Chemistry Reference
In-Depth Information
multiplexed, qualitative or semi-quantitative low-cost point-of-care applications [
6
].
Whilst historically the lateral-
ow format has been optimised for qualitative point-
of-care diagnostics, the dipstick format has been designed for semi-quantitative
measurements. For example, urine dipsticks are widely used in clinical practice in
screening for renal, urinary, hepatic and metabolic disorders. Table
6.1
shows
commercial semi-quantitative urine dipsticks in the market. Colorimetric tests are
typically read by comparing the developed reaction zones with a reference chart.
However, subjective interpretation may result in erroneous diagnosis, limiting the
accuracy of colorimetric tests. To increase the accuracy of the measurement, colori-
metric tests can be analysed using benchtop equipment such as spectrophotometers, or
automated test-speci
fl
c readers such as CLINITEK Status
®
+ Analyzer (Siemens) or
Urisys 1100
®
Urine Analyzer (Roche). Recently, these devices have been offeredwith
connectivity options including data management solutions, such as data transfer
through serial, Ethernet and wireless connection, barcode data entry, and support for
healthcare connectivity protocols such as Health Level Seven (HL7) and point-of-care
testing POCT1-A2 standards. However, these dipstick readers have a number
of limitations that reduce their utility in resource-poor settings: (i) High retail price
(>$1,000), (ii) requirement for reader-speci
c test strips, (iii) poor portability, and (iv)
external power supply requirement.
The high mobile phone penetration and rapidly growing telecommunications
infrastructure represent an unprecedented opportunity for reading and transferring
point-of-care diagnostic data [
7
]. Global mobile-cellular subscriptions have grown
70 % over the last 5 years, reaching 7.3 billion as of 2014 (Fig.
6.1
)[
8
]. Hence, taking
advantage of the mobile phone infrastructure to monitor health conditions and the
environment will provide low-cost screening for existing and emerging diseases, and
improve the diagnostics at point-of-care setting. In telemedicine, a healthcare worker
can capture the image of the rapid test (e.g. colorimetric) and send it to a server at a
centralised facility [
9
]. The server running imaging software can analyse the image
based on greyscale or RGB/chromaticity values, which can be correlated with the
concentration of the analyte tested. The use of smartphone cameras has been
proposed for diagnostic applications in dermatology [
10
], microscopy [
11
13
],
-
ophthalmology [
14
], chemical analyses [
15
,
16
] and paper-based micro
uidic
devices [
17
,
18
]. However, smartphone cameras have standardisation challenges in
optical analysis of colorimetric assays. For example, integrated colour balancing
functions of camera phones are optimised for photography in bright ambient light.
Recently, there have been several approaches to address the issues related to ambient
light variability during colorimetric test readouts. For instance, a housing unit has
been built to eliminate the variation in lighting conditions and positioning of the
camera. These solutions required a phone-speci
fl
c external housing unit and other
components such as batteries, LED arrays (for re
ection and transmission) and lenses
[
19
]. In another study, a calibration chart and test assay images were captured using
the phone camera, and the chromaticity diagram-based image processing was per-
formed externally with a computer [
20
]. Fully-integrated smartphone apps that
quantify different types of colorimetric tests on both iOS and Android platforms are
needed to facilitate rapid screening at point-of-care settings.
fl
