Implicit Motor Sequence Learning in People with Mild to Moderate Parkinson's Disease: Behavior and Related Brain Function.

BACKGROUND: Deficits in motor learning could be an important explanation for the balance and gait impairments characteristic of people with Parkinson's disease (PD). Empirical studies often report that so-called implicit motor sequence learning is impaired in people with PD, but the results are inconclusive. Altered brain activity during implicit motor sequence learning has also been reported for people with PD in comparison to healthy individuals. OBJECTIVE: To investigate implicit motor sequence learning and associated neural correlates in individuals with mild to moderate PD. METHODS: Fifty-seven participants with PD and 34 healthy participants, all ≥60 years of age, performed the serial reaction time task (SRTT) during the acquisition of functional magnetic resonance imaging (fMRI) data. We analyzed the SRTT as a measure of implicit motor sequence learning in two complementary ways. We analyzed the task-induced fMRI data within regions of interest (ROIs) as well as functional connectivity between ROIs. RESULTS: We found a significant group difference in SRTT performance indicating that the participants with PD had a somewhat lower level of implicit motor sequence learning than the healthy participants. Exploratory analyses suggested that impairments in implicit motor sequence learning for people with PD might be due to a lower learning rate. We did not find any significant group differences in the fMRI data. CONCLUSION: Our exploratory finding of a lower implicit motor learning rate in PD could have important implications for how people with PD should practice new motor tasks and physical exercise. Future studies need to confirm this finding with hypothesis-driven analyses.

TemplateFlow: FAIR-sharing of multi-scale, multi-species brain models.

Reference anatomies of the brain ('templates') and corresponding atlases are the foundation for reporting standardized neuroimaging results. Currently, there is no registry of templates and atlases; therefore, the redistribution of these resources occurs either bundled within existing software or in ad hoc ways such as downloads from institutional sites and general-purpose data repositories. We introduce TemplateFlow as a publicly available framework for human and non-human brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to share their resources under FAIR-findable, accessible, interoperable, and reusable-principles. TemplateFlow enables multifaceted insights into brains across species, and supports multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species.

Placebo Response and Media Attention in Randomized Clinical Trials Assessing Cannabis-Based Therapies for Pain: A Systematic Review and Meta-analysis.

Importance: Persistent pain is a common and disabling health problem that is often difficult to treat. There is an increasing interest in medicinal cannabis for treatment of persistent pain; however, the limited superiority of cannabinoids over placebo in clinical trials suggests that positive expectations may contribute to the improvements. Objective: To evaluate the size of placebo responses in randomized clinical trials in which cannabinoids were compared with placebo in the treatment of pain and to correlate these responses to objective estimates of media attention. Data Sources: A systematic literature search was conducted within the MEDLINE and Embase databases. Studies published until September 2021 were considered. Study Selection: Cannabinoid studies with a double-blind, placebo-controlled design with participants 18 years or older with clinical pain of any duration were included. Studies were excluded if they treated individuals with HIV/AIDS or severe skin disorders. Data Extraction and Synthesis: The study followed the Preferred Reporting Items for Systematic Review and Meta-analyses reporting guideline. Data were extracted by independent reviewers. Quality assessment was performed using the Risk of Bias 2 tool. Attention and dissemination metrics for each trial were extracted from Altmetric and Crossref. Data were pooled and analyzed using a random-effects statistical model. Main Outcomes and Measures: Change in pain intensity from before to after treatment, measured as bias-corrected standardized mean difference (Hedges g). Results: Twenty studies, including 1459 individuals (mean [SD] age, 51 [7] years; age range, 33-62 years; 815 female [56%]), were included. Pain intensity was associated with a significant reduction in response to placebo, with a moderate to large effect size (mean [SE] Hedges g, 0.64 [0.13]; P < .001). Trials with low risk of bias had greater placebo responses (q1 = 5.47; I2 = 87.08; P = .02). The amount of media attention and dissemination linked to each trial was proportionally high, with a strong positive bias, but was not associated with the clinical outcomes. Conclusions and Relevance: Placebo contributes significantly to pain reduction seen in cannabinoid clinical trials. The positive media attention and wide dissemination may uphold high expectations and shape placebo responses in future trials, which has the potential to affect the outcome of clinical trials, regulatory decisions, clinical practice, and ultimately patient access to cannabinoids for pain relief.

