Novel Use of Intracranial Arterial Pressure Waveforms to Detect Occlusive Events During Neuroendovascular Treatment

Abstract

BACKGROUND

Unexpected occlusive events, such as thrombosis, can cause serious complications during neuroendovascular treatment. Angiography provides only intermittent assessments, potentially missing rapidly developing occlusions, highlighting the need for continuous monitoring. This retrospective study assessed how accurately continuous monitoring of intracranial arterial pressure waveforms can detect occlusive events.

METHODS

We computed wavelet‐based time‐frequency amplitude of intracranial arterial pressure waveforms at frequencies ranging from 6 to 18 Hz in each of the 6444 trials obtained from 43 arteries in 37 patients. We determined whether modulation of this amplitude correctly classified the patent or occluded states defined by angiography.

RESULTS

Mixed‐model analysis revealed a significant increase in time‐frequency amplitude during occlusive events (P < 0.001). Receiver operating characteristic analysis indicated that an increase of ≥13.9% from baseline in the 6–18 Hz time‐frequency amplitude could detect occlusive events with a sensitivity of 88.5%, specificity of 87.5%, positive predictive value of 36.1%, and negative predictive value of 96.4%. A sustained increase of ≥14.3% for 5 or more consecutive trials could detect occlusive events with a sensitivity of 82.3%, specificity of 96.8%, positive predictive value of 75.5%, and negative predictive value of 94.8%.

CONCLUSIONS

Our preliminary study suggests that continuous intracranial arterial pressure monitoring holds promise as an adjunctive tool to accurately detect occlusive events. A prospective study is warranted to definitively establish its diagnostic value during neuroendovascular treatment.

Unexpected occlusive events during neuroendovascular treatment, such as thrombosis, can cause serious complications. ¹ , ² , ³ The incidence of thromboembolic complications during neuroendovascular treatment has been reported to range from 1% to 9%. ¹ , ² , ³ Early detection enables prompt intervention to minimize adverse outcomes. ⁴ , ⁵ , ⁶ , ⁷ Angiography is the current gold standard for evaluating intravascular conditions. However, it captures only brief periods during contrast injection, typically lasting a few seconds, and substantial intervals between imaging sessions remain unmonitored throughout the procedure. Providers of neuroendovascular treatment are encouraged to minimize contrast media and radiation exposure to reduce the risk of adverse events. ⁸ As a result, periods without angiographic assessment inevitably occur. Occlusions occurring during these intervals may remain undetected. Addressing these unmet needs thus requires continuous, real‐time intravascular monitoring capable of providing timely alerts precisely when angiographic confirmation of an occlusive event is necessary.

Intracranial arterial pressure (IAP) waveforms can be continuously measured via a catheter already placed for therapeutic purposes, thus requiring no additional invasive procedures. Characteristic morphological changes in IAP waveforms have been reported to reflect alterations in intravascular hemodynamics, which vary with peripheral resistance and stroke volume following arterial occlusion. ⁹ , ¹⁰ , ¹¹ Such waveform alterations can be quantified using time‐frequency analysis. ¹² , ¹³ Therefore, we tested the hypothesis that time‐frequency analysis of IAP waveforms can accurately differentiate occluded from patent states. Furthermore, we evaluated the predictive performance for detecting occluded states based on defined cutoff values.

METHODS

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Study Inclusion

We retrospectively studied patients who underwent neuroendovascular treatment for cerebral aneurysms (ruptured and unruptured), internal carotid artery stenosis, and parent artery occlusion at Kohnan Hospital (February–March 2022) and Iwaki City Medical Center (April–December 2022). Arteries with preexisting stenosis, occlusion, or pathological vascular shunts were excluded. ¹¹ , ¹⁴ , ¹⁵ The study was approved by the institutional review boards of Kohnan Hospital (2024‐1120‐07) and Iwaki City Medical Center (R6‐49) via an opt‐out procedure.

IAP Data Acquisition and Preprocessing

IAP was continuously measured using a pressure monitoring kit (Merit Medical Systems, South Jordan, UT, USA) connected to a guiding or angiographic catheter during stationary periods. Each time segment was classified as either patent or occluded based on angiographic findings. Patent states were defined as segments recorded between 2 angiographic assessments confirming patency. Occluded states included segments recorded between angiographic assessments confirming occlusion, or from the immediate period following complete balloon inflation until deflation.

