Lipid-lowering Therapy and Coronary Plaque Regression

Abstract

Lipid-lowering therapy plays a central role in reducing cardiovascular events. Over the past few decades, clinical trials utilizing several imaging techniques have consistently shown that lipid-lowering therapy can reduce the coronary plaque burden and improve plaque composition. Although intravascular ultrasound has been the most extensively used modality to assess plaque burden, other invasive modalities, such as optical coherence tomography and near-infrared spectroscopy, provide relevant data on plaque vulnerability, and computed tomography angiography detects both plaque volume and characteristics non-invasively. A large body of evidence supports the notion that reducing low-density lipoprotein cholesterol using statins combined with ezetimibe and proprotein convertase subtillisin/kexin type 9 inhibitors consistently shows improvements in plaque burden and favorable morphological changes. This review summarizes previously obtained data on the impact of lipid-lowering treatment strategies on atherosclerotic plaque regression, as assessed using several imaging modalities.

Introduction

Low-density lipoprotein cholesterol (LDL-C) is a key causal factor in the pathophysiology of atherosclerotic cardiovascular disease (ASCVD). Epidemiological studies have consistently demonstrated a dose-dependent relationship between plasma LDL-C concentrations and risk of ASCVD¹⁾. In addition to the magnitude of the LDL-C level, long-term exposure to persistently elevated LDL-C is recognized as a major contributor to an individual’s ASCVD risk²⁾.

Lipid-lowering therapy, primarily the management of LDL-C levels, is central to ASCVD prevention. The degree of benefit is directly associated with the extent of LDL-C reduction by intensive statin therapy as monotherapy and in combination with ezetimibe and proprotein convertase subtilisin kexin type 9 (PCSK9) inhibitors³⁾. Beneficial effects on coronary plaque volume and composition derived by lipid-lowering therapy has been considered a key mechanism of cardiovascular risk reduction. Over the past few decades, several invasive and non-invasive imaging modalities have been applied in a number of clinical trials to assess the effect of lipid-lowering therapy on coronary plaque burden and local plaque characteristics.

In this review, we summarize previously obtained data on the impact of lipid-lowering treatment strategies on atherosclerotic plaque regression, as assessed by several imaging modalities.

Mechanisms Underlying Plaque Formation and Progression

Plaque formation is a complex, multifactorial, and multistep process that typically persists for years or decades. In particular, in the presence of endothelial dysfunction that results from continuous exposure to several pathogenic risk factors, such as hypertension, dyslipidemia, diabetes mellitus, and smoking, lipoprotein particles such as LDL-C cross the endothelial barrier and remain in the arterial wall^4-6). Recruitment of inflammatory cells induced by oxidative stress promotes the uptake of modified lipoprotein particles by macrophages and the development of foam cells. The accumulation of foam cells arising from lipid-laden macrophages and smooth muscle cell proliferation result in fibrous cap formation and plaque growth. Inflammatory cell infiltration, smooth muscle cell death, and matrix degradation lead to a vulnerable plaque with a thin fibrous cap and lipid-rich necrotic core.

Atherosclerosis is generally considered to be a chronic progressive disease that may be complicated by several ischemic events. The size of the total atherosclerotic plaque burden is likely to be proportional to both the concentration of circulating LDL-C and other ApoB-containing lipoproteins and the total duration of exposure to these lipoproteins²⁾. There are several stages of plaque progression, including subclinical atherosclerosis (intimal thickening and intimal xanthoma), vulnerable plaques that may cause thrombotic events, and stable plaques with calcification. Vulnerable plaques are generally characterized by an increased plaque burden, positive remodeling, a large lipid core covered by a thin fibrous cap, macrophage accumulation, and neovascularization⁷⁾.

Plaque Regression and its Impact on Clinical Outcomes

Plaque regression has traditionally been defined as an increase in luminal diameter by coronary angiography as a surrogate marker of plaque size reduction⁸⁾. However, recent advances in plaque imaging modalities have enabled not only a direct assessment of atherosclerotic plaque burden but also plaque composition. In addition to plaque burden, an established surrogate measure using intravascular ultrasound (IVUS) for future cardiovascular events, the plaque component is also a relevant determinant of plaque-related ischemic events. In this context, plaque regression can be defined as favorable changes in plaque morphology including atheroma volume and components that reduce the subsequent risk of cardiovascular events⁹⁾. In daily practice, plaque regression characterized by the reduction of plaque volume and change from unstable plaque with high-risk features to stable calcified plaque is often observed after intensive primary/secondary prevention.