Multiple spatial scale mapping of time-resolved brain network reconfiguration during evoked pain in patients with rheumatoid arthritis.

Functional brain networks and the perception of pain can fluctuate over time. However, how the time-dependent reconfiguration of functional brain networks contributes to chronic pain remains largely unexplained. Here, we explored time-varying changes in brain network integration and segregation during pain over a disease-affected area (joint) compared to a neutral site (thumbnail) in 28 patients with rheumatoid arthritis (RA) in comparison with 22 healthy controls (HC). During functional magnetic resonance imaging, all subjects received individually calibrated pain pressures corresponding to visual analog scale 50 mm at joint and thumbnail. We implemented a novel approach to track changes of task-based network connectivity over time. Within this framework, we quantified measures of integration (participation coefficient, PC) and segregation (within-module degree z-score). Using these network measures at multiple spatial scales, both at the level of single nodes (brain regions) and communities (clusters of nodes), we found that PC at the community level was generally higher in RA patients compared to HC during and after painful pressure over the inflamed joint and corresponding site in HC. This shows that all brain communities integrate more in RA patients than in HC for time points following painful stimulation to a disease-relevant body site. However, the elevated community-related integration seen in patients appeared to not pertain uniquely to painful stimulation at the inflamed joint, but also at the neutral thumbnail, as integration and segregation at the community level did not differ across body sites in patients. Moreover, there was no specific nodal contribution to brain network integration or segregation. Altogether, our findings indicate widespread and persistent changes in network interaction in RA patients compared to HC in response to painful stimulation.

Behavioural and neuroplastic effects of a double-blind randomised controlled balance exercise trial in people with Parkinson's disease.

Balance dysfunction is a disabling symptom in people with Parkinson's disease (PD). Evidence suggests that exercise can improve balance performance and induce neuroplastic effects. We hypothesised that a 10-week balance intervention (HiBalance) would improve balance, other motor and cognitive symptoms, and alter task-evoked brain activity in people with PD. We performed a double-blind randomised controlled trial (RCT) where 95 participants with PD were randomised to either HiBalance (n = 48) or a control group (n = 47). We found no significant group by time effect on balance performance (b = 0.4 95% CI [-1, 1.9], p = 0.57) or on our secondary outcomes, including the measures of task-evoked brain activity. The findings of this well-powered, double-blind RCT contrast previous studies of the HiBalance programme but are congruent with other double-blind RCTs of physical exercise in PD. The divergent results raise important questions on how to optimise physical exercise interventions for people with PD.Preregistration clinicaltrials.gov: NCT03213873.

Brain network segregation and integration during painful thermal stimulation.

The present study aimed to determine changes in brain network integration/segregation during thermal pain using methods optimized for network connectivity events with high temporal resolution. Participants (n = 33) actively judged whether thermal stimuli applied to the volar forearm were painful or not and then rated the warmth/pain intensity after each trial. We show that the temporal evolution of integration/segregation within trials correlates with the subjective ratings of pain. Specifically, the brain shifts from a segregated state to an integrated state when processing painful stimuli. The association with subjective pain ratings occurred at different time points for all networks. However, the degree of association between ratings and integration/segregation vanished for several brain networks when time-varying functional connectivity was measured at lower temporal resolution. Moreover, the increased integration associated with pain is explained to some degree by relative increases in between-network connectivity. Our results highlight the importance of investigating the relationship between pain and brain network connectivity at a single time point scale, since commonly used temporal aggregations of connectivity data may result in that fine-scale changes in network connectivity may go unnoticed. The interplay between integration/segregation reflects shifting demands of information processing between brain networks and this adaptation occurs both for cognitive tasks and nociceptive processing.

Genetic Influence on Nociceptive Processing in the Human Brain-A Twin Study.

