Automatic detection of misleading blood flow values in CT perfusion studies of lung cancer

CT Perfusion in Patients with Lung Cancer: Squamous Cell Carcinoma and Adenocarcinoma Show a Different Blood Flow

“…In particular, BF values strictly lower than 1 mL/min/100 g were automatically removed, being considered unlikely compliant with physiological values and rather ascribable to numerical errors. Similarly, BF values undergoing high TCC fitting errors due to the presence of structures, such as blood vessels and bronchi, or dynamic artefacts, were automatically detected as unreliable through the method presented in [ 26 ]. Finally, mean BF values were computed for each examination and considered to identify hemodynamic differences between the two histological NSCLC subtypes, AC and SCC.…”

“…Various perfusion parameters have been reported to differ between lung cancer subtypes [ 13 , 15 ], showing discordant results [ 16 – 21 ]. However, when considering these discordant findings, we must bear in mind that BF computation of lung tumours is exposed to several sources of error [ 22 ], arising from respiratory motion [ 23 ], CTp artefacts [ 24 ], and, not to forget, tumour location [ 25 ], which can affect the reliability of BF values [ 26 ], thus dimming the real nature of tumours and hampering development and standardization of biomarkers. As regards tumour location, its influence on BF values is rarely considered in CTp studies.…”

“…Nonetheless, it has been shown that perfusion in central carcinomas is significantly lower than in peripheral ones, due to the different recruitment of vessels [ 27 ]. Nevertheless, also anatomical structures inside lesion, such as vessels and bronchi, can be responsible for jeopardizing perfusion analyses [ 26 ].…”

Multislice Analysis of Blood Flow Values in CT Perfusion Studies of Lung Cancer

“…Voxel-based BF values, expressed in mL/min/100 g, were computed for each slice, using an in-house algorithm developed in Matlab (MathWorks, Natick, MA), implementing the maximum slope method [35] and represented through the use of colorimetric maps. Misleading perfusion values computed on poorly representative TCCs (due to a bad fit) were excluded from the analysis according to what is reported in [16, 36], in order to obtain more reliable results. The corresponding voxels are displayed in the colour maps with the “pink” colour.…”

“…Afterwards, the improvement of technology has permitted working on the whole tumour [14], or groups of slices, as the central ones [15]. However, authors have still continued working on a single section only [16], chosen as the one representing the largest tumour diameter [17], or better incorporated the solid-appearing part of the target lesion [18], or else being in the middle scan position [19–21]. Nonetheless, several researchers choose the single tumour section based on visual considerations only [22], such as that having the best quality [23], or the widest area [24], jointly to the least variability [25].…”