The clinical relevance of plaque regression has been addressed by previous meta-analyses^{10, 11)}. A recent meta-regression analysis synthesizing 23 studies of lipid-lowering therapy reporting changes in percent atheroma volume by IVUS and clinical outcomes has demonstrated a significant association between plaque regression and reduction in cardiovascular events¹²⁾. Among 7407 patients with trial durations ranging from 11 to 104 weeks, an adjusted analysis revealed that a 1% decrease in the mean percent atheroma volume (PAV) was associated with a 14% reduced odds of major adverse cardiovascular endpoints (MACE) (adjusted odds ratio: 0.86, 95% confidence interval [CI]: 0.68-0.96, P=0.01). These results suggest that changes in the PAV may be a surrogate marker for cardiovascular events and thus may highlight the clinical relevance of temporal assessment of coronary plaques to more accurately guide decisions on titration of lipid-lowering treatment.

Plaque Assessment by Imaging Modalities

Several invasive and non-invasive imaging modalities have been used to assess plaque burden and components in previous clinical studies. The characteristics of each imaging modality used for the assessment of coronary plaques are summarized in Fig.1.

Fig.1. Characteristics of imaging modalities for assessing coronary plaques.

CTA, computed tomography angiography; FCT, fibrous cap thickness; IVUS, intravascular ultrasound; LCBI, lipid core burden index; NA, not available; NIRS, near-infrared spectroscopy; OCT, optical coherence tomography; PAV, percent atheroma volume; TAV, total atheroma volume.

Invasive Imaging

IVUS imaging is based on ultrasound waves produced by the oscillatory movement of a transducer and uses differences in reflections by various arterial structures to generate cross-sectional images of the arterial wall and lumen. IVUS has a resolution of 100–150 µm and a penetration depth of 4–8 mm. By detecting both lumen and vessel contours, IVUS can provide the plaque burden (plaque area=vessel area – lumen area). Thus, IVUS has been the major invasive modality for assessing atherosclerotic plaques and is currently considered the gold standard for plaque quantification. IVUS-derived outcome measures include the PAV, calculated using the following formula:

$\mathrm{\text{PAV}}=\frac{\mathrm{\Sigma }({\mathrm{\text{EEM}}}_{\mathrm{\text{area}}}-{\mathrm{\text{lumen}}}_{\mathrm{\text{area}}})}{{\mathrm{\Sigma }\mathrm{\text{EEM}}}_{\mathrm{\text{area}}}}\times 100,$

where EEM_area=external elastic membrane area, and total atheroma volume (TAV), calculated as the sum of the differences between EEM and lumen areas across all evaluable frames (i.e. Σ[EEM_area − lumen_area]). Owing to its limited resolution, IVUS cannot reliably assess the fibrous cap thickness and detailed plaque components. A previous study using computed tomography angiography (CTA) data reported that, compared with the TAV and normalized TAV, the PAV was less strongly affected by body surface area and may be an optimal variable to quantify coronary atherosclerosis burden¹³⁾. Plaque composition has been assessed with several post-processing methods using spectral analyses of radiofrequency backscatter data, such as virtual histology (VH)-IVUS, integrated backscatter (IB)-IVUS, and iMAP. VH-IVUS has been the most commonly used method in previous plaque regression studies and provides information on plaque components, including necrotic core, dense calcium, fibrous, and fibrofatty tissue¹⁴⁾. Although VH-IVUS-derived thin-cap fibroatheroma (TCFA) has been used as a high-risk characteristic for future cardiovascular events¹⁵⁾, its diagnostic ability compared with optical coherence tomography (OCT) is reportedly lower due to its limited resolution¹⁶⁾. These modalities are thus no longer used in current daily practice.

