The inaccuracy of simple visual interpretation for measurement of carotid stenosis by arteriography

2D perfusion angiography: an alternative method to evaluate endovascular intervention for acute lower limb ischemia

BACKGROUND

Despite advances in endovascular techniques to treat acute limb ischemia (ALI), evaluation of clinical outcomes for revascularization remains challenging, especially the accurate quantification of post-endovascular limb perfusion. This study aimed to investigate the accuracy and value of 2D perfusion angiography to evaluate endovascular intervention for ALI.

METHODS

A total of 47 patients with ALI were retrospectively analyzed. The transcutaneous oxygen partial pressure (TcPO2) was obtained using laser Doppler blood perfusion monitoring. The ankle-brachial index (ABI) and angiographic images were obtained before and after endovascular intervention. iFlow imaging was used to obtain color-coded images. Regions of interest (ROIs) at the femoral head, knee joint, and ankle joint were selected to obtain the time to peak (TTP). The differences in the TTP between the knee and femoral head regions (TTP difference in the knee area) and between the ankle and knee regions (TTP difference in the ankle area) were observed. The TTP, ABI, and TcPO2 between the complete response (CR), partial response (PR), no response (NR), and amputation (AM) groups were compared. The correlation between TTP changes in the ankle area (ΔTTP) and changes in ABI (ΔABI)/changes in TcPO2 (ΔTcPO2) was analyzed.

RESULTS

There was a significant increase in both TcPO2 and ABI compared with the pre-intervention values (27.75 ± 5.32 vs 40.92 ± 4.62, and 0.35 ± 0.16 vs 0.79 ± 0.15, respectively, all p < 0.01). The post-intervention TTP differences in the knee areas (5.12 ± 2.45 s) and ankle areas (6.93 ± 4.37 s) were significantly faster than pre-intervention TTP differences (7.03 ± 2.57 s and 10.66 ± 4.07 s, respectively, all p < 0.05). The post-operative TTP in the ankle area, post-operative TTP difference in the ankle area, and ΔTTP in the AM group were higher than the values in the CR and PR groups. The ΔTTP demonstrated strong correlation with ΔABI (r = -0.722, p < 0.01) and ΔTcPO2 (r = -0.734, p < 0.01).

CONCLUSIONS

2D perfusion angiography with enhanced visual and quantitative analysis exhibits great potential to evaluate the efficacy of endovascular intervention, and provides a quantitative and sensitive tool to evaluate post-endovascular limb perfusion for ALI patients.

Deep learning-based interpretation of basal/acetazolamide brain perfusion SPECT leveraging unstructured reading reports

PURPOSE

Basal/acetazolamide brain perfusion single-photon emission computed tomography (SPECT) has been used to evaluate functional hemodynamics in patients with carotid artery stenosis. We aimed to develop a deep learning model as a support system for interpreting brain perfusion SPECT leveraging unstructured text reports.

METHODS

In total, 7345 basal/acetazolamide brain perfusion SPECT images and their text reports were retrospectively collected. A long short-term memory (LSTM) network was trained using 500 randomly selected text reports to predict manually labeled structured information, including abnormalities of basal perfusion and vascular reserve for each vascular territory. Using this trained LSTM model, we extracted structured information from the remaining 6845 text reports to develop a deep learning model for interpreting SPECT images. The model was based on a 3D convolutional neural network (CNN), and the performance was tested on the other 500 cases by measuring the area under the receiver-operating characteristic curve (AUC). We then applied the model to patients who underwent revascularization (n = 33) to compare the estimated output of the CNN model for pre- and post-revascularization SPECT and clinical outcomes.

RESULTS

The AUC of the LSTM model for extracting structured labels was 1.00 for basal perfusion and 0.99 for vascular reserve for all 9 brain regions. The AUC of the CNN model designed to identify abnormal perfusion was 0.83 for basal perfusion and 0.89 for vascular reserve. The output of the CNN model was significantly improved according to the revascularization in the target vascular territory, and its changes in brain territories were concordant with clinical outcomes.

