Small Airway Disease in Pre-Chronic Obstructive Pulmonary Disease with Emphysema: A Cross-Sectional Study.

Rationale: Small airway disease is an important pathophysiological feature of chronic obstructive pulmonary disease (COPD). Recently, "pre-COPD" has been put forward as a potential precursor stage of COPD that is defined by abnormal spirometry findings or significant emphysema on computed tomography (CT) in the absence of airflow obstruction. Objective: To determine the degree and nature of (small) airway disease in pre-COPD using microCT in a cohort of explant lobes/lungs. Methods: We collected whole lungs/lung lobes from patients with emphysematous pre-COPD (n = 10); Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage I (n = 6), II (n = 6), and III/IV (n = 7) COPD; and controls (n = 10), which were analyzed using CT and microCT. The degree of emphysema and the number and morphology of small airways were compared between groups, and further correlations were investigated with physiologic measures. Airway and parenchymal pathology was also validated with histopathology. Measurements and Main Results: The numbers of transitional bronchioles and terminal bronchioles per milliliter of lung were significantly lower in pre-COPD and GOLD stages I, II, and III/IV COPD compared with controls. In addition, the number of alveolar attachments of the transitional bronchioles and terminal bronchioles was also lower in pre-COPD and all COPD groups compared with controls. We did not find any differences between the pre-COPD and COPD groups in CT or microCT measures. The percentage of emphysema on CT showed the strongest correlation with the number of small airways in the COPD groups. Histopathology showed an increase in the mean chord length and a decrease in alveolar surface density in pre-COPD and all GOLD COPD stages compared with controls. Conclusions: Lungs of patients with emphysematous pre-COPD already show fewer small airways and airway remodeling even in the absence of physiologic airway obstruction.

Parkinson's Disease Tremor Differentially Responds to Levodopa and Subthalamic Stimulation.

Background: Tremor in Parkinson's disease (PD) has an inconsistent response to levodopa and subthalamic deep brain stimulation (STN-DBS). Objectives: To identify predictive factors of PD tremor responsiveness to levodopa and STN-DBS. Material and Methods: PD patients with upper limb tremor who underwent STN-DBS were included. The levodopa responsiveness of tremor (overall, postural, and rest sub-components), was assessed using the relevant Unified Parkinson's Disease Rating Scale-III items performed during the preoperative assessment. Post-surgical outcomes were similarly assessed ON and OFF stimulation. A score for the rest/postural tremor ratio was used to determine the influence of rest and postural tremor severity on STN-DBS outcome. Factors predictive of tremor responsiveness were determined using multiple linear regression modeling. Volume of tissue activated measurement coupled to voxel-based analysis was performed to identify anatomical clusters associated with motor symptoms improvement. Results: One hundred and sixty five patients were included in this study. Male gender was negatively correlated with tremor responsiveness to levodopa, whereas the ratio of rest/postural tremor was positively correlated with both levodopa responsiveness and STN-DBS tremor outcome. Clusters corresponding to improvement of tremor were in the subthalamic nucleus, the zona incerta and the thalamus, whereas clusters corresponding to improvement for akinesia and rigidity were located within the subthalamic nucleus. Conclusion: More severe postural tremor and less severe rest tremor were associated with both poorer levodopa and STN-DBS response. The different locations of clusters associated with best correction of tremor and other parkinsonian features suggest that STN-DBS effect on PD symptoms is underpinned by the modulation of different networks.

Association of Clinical and Neuroanatomic Factors With Response to Ventral Tegmental Area DBS in Chronic Cluster Headache.

BACKGROUND AND OBJECTIVES: Deep brain stimulation (DBS) of the ventral tegmental area (VTA) is a surgical treatment option for selected patients with refractory chronic cluster headache (CCH). We aimed to identify clinical and structural neuroimaging factors associated with response to VTA DBS in CCH. METHODS: This prospective observational cohort study examines consecutive patients with refractory CCH treated with VTA DBS by a multidisciplinary team in a single tertiary neuroscience center as part of usual care. Headache diaries and validated questionnaires were completed at baseline and regular follow-up intervals. All patients underwent T1-weighted structural MRI before surgery. We compared clinical features using multivariable logistic regression and neuroanatomic differences using voxel-based morphometry (VBM) between responders and nonresponders. RESULTS: Over a 10-year period, 43 patients (mean age 53 years, SD 11.9), including 29 male patients, with a mean duration of CCH 12 years (SD 7.4), were treated and followed up for at least 1 year (mean follow-up duration 5.6 years). Overall, there was a statistically significant improvement in median attack frequency from 140 to 56 per month (Z = -4.95, p < 0.001), attack severity from 10/10 to 8/10 (Z = -4.83, p < 0.001), and duration from 110 to 60 minutes (Z = -3.48, p < 0.001). Twenty-nine (67.4%) patients experienced ≥50% improvement in attack frequency and were therefore classed as responders. There were no serious adverse events. The most common side effects were discomfort or pain around the battery site (7 patients) and transient diplopia and/or oscillopsia (6 patients). There were no differences in demographics, headache characteristics, or comorbidities between responders and nonresponders. VBM identified increased neural density in nonresponders in several brain regions, including the orbitofrontal cortex, anterior cingulate cortex, anterior insula, and amygdala, which were statistically significant (p < 0.001). DISCUSSION: VTA DBS showed no serious adverse events, and, although there was no placebo control, was effective in approximately two-thirds of patients at long-term follow-up. This study did not reveal any reliable clinical predictors of response. However, nonresponders had increased neural density in brain regions linked to processing of pain and autonomic function, both of which are prominent in the pathophysiology of CCH.

