the HFOVT group in the following categories: PMN infiltration, alveolar hyperdistension, congestion, and fibrin deposition. CONCLUSIONS: Rapid reduction of mPaw and FiO(2) in our ALI model significantly reduced oxygenation, but, more importantly, caused VILI as evidenced by increased lung inflammation and alveolar hyperdistension. Specific criteria for titration of mPaw and inspired oxygen are needed to maximize the lung protective effects of HFOV while maintaining adequate gas exchange.

Loss of airway pressure during HFOV results in an extended loss of oxygenation: a retrospective animal study.

BACKGROUND: Patients with acute respiratory distress syndrome (ARDS) are often ventilated with high airway pressure. Brief loss of airway pressure may lead to an extended loss of oxygenation. While using high frequency oscillatory ventilation (HFOV) in a porcine acute lung injury model, two animals became disconnected from the ventilator with subsequent loss of airway pressure. We compared the two disconnected animals to the two animals that remained connected to determine causes for the extended reduction in oxygenation. METHODS: ARDS was induced using 5% Tween. Thirty min of nonprotective ventilation (NPV) followed before placing the pigs on HFOV. Measurements were made at baseline, after lung injury, and every 30min during the 6-h study. Disconnections were treated by hand-ventilation and a recruitment maneuver before being placed back on HFOV. The lungs were histologically analyzed and wet/dry weights were measured to determine lung edema. RESULTS: Hemodynamics and lung function were similar in all pigs at baseline, after injury, and following NPV. The animals that remained connected to the oscillator showed a continued improvement in PaO(2)/FiO(2) (P/F) ratio throughout the study. The animals that experienced the disconnection had a significant loss of lung function that never recovered. The disconnect animals had more diffuse alveolar disease on histologic analysis. CONCLUSIONS: A significant fall in lung function results following disconnection from HFOV, which remains depressed for a substantial period of time despite efforts to reopen the lung. Dispersion of edema fluid is a possible mechanism for the protracted loss of lung function.

Postural control of arm and fingers through integration of movement commands.

Every movement ends in a period of stillness. Current models assume that commands that hold the limb at a target location do not depend on the commands that moved the limb to that location. Here, we report a surprising relationship between movement and posture in primates: on a within-trial basis, the commands that hold the arm and finger at a target location depend on the mathematical integration of the commands that moved the limb to that location. Following damage to the corticospinal tract, both the move and hold period commands become more variable. However, the hold period commands retain their dependence on the integral of the move period commands. Thus, our data suggest that the postural controller possesses a feedforward module that uses move commands to calculate a component of hold commands. This computation may arise within an unknown subcortical system that integrates cortical commands to stabilize limb posture.

Moving an arm requires the brain to send electrical signals to the arm's muscles, causing them to contract. Neuroscientists call these types of brain signals "move signals". The brain also sends so-called hold signals, which hold the arm still in a desired position. Part of the brain known as the primary motor cortex helps to calculate the move signals for the arm, but it was unclear how the brain produces the corresponding hold signals. Fortunately, the fact that the brain moves other things besides arms may help answer this question. Previous research has shown, for example, that a brain area called the "neural integrator" calculates the hold signals needed to hold the eye in a specific position. The neural integrator does this by using basic principles of physics, and details of the speed and duration of the eye's movements. Now, Albert et al. show a similar mechanism appears to control hold signals for arm movements. In one set of experiments, muscle activity was measured as monkeys moved their arms or fingers to different target positions. In other experiments, human volunteers held a robot arm, and Albert et al. measured the forces they produced while reaching and holding still. Both the human and monkey experiments revealed a relationship between move signals and hold signals. Like for eye movements, hold signals for the arm could be calculated from the move signals. In further experiments with stroke patients where the brain had been damaged, the move signals were found to be deteriorated, but the way hold signals were calculated stayed the same. This suggests that there is an unknown structure within the brain that calculates hold signals based on move signals. Investigating how the brain holds the arm still may help scientists understand why some neurological conditions like stroke or dystonia cause unwanted movements or unusual postures. This might also lead scientists to develop new ways to treat these conditions.

The role of time and pressure on alveolar recruitment.

Inappropriate mechanical ventilation in patients with acute respiratory distress syndrome can lead to ventilator-induced lung injury (VILI) and increase the morbidity and mortality. Reopening collapsed lung units may significantly reduce VILI, but the mechanisms governing lung recruitment are unclear. We thus investigated the dynamics of lung recruitment at the alveolar level. Rats (n = 6) were anesthetized and mechanically ventilated. The lungs were then lavaged with saline to simulate acute respiratory distress syndrome (ARDS). A left thoracotomy was performed, and an in vivo microscope was placed on the lung surface. The lung was recruited to three recruitment pressures (RP) of 20, 30, or 40 cmH(2)O for 40 s while subpleural alveoli were continuously filmed. Following measurement of microscopic alveolar recruitment, the lungs were excised, and macroscopic gross lung recruitment was digitally filmed. Recruitment was quantified by computer image analysis, and data were interpreted using a mathematical model. The majority of alveolar recruitment (78.3 +/- 7.4 and 84.6 +/- 5.1%) occurred in the first 2 s (T2) following application of RP 30 and 40, respectively. Only 51.9 +/- 5.4% of the microscopic field was recruited by T2 with RP 20. There was limited recruitment from T2 to T40 at all RPs. The majority of gross lung recruitment also occurred by T2 with gradual recruitment to T40. The data were accurately predicted by a mathematical model incorporating the effects of both pressure and time. Alveolar recruitment is determined by the magnitude of recruiting pressure and length of time pressure is applied, a concept supported by our mathematical model. Such a temporal dependence of alveolar recruitment needs to be considered when recruitment maneuvers for clinical application are designed.