OCT imaging is obtained using near-infrared light and offers greater resolution (10-20 µm) than IVUS, providing more detailed images of superficial arterial wall microstructures, including fibrous cap thickness, macrophages, ulcers, and thrombi. OCT-derived TCFA, a high-risk plaque characteristic prone to acute coronary events, is usually defined as a fibrous cap thickness of ＜65 µm¹⁷⁾. Major OCT-derived outcome measures include minimum fibrous cap thickness (FCT), macrophage angle, and lipid arc. However, owing to low tissue penetration (i.e. maximum of 2 mm), OCT cannot accurately measure the plaque burden and vessel size, especially in lipid-rich tissues.

Near-infrared spectroscopy (NIRS) uses a spectroscopic analysis of backscattered light and provides information on the cholesterol content in the arterial wall. Combining NIRS with IVUS facilitates an accurate and objective assessment (i.e. less operator-dependent) of lipid-rich plaques with visualization of the lumen and plaque. The amount of lipid is described as the lipid-core burden index (LCBI), calculated by dividing the number of yellow pixels by the total number of pixels available, multiplied by 1000 (ranging from 0 to 1000)¹⁸⁾. The maxLCBI_4mm is usually used to quantify the maximal regions of lipid-rich plaques within the interventional target region, divided into 4-mm coronary segments. A previous imaging study reported that NIRS-derived lipid-rich plaques were strongly associated with high-risk plaque features on IVUS and OCT¹⁹⁾.

Non-Invasive Imaging

Coronary CTA is a non-invasive modality that can quantitatively assess coronary stenoses and plaques. CTA classifies plaque type into low attenuation, fibro-fatty, fibrous, and calcified plaques according to Hounsfield units²⁰⁾. The qualitative features of high-risk plaques detected by CTA include low attenuation plaque, positive remodeling, spotty calcification, and napkin ring sign²¹⁾. In contrast to intracoronary imaging that can visualize only imaged segments, CTA can provide whole coronary tree information, including stenoses, plaque volume, and plaque components. Recently, CTA has been shown to enable visualization of pericoronary adipose tissue attenuation, which reflects the degree of coronary artery inflammation²²⁾. The limitations of CTA include a lower resolution than intracoronary imaging and imaging artefacts, such as motion and beam hardening, which can result in misclassification of plaque components.

Other non-invasive modalities include cardiac magnetic resonance (CMR) and positron emission tomography (PET). CMR can detect coronary stenoses and characterize the vessel wall, including positive remodeling²³⁾. However, due to its limited spatial resolution and time-consuming nature, CMR is not routinely used for coronary assessment in daily practice, and there are no studies examining coronary plaque regression. PET can detect coronary plaque inflammation and calcification using radioligands (e.g. 18F-fluorodeoxyglucose [18F-FDG] and 18F-sodium fluoride)²⁴⁾. Due to the uptake of 18F-FDG at myocardium, the resolution to assess inflammation in coronary plaques is limited. The novel radiotracer 18F-sodium fluoride that binds to vascular microcalcifications showed good diagnostic ability in identifying culprit lesions and vulnerable plaques when combined with CT or CMR^{25, 26)}.

Effect of Lipid-Lowering Therapy on Coronary Plaque

Numerous imaging studies have assessed the effect of lipid-lowering therapy on coronary plaques and provided a mechanistic rationale for the cardiovascular benefits of lipid-lowering therapy. The relationship between the achieved LDL-C level and plaque regression in previous pharmacological trials (statins, ezetimibe, and PCSK9 inhibitors) is summarized in Fig.2 (Supplementary Tables 1 and 2 for full study details). Although substantially heterogeneous across studies according to study design (e.g. baseline lipid management, length of follow-up, patient presentation, baseline plaque burden) and drugs investigated, favorable changes in the PAV (-5.7% to +0.9%), TAV (-26.1% to +0.2%), minFCT (+7.7 µm to +110.1 µm), and maxLCBI4mm (-149.1 to -5.2) were demonstrated in previous randomized controlled trials (RCTs) and observational studies (Fig.2).

Fig.2. Correlation between plaque variables by intracoronary imaging and achieved LDL-C.