Nociceptive processing in the human brain is complex and involves several brain structures and varies across individuals. Determining the structures that contribute to interindividual differences in nociceptive processing is likely to improve our understanding of why some individuals feel more pain than others. Here, we found specific parts of the cerebral response to nociception that are under genetic influence by employing a classic twin-design. We found genetic influences on nociceptive processing in the midcingulate cortex and bilateral posterior insula. In addition to brain activations, we found genetic contributions to large-scale functional connectivity (FC) during nociceptive processing. We conclude that additive genetics influence specific brain regions involved in nociceptive processing. The genetic influence on FC during nociceptive processing is not limited to core nociceptive brain regions, such as the dorsal posterior insula and somatosensory areas, but also involves cognitive and affective brain circuitry. These findings improve our understanding of human pain perception and increases chances to find new treatments for clinical pain.

Genetic risk for bipolar disorder and schizophrenia predicts structure and function of the ventromedial prefrontal cortex.

BACKGROUND: Bipolar disorder is highly heritable and polygenic. The polygenic risk for bipolar disorder overlaps with that of schizophrenia, and polygenic scores are normally distributed in the population. Bipolar disorder has been associated with structural brain abnormalities, but it is unknown how these are linked to genetic risk factors for psychotic disorders. METHODS: We tested whether polygenic risk scores for bipolar disorder and schizophrenia predict structural brain alterations in 98 patients with bipolar disorder and 81 healthy controls. We derived brain cortical thickness, surface area and volume from structural MRI scans. In post-hoc analyses, we correlated polygenic risk with functional hub strength, derived from resting-state functional MRI and brain connectomics. RESULTS: Higher polygenic risk scores for both bipolar disorder and schizophrenia were associated with a thinner ventromedial prefrontal cortex (vmPFC). We found these associations in the combined group, and separately in patients and drug-naive controls. Polygenic risk for bipolar disorder was correlated with the functional hub strength of the vmPFC within the default mode network. LIMITATIONS: Polygenic risk is a cumulative measure of genomic burden. Detailed genetic mechanisms underlying brain alterations and their cognitive consequences still need to be determined. CONCLUSION: Our multimodal neuroimaging study linked genomic burden and brain endophenotype by demonstrating an association between polygenic risk scores for bipolar disorder and schizophrenia and the structure and function of the vmPFC. Our findings suggest that genetic factors might confer risk for psychotic disorders by influencing the integrity of the vmPFC, a brain region involved in self-referential processes and emotional regulation. Our study may also provide an imaging-genetics vulnerability marker that can be used to help identify individuals at risk for developing bipolar disorder.

Temporal flow of hubs and connectivity in the human brain.

Hubs in brain network connectivity have previously been observed using neuroimaging techniques and are generally believed to be of pivotal importance to establish and maintain a functional platform on which cognitively meaningful and energy-efficient neuronal communication can occur. However, little is known if hubs are static (i.e. a brain region is always a hub) or if these properties change over time (i.e. brain regions fluctuate in their 'hubness'). To address this question, we introduce two new methodological concepts, the flow of brain connectivity and node penalized shortest paths which are then applied to time-varying functional connectivity fMRI BOLD data. We show that the constellations of active hubs change over time in a non-trivial way and that activity of hubs is dependent on the temporal scale of investigation. Slower fluctuations in the number of active hubs that exceeded the degree expected by chance alone were detected primarily in subcortical structures. Moreover, we observed faster fluctuations in hub activity residing predominately in the default mode network that suggests dynamic events in brain connectivity. Our results suggest that the temporal behavior of connectivity hubs is a multilayered and complex issue where method-specific properties of temporal sensitivity to time-varying connectivity must be taken into account. We discuss our results in relation to the on-going discussion of the existence of discrete and stable states in the resting-brain and the role of network hubs in providing a scaffold for neuronal communication across time.

Analysis of task-based functional MRI data preprocessed with fMRIPrep.

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time consuming, error prone and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure to standardize both the input datasets (MRI data as stored by the scanner) and the outputs (data ready for modeling and analysis), fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.