An evaluation of multidetector computed tomography in detecting pancreatic injury: results of a multicenter AAST study.

BACKGROUND: Efforts to determine the suitability of low-grade pancreatic injuries for nonoperative management have been hindered by the inaccuracy of older computed tomography (CT) technology for detecting pancreatic injury (PI). This retrospective, multicenter American Association for the Surgery of Trauma-sponsored trial examined the sensitivity of newer 16- and 64-multidetector CT (MDCT) for detecting PI, and sensitivity/specificity for the identification of pancreatic ductal injury (PDI). METHODS: Patients who received a preoperative 16- or 64-MDCT followed by laparotomy with a documented PI were enrolled. Preoperative MDCT scans were classified as indicating the presence (+) or absence (-) of PI and PDI. Operative notes were reviewed and all patients were confirmed as PI (+), and then classified as PDI (+) or (-). As all patients had PI, an analysis of PI specificity was not possible. PI patients formed the pool for further PDI analysis. As sensitivity and specificity data were available for PDI, multivariate logistic regression was performed for PDI patients using the presence or absence of agreement between CT and operative note findings as an independent variable. Covariates were age, gender, Injury Severity Score, mechanism of injury, presence of oral contrast, presence of other abdominal injuries, performance of the scan as part of a dedicated pancreas protocol, and image thickness < or =3 mm or > or =5 mm. RESULTS: Twenty centers enrolled 206 PI patients, including 71 PDI (+) patients. Intravenous contrast was used in 203 studies; 69 studies used presence of oral contrast. Eight-nine percent were blunt mechanisms, and 96% were able to have their duct status operatively classified as PDI (+) or (-). The sensitivity of 16-MDCT for all PI was 60.1%, whereas 64-MDCT was 47.2%. For PDI, the sensitivities of 16- and 64-MDCT were 54.0% and 52.4%, respectively, with specificities of 94.8% for 16-MDCT scanners and 90.3% for 64-MDCT scanners. Logistic regression showed that no covariates were associated with an increased likelihood of detecting PDI for either 16- or 64-MDCT scanners. The area under the curve was 0.66 for the 16-MDCT PDI analysis and 0.77 for the 64-MDCT PDI analysis. CONCLUSION: Sixteen and 64-MDCT have low sensitivity for detecting PI and PDI, while exhibiting a high specificity for PDI. Their use as decision-making tools for the nonoperative management of PI are, therefore, limited.

Alveolar instability caused by mechanical ventilation initially damages the nondependent normal lung.

BACKGROUND: Septic shock is often associated with acute respiratory distress syndrome, a serious clinical problem exacerbated by improper mechanical ventilation. Ventilator-induced lung injury (VILI) can exacerbate the lung injury caused by acute respiratory distress syndrome, significantly increasing the morbidity and mortality. In this study, we asked the following questions: what is the effect of the lung position (dependent lung versus nondependent lung) on the rate at which VILI occurs in the normal lung? Will positive end-expiratory pressure (PEEP) slow the progression of lung injury in either the dependent lung or the nondependent lung? MATERIALS AND METHODS: Sprague-Dawley rats (n = 19) were placed on mechanical ventilation, and the subpleural alveolar mechanics were measured with an in vivo microscope. Animals were placed in the lateral decubitus position, left lung up to measure nondependent alveolar mechanics and left lung down to film dependent alveolar mechanics. Animals were ventilated with a high peak inspiratory pressure of 45 cmH2O and either a low PEEP of 3 cmH2O or a high PEEP of 10 cmH2O for 90 minutes. Animals were separated into four groups based on the lung position and the amount of PEEP: Group I, dependent + low PEEP (n = 5); Group II, nondependent + low PEEP (n = 4); Group III, dependent + high PEEP (n = 5); and Group IV, nondependent + high PEEP (n = 5). Hemodynamic and lung function parameters were recorded concomitant with the filming of alveolar mechanics. Histological assessment was performed at necropsy to determine the presence of lung edema. RESULTS: VILI occurred earliest (60 min) in Group II. Alveolar instability eventually developed in Groups I and II at 75 minutes. Alveoli in both the high PEEP groups were stable for the entire experiment. There were no significant differences in arterial PO2 or in the degree of edema measured histologically among experimental groups. CONCLUSION: This open-chest animal model demonstrates that the position of the normal lung (dependent or nondependent) plays a role on the rate of VILI.