Bubble plot showing the change in the PAV (A), % change in the TAV (B), change in minimum FCT (C), and change in maxLCBI_4mm (D) (y-axis) in comparison with the achieved LDL-C (x-axis) in the treatment arms of major plaque regression trials (control arms are not shown). The bubble size was proportional to the number of patients in the treatment arm. FCT, fibrous cap thickness; LCBI, lipid core burden index; LDL-C, low-density lipoprotein cholesterol; PAV, percent atheroma volume; TAV, total atheroma volume.

Supplementary Table 1.Summary of plaque regression trials utilizing IVUS

Study name	Year	Study design	Follow-up Period	Presentation	Treatment	Sample size	LDL BL (mg/dL)	LDL FUP (mg/dL)	PAV BL (%)	PAV FUP (%)	Change in PAV (%)	TAV BL (mm3)	TAV FUP (mm3)	%change in TAV (%)
Statin
GAIN1	2001	RCT	1 year	CCS	Atorvastatin 20-80mg	48	155	86	NA	NA	NA	121.3	NA	+2.5
					Usual care	51	166	140	NA	NA	NA	104.7	NA	+11.8
ESTABLISH2	2004	RCT	6 months	ACS	Atorvastatin 20mg	24	125	70	NA	NA	NA	69.6	61.4	-13.1
					Usual care	24	124	119	NA	NA	NA	59.5	63.7	+8.7
REVERSAL3	2004	RCT	18 months	CAD	Atorvastatin 80mg	253	150	79	38.4	39	+0.6	184.4	183.9	-0.4*
					Pravastatin 40mg	249	150	110	39.5	41.4	+1.9	194.5	199.6	+2.7*
Kawasaki et al.4	2005	RCT	6 months	CCS	Atorvastatin 20mg	17	155	95	NA	NA	NA	159.2	155.4	-2.4‡
					Pravastatin 20mg	18	149	102	NA	NA	NA	166.2	164.6	-1.0‡
					Dietary stabilization	17	152	149	NA	NA	NA	159	159	0‡
Yokoyama et al.5	2005	RCT	6 months	CCS	Atorvastatin 10mg	29	133	87	NA	NA	NA	69.9	66	-5.6‡
					Dietary modification	30	NA	NA	NA	NA	NA	55.8	53.8	-3.6‡
Tani et al.6	2005	RCT	6 months	CCS	Pravastatin 10-20mg	52	130	104	NA	NA	NA	47	40	-14
					Non-statin	23	123	120	NA	NA	NA	44	44	+1.1
ASTEROID7	2006	Observational	1 year	CCS	Rosuvastatin 40mg	349	130	61	39.6	38.6	-0.98	212.2†	197.5†	-6.7†
COSMOS8	2009	Observational	76 weeks	CCS/UAP	Rosuvastatin 2.5-20mg	126	140	83	NA	NA	NA	72.1	66.8	-5.1
JAPAN-ACS9	2009	RCT	1 year	ACS	Pitavastatin 4mg	125	131	81	49.4	43.7	-5.7	49.8	41.6	-16.9
					Atorvastatin 20mg	127	134	84	50.5	44.3	-6.3	63.9	53.3	-18.1
Toi et al.10	2009	RCT	2-3 weeks	ACS	Pitavastatin 2mg	80	115	75	NA	NA	NA	NA	NA	-2.6
					Atorvastatin 10mg	80	122	85	NA	NA	NA	NA	NA	+0.2
Hong et al.11	2009	RCT	1 year	CCS/ACS	Rosuvastatin 10mg	50	116	64	NA	NA	NA	91.5	87.8	-4.0‡
					Simvastatin 20mg	50	119	78	NA	NA	NA	88.3	86.3	-2.2‡