CONCLUSION

We developed a deep learning model to support the interpretation of brain perfusion SPECT by converting unstructured text reports into structured labels. This model can be used as a support system not only to identify perfusion abnormalities but also to provide quantitative scores of abnormalities, particularly for patients who require revascularization.

Assessment of Flow after Lower Extremity Endovascular Revascularisation: A Feasibility Study Using Time Attenuation Curve Analysis of Digital Subtraction Angiography

Objectives

Endovascular revascularisation is the mainstay of the treatment of lower extremity peripheral arterial disease. Improvement in perfusion after treatment is often quantified by a corresponding increment in ankle or toe brachial indices. These measurements are difficult to obtain in patients with foot wounds, and have to be performed at a separate time and setting after revascularisation. This preliminary study aimed to evaluate the use of parametric colour coding and analysis of time attenuation curves as a real time quantitative measure of perfusion after endovascular revascularisation.

Methods

Forty-seven consecutive patients with critical limb ischaemia were retrospectively enrolled and analysed. Parametric colour coding and generation of time attenuation curves in the main pedal vessel was performed for pre- and post-intervention digital subtraction angiograms of each patient. The change in time attenuation curve parameters was compared with the change in ankle or toe brachial indices before and after intervention.

Results

Comparing before and after lower extremity endovascular intervention, there were significant changes in the washout parameters derived from the time attenuation curve. The percentage of contrast decay 4 seconds after peak (I _4s) demonstrated the strongest correlation (R = .482) with the change in ankle or toe brachial indices.

Conclusions

Parametric colour coding and time attenuation curve analysis might be a helpful tool that can provide real time intra-procedural quantitative data on pedal perfusion which can improve clinical outcomes.

Internal Carotid Artery Stenosis: Accuracy of Subjective Visual Impression for Evaluation with Digital Subtraction Angiography and Contrast-enhanced MR Angiography

PURPOSE

To prospectively determine, for both digital subtraction angiography (DSA) and contrast material-enhanced magnetic resonance (MR) angiography, the accuracy of subjective visual impression (SVI) in the evaluation of internal carotid artery (ICA) stenosis, with objective caliper measurements serving as the reference standard.

MATERIALS AND METHODS

Local ethics committee approval and written informed patient consent were obtained. A total of 142 symptomatic patients (41 women, 101 men; mean age, 70 years; age range, 44-89 years) suspected of having ICA stenosis on the basis of Doppler ultrasonographic findings underwent both DSA and contrast-enhanced MR angiography. With each modality, three independent neuroradiologists who were blinded to other test results first visually estimated and subsequently objectively measured stenoses. Diagnostic accuracy and percentage misclassification for correct categorization of 70%-99% stenosis were calculated for SVI, with objective measurements serving as the reference standard. Interobserver variability was determined with kappa statistics.

RESULTS

After exclusion of arteries that were unsuitable for measurement, 180 vessels remained for analysis with DSA and 159 vessels remained for analysis with contrast-enhanced MR angiography. With respect to 70%-99% stenosis, SVI was associated with average misclassification of 8.9% for DSA (8.9%, 7.8%, and 10.0% for readers A, B, and C, respectively) and of 11.7% for contrast-enhanced MR angiography (11.3%, 8.8%, and 15.1% for readers A, B, and C, respectively). Negative predictive values were excellent (92.3%-100%). Interobserver variability was higher for SVI (DSA, kappa = 0.62-0.71; contrast-enhanced MR angiography, kappa = 0.57-0.69) than for objective measurements (DSA, kappa = 0.75-0.80; contrast-enhanced MR angiography, kappa = 0.66-0.72).

CONCLUSION

SVI alone is not recommended for evaluation of ICA stenosis with both DSA and contrast-enhanced MR angiography. SVI may be acceptable as an initial screening tool to exclude the presence of 70%-99% stenosis, but caliper measurements are warranted to confirm the presence of such stenosis.