M. Volmer et al., PARTIAL LEAST-SQUARES REGRESSION FOR ROUTINE ANALYSIS OF URINARY CALCULUS COMPOSITION WITH FOURIER-TRANSFORM INFRARED-ANALYSIS, Clinical chemistry, 39(6), 1993, pp. 948-954
Quantitative assessment of urinary calculus (renal stone) constituents
by infrared analysis (IR) is hampered by the need of expert knowledge
for spectrum interpretation. Our laboratory performed a computerized
search of several libraries, containing 235 reference spectra from var
ious mixtures with different proportions. Library search was followed
by visual interpretation of band intensities for more precise semiquan
titative determination of the composition. We tested partial least-squ
ares (PLS) regression for the most frequently occurring compositions o
f urinary calculi. Using a constrained mixture design, we prepared var
ious samples containing whewellite, weddellite, and carbonate apatite
and used these as a calibration set for PLS regression. The value of P
LS analysis was investigated by the assay of known artificial mixtures
and selected patients' samples for which the semiquantitative composi
tions were determined by computerized library search followed by visua
l interpretation. Compared with that method, PLS analysis was superior
with respect to accuracy and necessity of expert knowledge. Apart fro
m some practical limitations in data-handling facilities, we believe t
hat PLS regression offers a promising tool for routine quantification,
not only for whewellite, weddellite, and carbonate apatite, but also
for other compositions of the urinary calculus.