Nasu et al. 12	2009	Observational	1 year	CCS	Fluvastatin 60mg	40	145	98	NA	NA	NA	440.2	403.8	-8.3‡
					Lipid-lowering diet	39	122	121	NA	NA	NA	432.9	443.7	+2.5‡
ARTMAP13	2011	RCT	6 months	CCS/ACS	Atorvastatin 20mg	143	110	56	42.3	43	-0.3	215	205	-3.9
					Rosuvastatin 10mg	128	109	53	43.3	42.3	-1.1	229	210	-7.4
SATURN14	2011	RCT	104 weeks	CAD	Atorvastatin 80mg	519	120	70	36	34.9	-0.99	144	139	-4.0‡
					Rosuvastatin 40mg	520	120	63	36.7	35.4	-1.22	144	136	-5.8‡
Hong et al. 15	2011	RCT	11 months	CCS/ACS	Rosuvastatin 20mg	65	122	62	48	47.3	-0.73	166	162	-2.4‡
					Atorvastatin 40mg	63	117	70	49.9	49.7	-0.19	190	186	-2.1‡
Guo et al. 16	2012	RCT	3-6 months	CCS	Atorvastatin 80mg	39	108	70	NA	NA	NA	36.5	25	-31.5‡
					Atorvastatin 40mg	43	112	72	NA	NA	NA	37.1	30.7	-17.3‡
					Atorvastatin 20mg	45	113	78	NA	NA	NA	33.8	36.1	+6.8‡
					Atorvastatin 10mg	47	117	91	NA	NA	NA	38.1	38.1	0‡
					Placebo	54	114	115	NA	NA	NA	34.8	37.5	+7.8‡
TRUTH17	2012	RCT	8 months	CCS/UAP	Pitavastatin 4mg	58	126	74	55.2	55	-0.2	NA	NA	-1.9
					Pravastatin 20mg	61	137	95	53.9	54.1	+0.2	NA	NA	-0.6
VENUS18	2012	RCT	6 months	CCS	Atorvastatin 40mg	20	112	52	51.6	50.1	-1.5	144.2	137.9	-4.4
					Atorvastatin 10mg	19	122	69	49.9	50.2	+0.4	98.5	94.6	-3.9
Hwang et al. 19	2013	Observational	6 months	ACS	Statin	54	120	67	NA	NA	NA	76.1	73.2	-2.9
YELLOW20	2013	Observational	7 weeks	CCS	Rosuvastatin 40mg	44	79	58	NA	NA	NA	195.8†	209.6†	+7.0
					Standard	43	83	82	NA	NA	NA	197.3†	199.6†	+1.2
Zhang et al. 21	2013	RCT	9 months	UAP	Atorvastatin 80mg	32	106	62	NA	NA	NA	43.2	41.7	-3.5‡
					Atorvastatin 20mg	30	106	80	NA	NA	NA	42.3	50.7	+19.9‡
IBIS-4 22	2015	Observational	13 months	STEMI	Rosuvastatin 40mg	82	128	74	44.0	43.0	-0.9	258.3	245.1	-5.1‡
YOKOHAMA- ACS23	2016	RCT	10 months	ACS	Atorvastatin 20mg	26	135	72	50.2	46.6	-3.6	70.3	63	-11.1
					Pitavastatin 4mg	26	140	78	44.1	41.2	-2.9	62.5	57.4	-8.1
					Pravastatin 10mg	25	152	107	46	47.5	+1.5	74.5	75.7	+0.4
					Fluvastatin 30mg	25	139	103	44.7	45.1	+0.4	56.2	55	+3.1
ALTAIR24	2016	RCT	48 weeks	CCS	Rosuvastatin 20mg	17	130	62	NA	NA	NA	56.5	53.4	-5.1
					Rosuvastatin 2.5mg	19	131	90	NA	NA	NA	58.1	59.3	+3.8
STABLE25	2016	RCT	1 year	CCS/ACS	Rosuvastatin 40mg	152	105	59	NA	NA	-0.88	NA	NA	-14.7†
					Rosuvastatin 10mg	73	109	79	NA	NA	-0.85	NA	NA	-13.6†
PREDICT26	2017	Observational	1 year	CCS + DM	Rosuvastatin 40mg	17	94	82	45.7	46.4	+0.7	NA	NA	NA