Multi-site, Multi-domain Airway Tree Modeling.

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to the quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and extensive clinical efforts for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Both quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage (https://atm22.grand-challenge.org/).

Automated airway quantification associates with mortality in idiopathic pulmonary fibrosis.

OBJECTIVES: The study examined whether quantified airway metrics associate with mortality in idiopathic pulmonary fibrosis (IPF). METHODS: In an observational cohort study (n = 90) of IPF patients from Ege University Hospital, an airway analysis tool AirQuant calculated median airway intersegmental tapering and segmental tortuosity across the 2nd to 6th airway generations. Intersegmental tapering measures the difference in median diameter between adjacent airway segments. Tortuosity evaluates the ratio of measured segmental length against direct end-to-end segmental length. Univariable linear regression analyses examined relationships between AirQuant variables, clinical variables, and lung function tests. Univariable and multivariable Cox proportional hazards models estimated mortality risk with the latter adjusted for patient age, gender, smoking status, antifibrotic use, CT usual interstitial pneumonia (UIP) pattern, and either forced vital capacity (FVC) or diffusion capacity of carbon monoxide (DLco) if obtained within 3 months of the CT. RESULTS: No significant collinearity existed between AirQuant variables and clinical or functional variables. On univariable Cox analyses, male gender, smoking history, no antifibrotic use, reduced DLco, reduced intersegmental tapering, and increased segmental tortuosity associated with increased risk of death. On multivariable Cox analyses (adjusted using FVC), intersegmental tapering (hazard ratio (HR) = 0.75, 95% CI = 0.66-0.85, p < 0.001) and segmental tortuosity (HR = 1.74, 95% CI = 1.22-2.47, p = 0.002) independently associated with mortality. Results were maintained with adjustment using DLco. CONCLUSIONS: AirQuant generated measures of intersegmental tapering and segmental tortuosity independently associate with mortality in IPF patients. Abnormalities in proximal airway generations, which are not typically considered to be abnormal in IPF, have prognostic value. CLINICAL RELEVANCE STATEMENT: Quantitative measurements of intersegmental tapering and segmental tortuosity, in proximal (second to sixth) generation airway segments, independently associate with mortality in IPF. Automated airway analysis can estimate disease severity, which in IPF is not restricted to the distal airway tree. KEY POINTS: • AirQuant generates measures of intersegmental tapering and segmental tortuosity. • Automated airway quantification associates with mortality in IPF independent of established measures of disease severity. • Automated airway analysis could be used to refine patient selection for therapeutic trials in IPF.

Radiology of Bronchiectasis.

Bronchiectasis is a radiological diagnosis made using computed tomographic (CT) imaging. Although visual CT assessment is necessary for the diagnosis of bronchiectasis, visual assessment of disease severity and progression is challenging. Computer tools offer the potential to improve the characterization of lung damage in patients with bronchiectasis. Newer imaging techniques such as MRI with hyperpolarized gas inhalation have the potential to identify early forms of disease and are without the constraints of requiring ionizing radiation exposure.

Improved X-ray computed tomography reconstruction of the largest fragment of the Antikythera Mechanism, an ancient Greek astronomical calculator.

The Antikythera Mechanism is an extraordinarily complex ancient Greek astronomical calculating device whose mode of operation is now relatively well understood particularly since imaging studies in 2005 revealed gears and inscriptions which were previously illegible. Unfortunately, the highest resolution X-ray computed tomography image of the largest fragment had some errors which meant that the reconstructed images were not as clear as had been expected. Here, the original X-ray data have been reanalysed and reconstructed. The new X-ray computed tomography images have improved contrast and resolution, leading to better clarity and legibility. The improvement in image quality is characterised and some examples of writing on the Mechanism which can now be read with increased confidence are given.