Agreement of sleep specialists with registered nurses' sleep study orders in supervised clinical practice.

STUDY OBJECTIVES: Incorporating registered nurses (RN-level) into obstructive sleep apnea (OSA) management decisions has the potential to augment the workforce and improve patient access, but the appropriateness of such task-shifting in typical practice is unclear. METHODS: Our medical center piloted a nurse triage program for sleep medicine referrals. Using a sleep specialist-designed decision-making tool, nurses triaged patients referred for initial sleep studies to either home sleep apnea test (HSAT) or in-laboratory polysomnography (PSG). During the first 5 months of the program, specialists reviewed all nurse triages. We compared agreement between specialists and nurses. RESULTS: Of 280 consultations triaged by nurses, nurses deferred management decisions to sleep specialists in 6.1% (n = 17) of cases. Of the remaining 263 cases, there was 88% agreement between nurses and specialists (kappa 0.80, 95% confidence interval 0.74-0.87). In the 8.8% (n = 23) of cases where supervising specialists changed sleep study type, specialists changed from HSAT to PSG in 16 cases and from PSG to HSAT in 7. The most common indication for change in sleep study type was disagreement regarding OSA pretest probability (n = 14 of 23). Specialists changed test instructions in 3.0% (n = 8) of cases, with changes either related to the use of transcutaneous carbon dioxide monitoring (n = 4) or adaptive servo-ventilation (n = 4). CONCLUSIONS: More than 80% of sleep study triages by registered nurses in a supervised setting required no sleep specialist intervention. Future research should focus on how to integrate nurses into the sleep medicine workforce in a manner that maximizes efficiency while preserving or improving patient outcomes.

Top-Down Beta Enhances Bottom-Up Gamma.

Several recent studies have demonstrated that the bottom-up signaling of a visual stimulus is subserved by interareal gamma-band synchronization, whereas top-down influences are mediated by alpha-beta band synchronization. These processes may implement top-down control of stimulus processing if top-down and bottom-up mediating rhythms are coupled via cross-frequency interaction. To test this possibility, we investigated Granger-causal influences among awake macaque primary visual area V1, higher visual area V4, and parietal control area 7a during attentional task performance. Top-down 7a-to-V1 beta-band influences enhanced visually driven V1-to-V4 gamma-band influences. This enhancement was spatially specific and largest when beta-band activity preceded gamma-band activity by ∼0.1 s, suggesting a causal effect of top-down processes on bottom-up processes. We propose that this cross-frequency interaction mechanistically subserves the attentional control of stimulus selection.SIGNIFICANCE STATEMENT Contemporary research indicates that the alpha-beta frequency band underlies top-down control, whereas the gamma-band mediates bottom-up stimulus processing. This arrangement inspires an attractive hypothesis, which posits that top-down beta-band influences directly modulate bottom-up gamma band influences via cross-frequency interaction. We evaluate this hypothesis determining that beta-band top-down influences from parietal area 7a to visual area V1 are correlated with bottom-up gamma frequency influences from V1 to area V4, in a spatially specific manner, and that this correlation is maximal when top-down activity precedes bottom-up activity. These results show that for top-down processes such as spatial attention, elevated top-down beta-band influences directly enhance feedforward stimulus-induced gamma-band processing, leading to enhancement of the selected stimulus.

The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

A jackknife approach to quantifying single-trial correlation between covariance-based metrics undefined on a single-trial basis.