IAP waveforms were filtered at 1–40 Hz and subdivided into trials corresponding to RR intervals derived from concurrently recorded ECG signals. Events containing ectopic beats were excluded. Continuous wavelet transform was applied to each IAP trial to obtain instantaneous time‐frequency amplitude values. For each trial, a specific integration window was defined (Methods S1). Within this window, time‐frequency amplitude values were integrated across 4 frequency bands (6–10 Hz, 10–14 Hz, 14–18 Hz, and 6–18 Hz). The spectral frequency band of interest was limited to 6–18 Hz because higher‐frequency components are prone to mechanical artifacts, whereas lower‐frequency components were considered unmeasurable in trials with short RR intervals. ¹² The diagnostic utility of these integrated values was subsequently evaluated.

Nonstandard Abbreviations and Acronyms

IAP

intracranial arterial pressure

CLINICAL PERSPECTIVE

What Is New?

• Continuous monitoring of intracranial arterial pressure waveforms enables accurate detection of arterial occlusion during neuroendovascular treatment.

What Are the Clinical Implications?

• This method allows clinicians to assess intracranial vascular status without relying solely on intermittent angiographic imaging.

• It has the potential to enhance procedural safety by facilitating real‐time detection of abrupt vascular changes.

Mixed‐Model Analysis

A mixed‐model analysis evaluated the impact of several fixed‐effect factors on the IAP time‐frequency amplitude of each of the 4 frequency bands. These fixed‐effect factors included artery occlusion state (occlusion versus patent), patient age, diagnosis of subarachnoid hemorrhage, IAP measurement trial order within each time segment, and effective luminal area of the catheter. The effective luminal area of the outer catheter used for IAP monitoring was calculated by subtracting the total cross‐sectional area of all coaxially inserted inner catheters from the cross‐sectional area of the outer catheter. Specifically, the cross‐sectional area of the outer catheter was computed using its inner diameter, and each inner catheter's cross‐sectional area was calculated using its outer diameter. All areas were computed using the formula π·(d/2)², where d represents the relevant diameter as specified by the manufacturer. Fixed‐effect variables included the diagnosis of subarachnoid hemorrhage, as it can alter arterial dynamics by increasing intracranial pressure and reducing cerebral perfusion, potentially influencing time‐frequency amplitude, ¹⁶ , ¹⁷ and the effective luminal area, as it was expected to directly affect focal arterial pressure and the IAP waveform. ¹⁸ , ¹⁹ To account for variability between arteries, both the sampled artery and intercept were included as random effects. Statistical significance was set at a Bonferroni‐corrected P value of <0.05.

Assessment of Diagnostic Performance of IAP Monitoring

Receiver operating characteristic (ROC) analysis was performed to assess how accurately the IAP‐based predictor variable could detect occlusion states as defined by angiography. The predictor variable was the percent change in time‐frequency amplitude from baseline, defined as the median value of the first 5 trials within each time segment. When the catheter's effective luminal area changed—for example, due to insertion or removal of a coaxial catheter—a new baseline was established. Diagnostic accuracy was assessed using a leave‐one‐artery‐out cross‐validation, determining optimal cutoff values by maximizing the Youden index within training sets. Classification metrics included the area under the ROC curve (AUROC), area under the precision–recall curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Detailed cross‐validation procedures and statistical tests are described in Methods S2.

All analyses were performed using MATLAB (R2024a, MathWorks, Natick, MA, USA; RRID: SCR_001622) and IBM SPSS Statistics (version 30, Armonk, NY, USA; RRID: SCR_002865).

RESULTS

Initially, 60 arteries from 52 patients were reviewed for eligibility. Ultimately, 43 arteries from 37 patients were included (Figure S1). The median patient age was 62 years (interquartile range: 50–71); 23 patients were female; 34 underwent endovascular treatment for cerebral aneurysms (ruptured in 19), 2 for neck internal carotid artery stenosis, and 1 for parent artery occlusion.

During endovascular treatment, occlusive events occurred in 14 of the 43 arteries: balloon occlusion of the parent artery (n = 9), coil occlusion of the parent artery (n = 3), and thrombotic occlusion (n = 2). A total of 124 time segments were identified, of which angiography classified 88 as patent states and 36 as occluded states. Of the 6461 RR intervals, 17 containing ectopic beats were excluded, leaving 6444 valid IAP trials (Figure S3). The median number of IAP measurement trials per time segment was 42.5 (interquartile range: 29.5–60.3). Further details are provided in Table 1 and Table S1.

Table 1.

