Emerging multimodality imaging techniques for the pulmonary circulation

Abstract

Pulmonary hypertension (PH) remains a challenging condition to diagnose, classify and treat. Current approaches to the assessment of PH include echocardiography, ventilation/perfusion scintigraphy, cross-sectional imaging using computed tomography and magnetic resonance imaging, and right heart catheterisation. However, these approaches only provide an indirect readout of the primary pathology of the disease: abnormal vascular remodelling in the pulmonary circulation. With the advent of newer imaging techniques, there is a shift toward increased utilisation of noninvasive high-resolution modalities that offer a more comprehensive cardiopulmonary assessment and improved visualisation of the different components of the pulmonary circulation. In this review, we explore advances in imaging of the pulmonary vasculature and their potential clinical translation. These include advances in diagnosis and assessing treatment response, as well as strategies that allow reduced radiation exposure and implementation of artificial intelligence technology. These emerging modalities hold the promise of developing a deeper understanding of pulmonary vascular disease and the impact of comorbidities. They also have the potential to improve patient outcomes by reducing time to diagnosis, refining classification, monitoring treatment response and improving our understanding of disease mechanisms.

FIGURE 1

Advances in pulmonary vascular imaging in the diagnosis and classification of pulmonary hypertension (PH). a) Early diagnosis of PH in at-risk groups. b) Screening in populations with a high prevalence of PH. Chest computed tomography (CT) angiography in a 71-year-old male with systemic sclerosis and PH demonstrating (left panel) subtle nodular ground-glass opacities and (right panel) spectral imaging with photon-counting CT demonstrating heterogeneous perfusion. c) Deep phenotyping to understand disease mechanisms and clinical classification: (left panel) subtle changes in pulmonary veno-occlusive disease (PVOD)/pulmonary capillary haemangiomatosis (PCH) with photon counting CT; (right panel) three-dimensional (3D) blood flow visualisation (Streamlines) in the right heart from 4D flow magnetic resonance imaging (MRI) in a 39-year-old female with pulmonary arterial hypertension (PAH), showing vortical (swirling/rotating) flow in the main pulmonary artery (MPA) and right ventricle (RV) during late systole. Colours indicate flow velocity magnitude (range is 0–0.64 m·s⁻¹). ¹¹C: carbon-11; PET: positron emission tomography; ¹²⁹Xe: xenon-129; RPA: right pulmonary artery; LPA: left pulmonary artery; RA: right atrium.

FIGURE 2

Advances in pulmonary vascular imaging in guiding assessing treatment of pulmonary hypertension (PH). a) Aid decision-making in all forms of PH. 3′-deoxy-3′-(¹⁸F)-fluorothymidine (¹⁸FLT) positron emission tomography (PET) scanning is increased in some patients with pulmonary arterial hypertension (PAH), which could signal a better treatment response to antiproliferative drugs. b) Assess impact of pharmacological interventions. (Left panel) Three-dimensional reconstruction of the macroscopic pulmonary vessels detected using a fully automated quantitative computed tomography (CT) pipeline software (Fluidda, Inc., USA). Small vessels (<5 mm² in cross-sectional area) are depicted in red, intermediate vessels (>5 mm² and <10 mm²) are depicted in yellow, and large vessels (>10 mm²) are depicted in blue. On the baseline CT (left) of a patient with chronic thromboembolic pulmonary hypertension (CTEPH) there is dilatation of large proximal vessels and loss of smaller vessels. Following successful pulmonary endarterectomy (PEA) (right), there is reduction in the larger vessels and significant increase in the distribution of the smaller vessels. (Analysis and image courtesy of Ben R. Lavon and Fluidda, Inc.) (Right panel) Xenon-129 (¹²⁹Xe) magnetic resonance sounding (MRS) oscillation imaging identifies regions with decreased perfusion (red) at baseline in a patient with operable CTEPH (before), with significant improvement after PEA surgery (after). c) Holistic approaches to assess impact of therapies. (Left panel) Magnetic resonance imaging (MRI) assessment of changes in right ventricular (RV) perfusion in CTEPH with PEA and (right panel) magnetic resonance angiography of disease burden in CTEPH. d) Disease burden to guide treatment. (Left panel) conventional CT pulmonary embolism (PE) demonstrating near-total occlusion of the right pulmonary artery. (Right panel) CT angiography with spectral imaging providing iodine maps that reveal multiple PE-type defects. RV: right ventricle; MBF: myocardial blood flow; MPR: multiplanar reformation; mPAP: mean pulmonary artery pressure; RPA: right pulmonary artery.

FIGURE 3

Technical advances and application of artificial intelligence (AI) in imaging in patients with pulmonary vascular disease. a) AI extraction of pulmonary hypertension (PH) features from standard computed tomography pulmonary angiography images including pulmonary artery dimensions, right ventricular hypertrophy and cardiac volumes to allow for fully automated PH diagnosis with potential to aid earlier diagnosis of PH. Reproduced and modified from [6] with permission. b) AI implementation in clinical workstreams. (Upper panel) Segmentation of lung parenchyma in patient with PH to aid classification; normal parenchyma (red), emphysema (teal), honeycombing (yellow), ground glass (green) and ground glass with additional reticulation (blue) allowing for improved phenotyping of patients with PH (group 1 versus group 3) (performed using the approach in Dwivedi et al. [7]). (Lower panel) Example of AI automated analysis incorporated into clinical workstreams with measurements of cine and flow sequences from cardiac magnetic resonance imaging allowing for rapid and fully automated quantification of metrics in patients with PH. Adapted from Alabed et al. [8]. c) Reduction to radiation exposure with computed tomography (CT). Compared to a conventional energy-integrating detector CT (third-generation dual-source CT) (left panel), the photon-counting CT (right panel) reduces radiation exposure with superior visualisation of small vessels such as supernumerary arteries (arrowheads).