Characteristic Features of Infrared Thermographic Imaging in Primary Raynaud's Phenomenon

Abstract

Raynaud's phenomenon (RP) is characterized by the episodic whitening of the fingers upon exposure to cold. Verification of the condition is crucial in vibration-exposed patients. The current verification method is outdated, but thermographic imaging seems promising as a diagnostic replacement. By investigating patients diagnosed with RP, the study aimed at developing a simple thermographic procedure that could be applied to future patients where verification of the diagnosis is needed. Twenty-two patients with primary RP and 58 healthy controls were examined using thermographic imaging after local cooling of the hands for 1 min in water of 10°C. A logistic regression model was fitted with the temperature curve characteristics to convey a predicted probability of having RP. The characteristics time to end temperature and baseline temperature were the most appropriate predictors of RP among those examined (p = 0.004 and p = 0.04, respectively). The area under the curve was 0.91. The cut-off level 0.46 yielded a sensitivity and specificity of 82% and 86%, respectively. The positive and negative predictive values were 69% and 93%, respectively. This newly developed thermographic method was able to distinguish between patients with RP and healthy controls and was easy to operate. Thus, the method showed great promise as a method for verification of RP in future patients. Trial registration: ClinicalTrials.gov NCT03094910.

Keywords: diagnostic method; infrared thermographic imaging; primary Raynaud’s phenomenon; vibration white finger.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1

The thermographic examination setup with the infrared thermographic camera (large white arrow). R = right, L = left. After the cold challenge, the hands were left to rewarm on a towel (black arrow). The thermographic image illustrates the hands during rewarming. The small white arrows mark the elliptical area of interest on the middle phalanx of each investigated finger on the left hand. Both hands were investigated.

Figure 2

The thermographic parameters initially included in the curve analysis. The S-shaped curve is shown as an example, as the initial analysis on horizontally running curves was unsuccessful for some of the parameters. The light blue “dot-dashed” line marks the baseline finger temperature (tbase), the dark green line marks the end temperature (tend), and the percentage temperature recovery from the first to the latter is the R%. The vertical “long-dashed” line represents the time to tend. The orange line marks the finger temperature halfway through rewarming (t50), while the vertical dotted line marks the time to t50. The vertical yellow and gold lines represent the lower and upper lag times, respectively. The green horizontal line marks the finger temperature immediately after cooling (t0).

Figure 3

Flowchart of the proposed acquisition of rewarming curves after cold provocation (blue section) and the subsequent analysis of the curves, including the fitting of the prediction model (orange section). *The analysis conveyed eight sets of predictors, one set for each of the four ulnar fingers on each hand, which were reduced to one set by selection of the following values: tbase (mean), t0 (mean), tend (lowest value), time to tend (highest value). t50* and R% were calculated from the selected values of tbase, t0, and tend. Curve type was classified as S-shaped if all curves were S-shaped. If one or more curves were horizontal, curve type was classified as such. tbase = baseline finger temperature; t0 = finger temperature immediately after cooling; tend = end temperature; t50* = finger temperature halfway through rewarming; R% = the percentage temperature recovery at end temperature.

Figure 4

The two curve types identified during the analysis of the thermographic temperature curves. The numbers 1–3 refer to the time points of baseline, immediately after cooling, and at the end of the thermographic examination, respectively. These time points correspond to the temperature variables tbase, t0, and tend, respectively. The thermographic images associated with the mentioned time points are shown. The gray bar marks the time of the cold provocation. The top bar of the thermographic images shows the hands of a healthy participant (a), while the bottom bar presents the hands of a patient with RP (b). Note the lower temperature in the fingers of the patient compared with the healthy participant, especially at baseline and at end temperature (arrows). tbase = baseline finger temperature; t0 = finger temperature immediately after cooling; tend = end temperature.

Figure 5

Calibration belt plot with 80% and 95% confidence intervals. The blue diagonal line represents the ideal calibration line, where predicted probability equals actual (observed) probability. The black line with the gold observation points represents the fitted logistic regression model. The model did not differ significantly from the ideal line, p = 0.70. The rugs at the bottom and top of the plot give an impression of the density of the predictions for controls and patients, respectively. The calibration belt was plotted according to the method described in [21].

Figure 6

The receiver operating characteristic (ROC) curve generated from the final logistic regression model. The blue point marks the place on the curve where sensitivity and specificity are highest. This optimal point on the curve was used to derive the cut-off value, above or below which diagnosis is either confirmed or rejected, respectively. The gray area surrounding the ROC curve represents the 95% confidence interval.

Figure 7

The nomogram constructed from the final logistic regression model generated from the described thermographic procedure. The red illustrations mark an example of how to read the nomogram (a set of values generated from a patient); time to tend = 60 min., tbase = 26.5°C. In this example, the predicted probability of RP is above the cut-off value of 0.46 (blue line) and according to the thermographic test, the patient is positive for RP. For predicted probabilities below the cut-off value, diagnosis will be rejected. tbase = baseline finger temperature, time to tend = time to end temperature.

Figure 8

Flowchart of the results generated from the analysis of rewarming curves, fitting of prediction model (both orange section), and validation of the model as well as the subsequent calculation of the proposed cut-off level and construction of the nomogram (gray section). The orange section corresponds to the orange section of Figure 3. sloperew = slope of the curve during rapid rewarming; t50 = finger temperature halfway through rewarming; tbase = baseline finger temperature; t0 = finger temperature immediately after cooling; tend = end temperature; R% = percentage temperature recovery at end temperature; t50* = finger temperature halfway through rewarming (calculated). AUC = area under the curve. ROC = receiver operating characteristic.