Patient Profiles

Patient	Age	Sex	Occlusive events	Diagnosis	Target Lesion	Procedure
Pt 01	63	F	Yes	SAH	Rt. IC‐PC AN	Coil embolization
Pt 02	75	F	Yes	UIA	Lt. ICA lat. wall AN	BTO
Pt 03	50	M	Yes	UIA	Rt. IC‐PC AN	BAC
Pt 04	40	M	Yes	SAH	Rt. VA AN	PAO with coils
Pt 05	81	F	Yes	SAH	Rt. IC‐PC AN	BAC
Pt 06	72	F	Yes	UIA	Acom AN	Coil embolization
Pt 07	56	F	Yes	UIA	Lt. ICA lat. wall AN	BAC
Pt 08	59	F	Yes	UIA	Lt. IC‐Oph AN	BAC
Pt 09	78	F	Yes	SAH	Lt. VA AN	PAO with coils
Pt 10	40	F	No	SAH	Lt. ICA lat. wall AN	Coil embolization
Pt 11	74	F	No	SAH	Acom AN	Coil embolization
Pt 12	76	F	No	UIA	Lt. IC‐PC AN	Coil embolization
Pt 13	69	M	No	UIA	Rt. MCB AN	Coil embolization
Pt 14	51	M	No	UIA	Acom AN	Coil embolization
Pt 15	67	F	No	UIA	Lt. IC‐PC AN	Coil embolization
Pt 16	71	M	No	SAH	Acom AN	Coil embolization
Pt 17	67	M	No	SAH	Rt. IC‐PC AN	Coil embolization
Pt 18	54	M	No	SAH	Acom AN	Coil embolization
Pt 19	59	M	No	UIA	Rt. MCA AN	Coil embolization
Pt 20	71	M	No	ICS	Lt. cervical ICA	CAS
Pt 21	47	F	No	UIA	Acom AN	Coil embolization
Pt 22	65	F	No	UIA	Rt. IC‐PC AN	Coil embolization
Pt 23	49	F	No	SAH	Lt. IC‐PC AN	Coil embolization
Pt 24	62	F	Yes	UIA	Rt. MCB AN	BAC
Pt 25	48	F	Yes	SAH	Lt. ICA lat. wall AN	BAC
Pt 26	68	F	No	UIA	BA AN	Coil embolization
Pt 27	56	F	No	SAH	Acom AN	Coil embolization
Pt 28	47	M	No	SAH	Lt. ACA AN	Coil embolization
Pt 29	64	F	No	SAH	Acom AN	Coil embolization
Pt 30	75	M	No	ICS	Lt. cervical ICA	CAS
Pt 31	49	F	No	SAH	Lt. ICA lat. wall AN	Coil embolization
Pt 32	46	F	No	SAH	BA AN	Coil embolization
Pt 33	75	F	No	SAH	Lt. ICA lat. wall AN	Coil embolization
Pt 34	54	F	No *	VAO	Lt. VA	PAO with coils
Pt 35	43	M	Yes	SAH	Lt. VA AN	PAO with coils
Pt 36	55	M	No	SAH	Rt. VA AN	Coil embolization
Pt 37	69	M	Yes	UIA	Lt. ICA lat. wall AN	BAC

ACA indicates anterior cerebral artery; Acom, anterior communicating artery; AN, aneurysm; BA, basilar artery; BAC, balloon‐assisted coil embolization; BTO, balloon test occlusion; CAS, carotid artery stenting; F, female; ICA, internal carotid artery; IC‐Oph, internal carotid ophthalmic artery; IC‐PC, internal carotid–posterior communicating artery; ICS, internal carotid artery stenosis; lat. wall, lateral wall; Lt, left; M, male; MCA, middle cerebral artery; MCB, middle cerebral artery bifurcation; PAO, parent artery occlusion; Pt, patient; Rt, right; SAH, subarachnoid hemorrhage; UIA, unruptured intracranial aneurysm; VA, vertebral artery; and VAO, vertebral artery occlusion.

^*This patient had a history of left vertebral artery occlusion due to cervical spine fracture‐dislocation, and we performed additional occlusion of the parent artery to prevent thrombosis during an anticipated orthopedic reduction procedure. Therefore, we included only data from the right vertebral artery in the analysis.

No adverse events related to continuous IAP monitoring were noted. The Figure  illustrates snapshots of angiographic findings and IAP waveforms from a patient who underwent balloon‐assisted coil embolization of an unruptured intracranial aneurysm.