				CCS non-DM	+Rosuvastatin 40mg	44	95	70	44.6	43.2	-1.4	NA	NA	NA
YELLOW II27	2017	Observational	8-12 weeks	CCS	Rosuvastatin 40mg	85	87	51	60.7	61.0	+0.3	182.3	182.7	+0.2‡
Thondapu et al. 28	2019	RCT	1 year	CCS/ACS	Rosuvastatin 10mg	24	100	76	52.5	51.3	-1.2	109.2	102.5	-6.1‡
					Atorvastatin 20mg	19	115	80	54.5	54.4	-0.1	83.3	77.9	-6.5‡
Ezetimibe
HEAVEN29	2012	RCT	1 year	CCS	Atorvastatin 80mg+ ezetimibe 10mg	42	128	77	46.7	46.3	-0.4	NA	NA	NA
ZEUS30	2014	Observational	24 weeks	ACS	Atorvastatin 20mg + Ezetimibe 10mg	50	116	57	NA	NA	NA	75.1	66.9	-12.5
					Atorvastatin 20mg	45	114	70	NA	NA	NA	76.5	70.3	-7.5
PRECISE-IVUS31	2015	RCT	9-1 months	2CCS/ACS	Atorvastatin + Ezetimibe 10mg	100	110	63	51.3	49.3	-1.4*	72.6*	69.6*	-5.2*
					Atorvastatin	102	108	73	50.9	50.4	-0.3*	76.3*	77.3*	-1.3*
Masuda et al. 32	2015	RCT	6 months	CCS	Rosuvastatin 5mg + Ezetimibe 10mg	21	132	57	52.5	46.9	-5.6	55.3	47.1	-13.2
					Rosuvastatin 5mg	19	123	75	46.4	45.7	-0.7	43.5	40.9	-3.1
OCTIVUS33	2016	RCT	1 year	STEMI	Atorvastatin 80mg+Ezetimibe 10mg	39	143	54	40.1	39.2	-0.9	200*	189.3*	-5.4
					Atorvastatin 80mg + Placebo	41	159	77	43.4	42.2	-1.1	218.4*	212.2*	-2.8
ZIPANGU34	2017	RCT	9 months	CCS	Atorvastatin 10-20mg + Ezetimibe 10mg	49	101	61	50.0	49.3	-0.7	NA	NA	NA
					Atorvastatin 10-20mg	51	101	75	48.5	48.2	-0.3	NA	NA	NA
Hibi et al. 35	2018	RCT	10 moths	ACS	Pitavastatin 2mg + Ezetimibe 10mg	50	123	64	44.3	42.9	-1.5	233	222	-5.1
					Pitavastatin 2mg	53	126	87	43.9	42	-1.9	251	240	-6.2
Oh et al. 36	2021	RCT	1 year	CCS	Atorvastatin 10mg + Ezetimibe 10mg	18	107	61	45.9	42.7	-2.9	69.6*	66.2*	-4.9
					Atorvastatin 40mg	19	101	58	44.8	41	-3.2	79.6*	76.9*	-3.4
PCSK9 inhibitors
GLAGOV37	2016	RCT	78 weeks	CAD	Evolocumab 420mg/ month	423	93	37	36.4	35.6	-0.95	187†	181.5†	-2.9†
					Placebo	423	92	93	37.2	37.3	+0.05	191.4†	190.6†	-0.4†
ODYSSEY J-IVUS38	2019	RCT	36 weeks	ACS	Alirocumab 75-150mg every 2 weeks	93	98	35	44.4	NA	-1.3	124.2	NA	-5.4
					Atorvastatin ≥10 mg/day or Rosuvastatin ≥5 mg/ day	89	96	80	44	NA	-1.4	131.6	NA	-4.8
HUYGENS39	2022	RCT	52 weeks	NSTEMI	Evolocumab 420mg/ month	40	140	28	45.8	43.1	-2.29	244.3	204.1	-16.4
					Placebo	39	142	87	45.1	43.9	-0.61	244.7	240	-1.9
PACMAN-AMI40	2022	RCT	1 year	AMI	Alirocumab 150mg/2weeks	130	154	24	40.9	38.8	-2.1	261.4†	235.3†	-26.1†
					Placebo	135	151	74	43	42.1	-0.9	250.4†	235.4†	-15†

