Appendix
Detailed specification of used devices and software.
Surgery and supportive methods
All patients had a preoperative MRI scan (1.5 Tesla, according to the site-specific protocol,
including contrast enhanced (CE) T1, T2-weighted, spectroscopy, diffusion weighed scenes).
All surgeries were aided by the StealthViz application (Medtronic Inc., Minneapolis). Blue
light filtering of the neurosurgical microscope (OPMI Pentero with fluorescence kit BLU 400,
Carl Zeiss, Germany) was in compliance with the requirements of the European Medical
Device Directive 93/42/EEC. The excitation and observation wavelength ranges were 400410 and 620-710 nanometres respectively. The configuration of room luminance remained
constant throughout the study period. The microscope was equipped with the optional
integrated digital camera MKC-500HD (Ikegami Co.; Tokyo, Japan) available from the
microscope manufacturer. The following camera specifications were selected for the study
purposes: high-definition matrix 1920x1080p, 54dB signal-to-noise ratio, sensitivity of F12 at
2000 lux/3200°K, all generated by a 1/3-inch CMOS image sensor. The pre-defined camera
profiles of light sensitivity and white balance remained constant. Detailed data of spectral
sensitivity and light filtering in both the microscope and camera were unobtainable from the
manufacturers.
According to manufacturer’s information, the visualization of the fluorescence signal is
influenced by: the illumination intensity of the light source, transmission of the optical
system, total magnification, working distance, illuminated field diameter, room lighting,
operating field seen either on monitor or through the eyepieces, low camera shutter, gradually
elapsing fluorescence as well as perceptual non-uniformities of human eye (brochure: ZEISS
OPMI® Pentero®).
StealthStation S7 navigation (Medtronic Navigation; Louisville, CO, USA) facilitated all
surgeries; in three patients an intraoperative low-field MRI (PoleStar, Medtronic Navigation,
Louisville, CO, USA) was used to visualize the tumour remnant.
The extent of resection, including GTR, was assessed by comparing the preoperative contrast
enhancing T1-weighted tumour volume with the postoperative one. In accordance with the
RANO criteria, this study included an exam between 48 and 72 hours post-op 37. The overall
survival data was gathered, whereas the impact of either type of adjuvant therapy or additional
surgical therapy were not evaluated.
Objectives, study design and analysis
The navigation screen was recorded in high definition throughout the surgery (Nikon D7100;
Tokyo, Japan). It was synchronized with timeline of the video recorded in the operating
microscope (MPEG-4 compression). The selection criteria for probing samples for the
colorimetric evaluation were as follows: subjectively noticed spot demonstrating any
fluorescence, circumscribed by surrounding of a different colour, regardless of its later
surgical removal, probed from the movie until the evident brain shift has been noticed. The
correspondence between contrast's enhancing in T1 and fluorescence's colour feature
measures was assessed, though carries a potential bias risk due to the possible concurrent
brain shift. The combined video was viewed side by side in Shotcut software v.5.2.0 (Digia
Inc.; Santa Clara, CA, USA) without any digital filtering and was displayed on Dell U2410
32’’ monitor (1920x1200p, 16:10 widescreen aspect ratio, 80000:1 dynamic contrast ratio,
color depth of 1.07 billion, 100% coverage of CIE L*a*b* colour gamut 7).
The fluorescent colour features of tumour remnants were compared to those of other CE
regions. False - or + rates for fluorescence were not calculated as the tissue samples were not
separately assessed for histopathology. In order to increase their visibility, some videos were
post-processed in Shotcut using filters tailored to the obtained images. The colours of areas
corresponding to missed tumour and their backgrounds were sampled twice, before and after
the post-processing.
From the technical point of view, a group of various fluorescent colour features were
analysed. The points of interest (samples) from a video image (both the fluorescent region and
the matched background inside the tumour) were probed for RGB colour model values using
Colour Contrast Analyser v.2.2a (WAT Consortium, int’l). Then it was mathematically
transformed to a perceptually-oriented uniform colour space CIE 1976 L*a*b* (The
International Commission on Illumination)7. L* denotes lightness, a* defines red/green value
and b* yellow/blue value. The difference between the shades of matched interested
fluorescent region and the background determined the delta-E (ΔE) and Contrast Ratio (CR).
ΔE measured the difference/distance between two colours that is calculated from their all
colour coordinates (L*, a* and b*), while CR compared solely relative luminance (all colours
are normalized to greyscale). The first is the principal parameter describing the difference
between colours and the latter has been widely used for internet web content assessment.
The following formulas calculated colour differences:
- ΔE = √(𝐿1 − 𝐿2)2 + (𝑎1 − 𝑎2)2 + (𝑏1 − 𝑏2)2
- CR = (L1 + 0.05) / (L2 + 0.05)
where L1 and L2 denote the relative luminance of the lighter and darker colour
respectively; a1, b1 and a1, b1 are particular dimensions of lighter and darker colour
respectively.
CR was yielded automatically by Colour Contrast Analyser software, while ΔE as well as
RGB to CIE 1976 L*a*b* transformations were calculated using a pre-defined spread sheet
(Microsoft Office Excel 2010 for Windows).
(Figure 1).
Statistical analysis
The individual participant data (IPD) framework was adopted. Reports containing incomplete
variables were valid for selected analyses of their complete data. Chi-square, Student’s t-test
and their non-parametric equivalents tested univariate relations, whereas logistic regression
was used for multivariate analysis. The area under each Receiver Operating Characteristic
(ROC) curve (AUC) was calculated for significant factors. The Youden index was estimated
for relevant ROCs and denoted an optimal trade-off between sensitivity and specificity. The
Cox proportional hazards model explored the relationship between survival and explanatory
variables. Statistica Software v.10.0 (StatSoft Inc.; Tulsa, OK, USA), and Prism (GraphPad;
La Jolla, CA, USA) were used and p value <0.05 was considered statistically significant. The
continuous variables were expressed as mean ± standard deviation (SD).