Mixed‐Model Analysis

Occluded state, IAP measurement trial order, and effective luminal area were each independently associated with increased time‐frequency amplitude on IAP waveforms across all 4 frequency bands analyzed (P<0.001; Table 2); these associations remained significant after Bonferroni correction (α = 0.0125). All pairwise correlation coefficients were <0.7, indicating no substantial multicollinearity among these fixed‐effect variables. Neither age nor diagnosis of subarachnoid hemorrhage had a significant effect on time‐frequency amplitude.

Table 2.

Result of Mixed‐Model Analysis

Occluded state
Frequency bands (Hz)	Estimate (mmHgs)	SE	Degrees of freedom	t value	P value	95% CI
						Lower	Upper
6–10	1.666	0.030	6416.051	55.596	<0.001	1.607	1.725
10–14	1.106	0.022	6426.183	49.377	<0.001	1.062	1.150
14–18	0.247	0.012	6422.845	20.767	<0.001	0.224	0.270
6–18	3.019	0.054	6418.070	55.421	<0.001	2.912	3.126

Intracranial arterial pressure measurement trial order
Frequency bands (Hz)	Estimate (mmHg s)	SE	Degrees of freedom	t‐value	P value	95% CI
						Lower	Upper
6–10	0.001	3.08×10−4	6408.657	4.816	<0.001	0.001	0.002
10–14	0.001	2.31×10−4	6415.826	4.578	<0.001	0.001	0.002
14–18	0.001	1.22×10−4	6413.366	5.079	<0.001	3.81×10−4	0.001
6–18	0.003	0.001	6409.990	5.638	<0.001	0.002	0.004

Effective luminal area of the catheter
Frequency bands (Hz)	Estimate (mmHg s)	SE	Degrees of freedom	t‐value	P value	95% CI
						Lower	Upper
6–10	0.645	0.021	6427.507	30.925	<0.001	0.604	0.686
10–14	0.467	0.016	6328.887	30.096	<0.001	0.437	0.498
14–18	0.322	0.008	6377.544	38.981	<0.001	0.306	0.338
6–18	1.435	0.038	6417.544	37.885	<0.001	1.361	1.509

Patient age
Frequency bands (Hz)	Estimate (mmHg s)	SE	Degrees of freedom	t‐value	P value	95% CI
						Lower	Upper
6–10	0.037	0.024	40.025	1.528	0.134	−0.012	0.085
10–14	0.030	0.013	40.022	2.236	0.031	0.003	0.057
14–18	0.019	0.008	40.184	2.428	0.020	0.003	0.035
6–18	0.085	0.041	40.031	2.095	0.043	0.003	0.168

Diagnosis of subarachnoid hemorrhage
Frequency bands (Hz)	Estimate (mmHg s)	SE	Degrees of freedom	t‐value	P value	95% CI
						Lower	Upper
6–10	0.389	0.579	39.965	0.673	0.505	−0.78	1.559
10–14	0.220	0.325	39.917	0.678	0.502	−0.436	0.877
14–18	0.114	0.189	40.095	0.605	0.548	−0.267	0.495
6–18	0.723	0.987	39.963	0.732	0.468	−1.273	2.718

Diagnostic Performance of IAP Monitoring

ROC analysis revealed that the 6–18 Hz time‐frequency amplitude provided the highest overall performance in detecting occlusive trials. Specifically, the mean Youden index averaged across 43 arteries was 0.67, with AUROC of 0.881 (P<0.001; 95% CI, 0.878–0.884), area under the precision–recall curve of 0.772 (P<0.001; 95% CI, 0.768–0.775), best cutoff of 13.9% increase (P<0.001; 95% CI, 13.8–14.1), sensitivity of 88.5% (P<0.001; 95% CI, 74.3–100), specificity of 87.5% (P<0.001; 95 %CI, 81.2–93.8), PPV of 36.1% (P = 0.09), and NPV of 96.4% (P<0.001; 95% CI, 93.0–99.8). The performance metrics of each time‐frequency amplitude predictor for individual arteries are presented in Tables S2–S5.

To assess whether brief fluctuations in time‐frequency amplitude were the primary cause of false‐positive detections in some occlusive trials, we conducted a post hoc ROC analysis. We hypothesized that a sustained increase in the 6–18 Hz time‐frequency amplitude—exceeding the cutoff for 5 consecutive trials—would improve PPV without negatively affecting other classification metrics. One time segment evaluating the left internal carotid artery in Patient 37 contained only 7 IAP measurement trials, making it impossible to assess sustained changes (≥5 trials); therefore, this time segment was excluded from the post hoc analysis.