The quantification of covariance between neuronal activities (functional connectivity) requires the observation of correlated changes and therefore multiple observations. The strength of such neuronal correlations may itself undergo moment-by-moment fluctuations, which might e.g. lead to fluctuations in single-trial metrics such as reaction time (RT), or may co-fluctuate with the correlation between activity in other brain areas. Yet, quantifying the relation between moment-by-moment co-fluctuations in neuronal correlations is precluded by the fact that neuronal correlations are not defined per single observation. The proposed solution quantifies this relation by first calculating neuronal correlations for all leave-one-out subsamples (i.e. the jackknife replications of all observations) and then correlating these values. Because the correlation is calculated between jackknife replications, we address this approach as jackknife correlation (JC). First, we demonstrate the equivalence of JC to conventional correlation for simulated paired data that are defined per observation and therefore allow the calculation of conventional correlation. While the JC recovers the conventional correlation precisely, alternative approaches, like sorting-and-binning, result in detrimental effects of the analysis parameters. We then explore the case of relating two spectral correlation metrics, like coherence, that require multiple observation epochs, where the only viable alternative analysis approaches are based on some form of epoch subdivision, which results in reduced spectral resolution and poor spectral estimators. We show that JC outperforms these approaches, particularly for short epoch lengths, without sacrificing any spectral resolution. Finally, we note that the JC can be applied to relate fluctuations in any smooth metric that is not defined on single observations.

Prevalence of chronic obstructive pulmonary disease and tobacco use in veterans at Boise Veterans Affairs Medical Center.

BACKGROUND: Although its prevalence is still debated, chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality in the United States, and smoking cessation remains the only intervention that can significantly improve the prognosis of COPD. METHODS: To determine the prevalence of COPD in a typical population seeking care at a Veterans Affairs Medical Center; the impact of smoking, age, and sex on the prevalence of COPD in this population; and how often spirometry is done in patients at risk for COPD, we extracted data from the Veterans Integrated Service Network 20 Consumer Health Information and Performance Sets database, on patients seen at the Boise Veterans Affairs Medical Center between January 1, 1999, and May 30, 2006. RESULTS: Approximately 8.8% (2,556/28,983) of all patients and 14.1% (1,152/8,149) of smokers were reported to have COPD. The odds of COPD in smokers, after adjusting for age and sex, was 3.18 (95% confidence interval 2.88-3.50) times greater than in nonsmokers. Males were 1.48 times more likely to have COPD than females, and there was an increasing risk of COPD with age. Thirty-nine percent of all veterans and 54% of those with COPD were active smokers. 273 (60%) of the 455 symptomatic smokers without a prior diagnosis of COPD were not evaluated with spirometry. CONCLUSIONS: The prevalence of COPD in patients at the Boise Veterans Affairs Medical Center was consistent with that in other United States surveys, although the underutilization of screening spirometry in those at risk for COPD may have caused underestimation of the prevalence. Smoking, age, and male sex were identified as significant risk factors for COPD, and the prevalence of active smoking remains high in this population of veterans.

Is pulmonary arterial hypertension in neurofibromatosis type 1 secondary to a plexogenic arteriopathy?

BACKGROUND: Neurofibromatosis type 1 (NF1) is a common disorder of dysregulated tissue growth secondary to mutations in the tumor suppressor gene NF1. Pulmonary arterial hypertension (PAH) in patients with NF1 is hypothesized to be secondary to an underlying vasculopathy. METHODS: We describe the entity we term NF1-associated PAH (NF1-PAH) in four new patients and update the data on four previously published reports of patients with PAH and NF1. We performed genetic testing of the bone morphogenic protein receptor 2 (BMPR2) gene, which mutated in 70% of patients with familial PAH and approximately 25% of patients with idiopathic PAH. We report, for the first time, pathologic findings in the autopsy-obtained lung of one patient with NF1-PAH. RESULTS: Patients with NF1-PAH have a generally poor long-term prognosis. In four patients, we observed the mosaic pattern of lung attenuation on a CT scan of the chest, a radiographic finding that can be consistent with an underlying vasculopathy. No mutations or rearrangements in the BMPR2 gene were found. We observed complex plexiform lesions in the one available autopsy specimen. Similar lesions are a hallmark of plexogenic pulmonary arteriopathy and are associated with several severe types of PAH. (Plexiform lesions should not be confused with plexiform neurofibromas, which are distinctive tumors seen in NF1.) CONCLUSIONS: Our findings suggest that NF1 should be considered as being "associated with PAH as outlined in the Revised Clinical Classification of Pulmonary Hypertension. Understanding the mechanism of PAH in NF1 may inform the pathogenesis of PAH, NF1-PAH itself, and other NF1-associated vasculopathies. The pulmonary vasculature should now be included among the arterial beds affected by NF1 vasculopathy.

