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Background: Precise location of intracranial lesions before surgery is important, but occasionally difficult. Modern navigation systems are very helpful, but expensive. A low-cost solution that could locate brain lesions and their surface projections in augmented reality would be beneficial. We used an iPhone to partially achieve this goal, and evaluated its accuracy and feasibility in a clinical neurosurgery setting. Methodology/Principal Findings: We located brain lesions in 35 patients, and using an iPhone, we depicted the lesion’s surface projection onto the skin of the head. To assess the accuracy of this method, we pasted computed tomography (CT) markers surrounding the depicted lesion boundaries on the skin onto 15 patients. CT scans were then performed with or without contrast enhancement. The deviations (D) between the CT markers and the actual lesion boundaries were measured. We found that 97.7% of the markers displayed a high accuracy level (D ≤ 5mm). In the remaining 20 patients, we compared our iPhone-based method with a frameless neuronavigation system. Four check points were chosen on the skin surrounding the depicted lesion boundaries, to assess the deviations between the two methods. The integrated offset was calculated according to the deviations at the four check points. We found that for the supratentorial lesions, the medial offset between these two methods was 2.90 mm and the maximum offset was 4.2 mm. Conclusions/Significance: This low-cost, image-based, iPhone-assisted, augmented reality solution is technically feasible, and helpful for the localization of some intracranial lesions, especially shallow supratentorial intracranial lesions of moderate size. [ABSTRACT FROM AUTHOR]

Background: Locating the pyramidal tract (PT) is difficult in patients with thalamic or basal ganglia tumors, especially when the surrounding anatomical structures cannot be identified using computed tomography or magnetic resonance images. Hence, we objected to find a way to predict the location of the PT in patients with thalamic and basal ganglia tumors, Methodology/principal Findings: In 59 patents with thalamic or basal ganglia tumors, the PTs were constructed by with diffusion tensor imaging (DTI)-based fiber tracking (FT). In axial slices crossing the foramen of Monro, the tumor position was classified according to three lines. Line 1 was vertical and crossed the vertex point of the anterior limbs of the internal capsule. Lines 2 and line 3 were horizontal and crossed the foramen of Monro and joint of the middle and lateral thirds of the posterior limbs, respectively. Six (10.17%) patients were diagnosed with type 1 tumor, six (10.17%) with type 2, seven (11.86%) with type 3a, five (8.47%) with type 3b, 17 (28.81%) with type 4a, six (10.17%) with type 4b, three (5.08%) with type 5, and nine (15.25%) with type 6. In type 1 tumors, the PTs were located at the 12 o'clock position of the tumor, type 2 at six o'clock, type 3a between nine and 12 o'clock, type 3 between six and nine o'clock, type 4a between 12 and three o'clock, type 4b at three o'clock, type 5 between six and nine o'clock, and type 6 between three and six o'clock., Conclusions/significance: The position of the PT relative to the tumor could be determined according to the tumor location. These results could prove helpful in determining the location of the PT preoperatively.