The post hoc analysis indicated that using a sustained increase in time‐frequency amplitude reduced false‐positive detections, as evidenced by improved PPV. Specifically, the mean Youden index was 0.75, with a mean AUROC of 0.924 (P<0.001; 95% CI, 0.921–0.926), area under the precision–recall curve of 0.896 (P<0.001; 95% CI, 0.893–0.899), best cutoff of 14.3% increase (P<0.001; 95% CI, 14.2–14.4%), sensitivity of 82.3% (P<0.001; 95% CI, 64.8–99.9%), specificity of 96.8% (P<0.001; 95% CI, 92.9–100%), PPV of 75.5% (P = 0.027; 95% CI, 53.3–97.7%), and NPV of 94.8% (P<0.001; 95% CI, 90.4–99.3) (Table S6).

DISCUSSION

To our knowledge, this is the first study demonstrating that time‐frequency analysis of IAP waveforms can accurately detect occlusive events during neuroendovascular treatment. The duration of the endovascular procedure typically exceeded 2 hours across patients. Providers are generally advised to perform up to 40 angiographic imaging sessions per procedure. Even under this simplified assumption, the average interval between imaging sessions exceeds 3 minutes. Given that these intervals often span multiple minutes, transient vascular changes—such as abrupt occlusion—may go undetected. Therefore, we believe that our technique offers complementary diagnostic value by enabling continuous monitoring during clinically relevant gaps in intermittent angiography. Specifically, a sustained increase in the time‐frequency amplitude of IAP predicted occlusive trials with an AUROC of 0.924. Although these findings indicate that continuous IAP monitoring is promising for detecting occlusive events, a prospective study with a larger sample size is necessary to definitively confirm its diagnostic value. Our study is considered preliminary, as it was retrospectively conducted in a consecutive series of 37 patients who met eligibility criteria. Importantly, our results do not suggest that IAP monitoring could replace angiographic assessment; rather, they highlight its potential as an adjunctive tool to provide timely alerts precisely when angiographic confirmation of an occlusive event is needed. Given that most of the analyzed arteries were in the anterior circulation, further studies are needed to determine whether the reported diagnostic accuracy can be generalized to posterior circulation territories or adapted for use during other procedures such as flow diversion.

IAP waveforms reflect the dynamics of forward and reflected blood flows. ⁹ , ¹⁰ , ¹¹ , ¹⁵ The intensity and speed of reflected blood flow have been suggested to positively correlate with the reflection coefficient, effectively representing peripheral vessel resistance. ⁹ , ¹⁰ , ¹¹ , ¹⁵ Thus, the distinct notch observed on IAP waveforms, accompanied by increased time‐frequency amplitude (Figure 1B), likely reflects an earlier arrival of reflected blood flow resulting from arterial occlusion‐induced increases in vessel resistance.

Figure 1.

Changes inIAP waveforms associated with a transient arterial occlusion in Patient 05. Balloon‐assisted coil embolization was performed to treat an unruptured aneurysm in the left internal carotid artery. A, Angiographic image immediately before balloon inflation, showing a patent arterial state. B, Image after full balloon inflation, showing an occluded arterial state. C, Image following balloon deflation, returning to a patent state. Yellow arrowheads indicate the corresponding arterial region and the midpoint of balloon placement. Purple areas on intracranial arterial pressure waveforms and red dashed lines indicate the integration window used to calculate the continuous wavelet transform time‐frequency amplitude. The red circle on the fourth derivative of the IAP waveform marks its first trough. Note the clear augmentation of the continuous wavelet transform amplitude in the time‐frequency plot during the occluded state (B, bottom). CWT indicates continuous wavelet transform; and IAP, intracranial arterial pressure.

The strong performance of the 6–18 Hz band may reflect differences in patient heart rates. Narrower bands may not capture such variations as effectively (Tables S2–S5). The width of the notch depended on heart rate; higher rates produced a sharper notch, making the occlusion‐related increase in time‐frequency amplitude more pronounced in the higher‐frequency band. Therefore, we plan to use the 6–18 Hz time‐frequency amplitude in the next prospective study to more definitively evaluate the diagnostic utility of continuous IAP monitoring for detecting arterial occlusive events.