Functional anatomy of bronchial veins.

The amount of bronchial arterial blood that drains into the systemic venous system is not known. Therefore, in this study we further delineated the functional anatomy of the bronchial venous system in six adult, anesthetized, and mechanically ventilated sheep. Through a left thoracotomy, the left azygos vein was dissected and the insertion of the bronchial vein into the azygos vein was identified. A pouch was created by ligating the azygos vein on either side of the insertion of the bronchial vein. A catheter was inserted into this pouch for the measurement of bronchial venous occlusion pressure and bronchial venous blood flow. An ultrasonic flow probe was placed around the common bronchial branch of the bronchoesophageal artery to monitor the bronchial arterial blood flow. Catheters were also placed into the carotid artery and the pulmonary artery. The mean bronchial blood flow was 20.6+/-4.2mlmin(-1) (mean+/-SEM) and, of this, only about 13% of the blood flow drained into the azygos vein. The mean systemic artery pressure was 72.4+/-4.1mmHg whereas the mean bronchial venous occlusion pressure was 38.1+/-2.1mmHg. The mean values for blood gas analysis were as follows: bronchial venous blood pH=7.54+/-0.02, PCO(2)=35+/-2.6, PO(2)=95+/-5.7mmHg; systemic venous blood-pH=7.43+/-0.02, PCO(2)=48+/-3.2, PO(2)=42+/-2.0mmHg; systemic arterial blood-pH=7.51+/-0.03, PCO(2)=39+/-2.1, PO(2)=169+/-9.8mmHg. We conclude that the major portion of the bronchial arterial blood flow normally drains into the pulmonary circulation and only about 13% drains into the bronchial venous system. In addition, the oxygen content of the bronchial venous blood is similar to that in the systemic arterial blood.

Bronchioloalveolar carcinoma masquerading as pneumonia.

Bronchioloalveolar carcinoma (BAC) is a relatively rare adenocarcinoma that typically arises in the lung periphery and grows along alveolar walls, without destroying the lung parenchyma. It is often multicentric and may arise from a previously stable scar. Because the parenchyma is preserved and because BAC may arise simultaneously in multiple lobes, the chest radiograph and symptoms (cough, chest pain, and sputum production) may be indistinguishable from pneumonia or other noninfectious inflammatory processes (eg, hypersensitivity pneumonitis or bronchiolitis obliterans). The clinician should suspect BAC if what otherwise appears to be pneumonia lacks fever or leukocytosis or does not respond to antibiotics. BAC accounts for 2.6-4.3 % of all lung cancers. On a radiograph, BAC often appears as a solitary nodule, but may also appear as a patchy, lobar or multilobar infiltrates, often with air bronchograms indistinguishable from pneumonia. Positron-emission tomography does not help distinguish BAC from pneumonia. Among BAC patients, 62% present without symptoms and with only an abnormal radiograph, whereas 38% present with symptoms of cough, chest pain, and sputum production. Bronchoscopy is usually normal. Preoperative diagnosis with transbronchial biopsy, bronchoscopic cytology examination, or expectorated sputum cytology is more common with the diffuse or multicentric forms. Cure depends on complete resection. A trial of antibiotics and reassessment of clinical findings is a reasonable approach, but biopsy or cytology is the only means of ruling in malignancy and ruling out other etiologies, so biopsy should always be considered when a presumed pneumonia does not respond to antibiotics. I saw a 61-year-old man whose initial diagnosis was pneumonia. He took a 10-day course of oral azithromycin, but his symptoms and chest radiograph were unchanged. A tomogram showed interstitial prominence and peripheral air-space disease in the right upper and lower lobes. Transbronchial biopsy of the right upper lobe showed Clara cells, with substantial atypia and various nuclear-cytoplasmic ratios. The underlying pulmonary architecture was preserved and no invasive component was seen. The diagnosis was changed to nonmucinous BAC. Pneumonectomy was successful and he was cancer-free for about 10 months, after which the cancer returned and from which he eventually died.