Assessing Near-Infrared Optical Tomography's Depth Capability in Imaging Brain Vessels: An Experimental Study.

Advanced brain vessel imaging is crucial for diagnosing and treating brain-related conditions such as lesions and strokes, ultimately enhancing brain health. Among the range of cerebrovascular imaging modalities, near-infrared optical tomography (NIROT) stands out for its cost-effectiveness and brain oxygenation quantification. The objective of this project, as a continuation of our prior simulation study, is to evaluate in vitro the Pioneer system for imaging blood vessels. An experimental study was performed on a silicon phantom with a tube inclusion mimicking the superficial blood vessels at a depth of 5 mm. The experiment employed a time domain (TD) NIROT called Pioneer system. Image reconstruction was performed using the obtained TD data. We used root mean square error (RMSE) to evaluate the accuracy of the reconstructed images. We were able to detect the location and structure of the tube with a RMSE of 0.0285. This experimental study showed that the TD NIROT Pioneer system can detect vessel-like inclusion at the depth of 5 mm.

Imaging Deep Haemorrhage and Ischaemia in Preterm Infants' Heads with Time-Domain Near-Infrared Optical Tomography: Phantom Study.

BACKGROUND AND AIM: The occurrence of brain lesions in preterm infants is common and can result in lasting disabilities. To prevent these and to safeguard the brain through therapeutic measures or neuroprotective treatments, it is important to identify cerebral ischaemia/hypoxia and haemorrhage at an early stage. For this purpose, we have successfully developed a cutting-edge time-domain near-infrared optical tomography (TD-NIROT) system, which offers diagnostic imaging for neonatal brain oxygenation. Our objective is to validate the effectiveness of the TD-NIROT in detecting deep ischaemia/hypoxia and haemorrhages through phantom experiments. METHODS: Spherical silicone phantoms were fabricated to replicate the head of preterm infant. To simulate the lesions, we made two head phantoms and embedded small inclusions mimicking ischaemia and haemorrhage at the depth of 30 mm. Additionally, a spherical interface was constructed to connect the spherical phantom to the imaging system, allowing us to collect time-domain data. Following the data acquisition, we proceeded with image reconstruction. Dice similarity was used as an indicator of the accuracy and similarity between the reconstructed images and the ground truth. RESULTS AND DISCUSSION: The resulting images exhibited an accurate location of haemorrhage and detected the ischaemia with a slightly shifted position with Dice similarity of 0.47 and 0.27. CONCLUSION: Our experiment validates the capability of our TD-NIROT system in successfully detecting deep haemorrhages and ischaemia within the phantom model. The achieved results suggest a promising level of accuracy in the imaging process. These findings are encouraging to continue this work to ultimately achieve clinical application of the TD-NIROT system in diagnosing and monitoring neonatal brain injuries.

Imaging Cerebral Blood Vessels Using Near-Infrared Optical Tomography: A Simulation Study.

Cerebral veins have received increasing attention due to their importance in preoperational planning and the brain oxygenation measurement. There are different modalities to image those vessels, such as magnetic resonance angiography (MRA) and recently, contrast-enhanced (CE) 3D gradient-echo sequences. However, the current techniques have certain disadvantages, i.e., the long examination time, the requirement of contrast agents or inability to measure oxygenation. Near-infrared optical tomography (NIROT) is emerging as a viable new biomedical imaging modality that employs near infrared light (650-950 nm) to image biological tissue. It was proven to easily penetrate the skull and therefore enables the brain vessels to be assessed. NIROT utilizes safe non-ionizing radiation and can be applied in e.g., early detection of neonatal brain injury and ischemic strokes. The aim is to develop non-invasive label-free dynamic time domain (TD) NIROT to image the brain vessels. A simulation study was performed with the software (NIRFAST) which models light propagation in tissue with the finite element method (FEM). Both a simple shape mesh and a real head mesh including all the segmented vessels from MRI images were simulated using both FEM and a hybrid FEM-U-Net network, we were able to visualize the superficial vessels with NIROT with a Root Mean Square Error (RMSE) lower than 0.079.