The results of our mixed‐model analysis indicate that capturing the relative increase in IAP time‐frequency amplitude over time may be more important than absolute amplitude values. Reductions in the effective luminal area significantly decreased the time‐frequency amplitude. This suggests that inserting additional coaxial catheters diminishes waveform magnitude. ¹⁸ , ¹⁹ Therefore, when changes in the effective luminal area occur, recalibrating the baseline IAP time‐frequency amplitude is recommended to optimally detect occlusive events.

We found no evidence suggesting IAP monitoring is challenging in patients with subarachnoid hemorrhage. No adverse events were observed in any of the study patients. Our mixed‐model analysis found no significant effect of subarachnoid hemorrhage diagnosis on IAP time‐frequency amplitude. Although elevated intracranial pressure reportedly influences cerebral perfusion, ¹⁶ , ¹⁷ we successfully performed continuous IAP monitoring and detected increases in time‐frequency amplitude associated with transient arterial occlusion (Table S6).

Later trials were associated with increased time‐frequency amplitude within the given time segments, although the effect was modest (0.003 mmHg·s per trial number in 6–18 Hz band; Table 2). One possible explanation is slowly developing vasospasm caused by endovascular manipulations, such as adjustments of catheters or balloons. Nonetheless, this trial effect may be clinically negligible, given that the magnitude of time‐frequency amplitude increase associated with arterial occlusion was 3.019 mmHg·s.

The reported low PPV (36.1%) in the per‐trial analysis is primarily due to false positive detections unrelated to true occlusive events. These false positives likely result from frequent, intrinsic fluctuations in the IAP waveform, which can produce transient time‐frequency amplitude augmentations that mimic true occlusive events. We also evaluated the PPV using a more stringent detection criterion: an event was classified as occlusive only when the time‐frequency amplitude augmentation persisted across at least 5 consecutive trials. This stricter threshold substantially reduced the false positive rate and improved the PPV to 75.5%, while modestly reducing the sensitivity from 88.5% to 82.3%. Furthermore, the study design, in which 29 of the 43 study arteries did not exhibit true occlusive events, also contributed to the relatively low PPV. Even when using diagnostic tools with high sensitivity and specificity, including a substantial number of patients or assessments without true positive events can reduce the PPV, as false positives comprise a larger proportion of the positive detections. ²⁰

The validity of angiographic examinations as the gold standard for defining arterial occlusion events warrants discussion. Angiography provides intermittent assessments; thus, we had to assume that the intravascular state (occluded or patent) remained stable between consecutive angiographic examinations. Angiography may fail to detect transient thrombosis‐related occlusions occurring between evaluations or transient recanalization immediately following documented occlusions. Figure S3 illustrates dynamic modulations of IAP time‐frequency amplitude in Patient 01, who experienced a thrombotic event during neuroendovascular treatment. This patient was 1 of 2 patients in whom the accuracy of IAP‐based occlusion detection was suboptimal. Figures S3C, S3J, and S3K demonstrate fluctuations in IAP time‐frequency amplitude even during angiographically defined occlusion states. We cannot rule out arterial instability due to fluctuating thrombotic conditions. After recognizing this occlusive event on angiography, fasudil hydrochloride and ozagrel sodium were administered. Subsequent angiograms revealed alternating patent and occluded states, supporting our suspicion of rapid intravascular changes. Eventually, the thrombus resolved completely without neurological deficits. This anecdotal observation led us to hypothesize that continuous IAP time‐frequency analysis could serve as an adjunctive tool, providing real‐time insights into rapidly changing intravascular conditions.

Sources of Funding

This study was funded by JSPS KAKENHI Grants 19K18376 and 25K19895.

Disclosures

None.

Supporting information

Supplementary Figure 1: Patient inclusion flow diagram.

Supplementary Figure 2: RR interval inclusion flow diagram.

Supplementary Figure 3: Dynamic modulation of time‐frequency amplitude in the 6–18 Hz band in Patient 01.

Supplementary Table 1: Detailed characteristics of sampled arteries and segments.

Supplementary Table 2: Detection performance of occlusive events in the 6–18 Hz frequency band.

Supplementary Table 3: Detection performance of occlusive events in the 6–10 Hz frequency band.

Supplementary Table 4: Detection performance of occlusive events in the 10–14 Hz frequency band.

Supplementary Table 5: Detection performance of occlusive events in the 14–18 Hz frequency band.

Supplementary Table 6: Detection performance of occlusive events in the 6–18 Hz frequency band (post hoc analysis).

Data Availability Statement

The data analyzed during this study are available from the corresponding author upon reasonable request.