ACS = acute coronary syndrome, AMI = acute myocardial infarction, BL = baseline, CAD = coronary artery disease, CCS = chronic coronary syndrome, DM = diabetes mellitus, FUP = follow-up, LDL = low-density lipoprotein, NA = not available, NSTEMI = non-ST elevation myocardial infarction, PAV = percent atheroma volume, PCSK9 = proprotein convertase subtilisin kexin type 9, RCT = randomized controlled trial, STEMI = ST elevation myocardial infarction, TAV = total atheroma volume, UAP = unstable angina pectoris.

^*median value, ^†normalized TAV, ^‡calculated from the reported values.

Supplementary Table 2.Summary of plaque regression trials utilizing OCT and NIRS-IVUS

Study name	Year	Study design	Modality	Follow-up Period	Presentation	Treatment	Sample size	LDL BL (mg/dL)	LDL FUP (mg/dL)	Min FCT BL (μm)	Min FCT FUP (μm)	ΔMin FCT (μm)	Max LCBI4mm BL	Max LCBI4mm FUP	ΔMax LCBI4mm BL
Statin
YELLOW20	2013	Observational	NIRS- IVUS	7 weeks	CCS	Rosuvastatin 40mg	36	82	58	NA	NA	NA	490.6＊	336.1＊	-149.1＊
						Standard	34	83	82	NA	NA	NA	356.7＊	385.7＊	+2.4＊
EASY-FIT41	2014	RCT	OCT	1 year	UAP	Atorvastatin 20mg	30	127＊	69＊	105＊	174＊	+73	NA	NA	NA
						Atorvastatin 5mg	30	117＊	78＊	117＊	132＊	+19	NA	NA	NA
IBIS-4 42	2015	Observational	OCT	13 months	STEMI	Rosuvastatin 40mg	83	128	74	64.9	87.9	+24.4	NA	NA	NA
YELLOW II27	2017	Observational	OCT NIRS- IVUS	8-12 weeks	CCS	Rosuvastatin 40mg	85	87	51	100.9	108.6	+7.7	416.6	400.2	-16.4
ESCORT43	2018	RCT	OCT	36 weeks	ACS	Pitavastatin 4mg	25	117＊	67＊	140＊	230＊	NA	NA	NA	NA
						Pitavastatin 4mg from 3weeks after baseline	28	118＊	76＊	135＊	200＊	NA	NA	NA	NA
Thondapu et al. 28	2019	RCT	OCT	1 year	CCS/ACS	Rosuvastatin 10mg	24	100	76	61.4	171.5	+110.1	NA	NA	NA
						Atorvastatin 20mg	19	115	80	60.8	127	+66.2	NA	NA	NA
Ezetimibe
Oh et al. 36	2021	RCT	NIRS- IVUS	1 year	CCS	Atorvastatin 80mg+Ezetimibe 10mg	39	143	54	NA	NA	NA	95	91	-5.2
						Atorvastatin 80mg + Placebo	41	159	77	NA	NA	NA	100	104	2.2
PCSK9 inhibitors
HUYGENS39	2022	RCT	OCT	52 weeks	NSTEMI	Evolocumab 420mg/month	56	140	28	56.6	100.6	+39.0＊	NA	NA	NA
						Placebo	63	142	87	54.6	81.7	+22.0＊	NA	NA	NA
PACMAN-AMI40	2022	RCT	OCT NIRS- IVUS	1 year	AMI	Alirocumab 150mg/2weeks	122 (OCT) 129 (NIRS)	154	24	107	169.6	+62.7	260.6	181.2	-79.4
						Placebo	133 (OCT) 134 (NIRS)	151	74	110.5	143.7	+33.2	276.2	238.6	-37.6

ACS = acute coronary syndrome, AMI = acute myocardial infarction, BL = baseline, CCS = chronic coronary syndrome, FCT = fibrous cap thickness, FUP = follow-up, IVUS = intravascular ultrasound, LCBI = lipid core burden index, LDL = low-density lipoprotein, NA = not available, NIRS = near infrared spectroscopy, NSTEMI = non-ST elevation myocardial infarction, OCT = optical coherence tomography, PCSK9 = proprotein convertase subtilisin kexin type 9, RCT = randomized controlled trial, STEMI = ST elevation myocardial infarction, UAP = unstable angina pectoris.

^＊median value.

Statins

Statins reduce cholesterol synthesis in the liver by inhibiting HMG-CoA reductase. The reduction in intracellular cholesterol promotes LDL receptor expression at the hepatocyte surface, resulting in an increased uptake of LDL-C from the blood and decreased plasma concentrations of LDL- and other ApoB-containing lipoproteins, including triglyceride (TG)-rich particles. Although the degree of LDL-C reduction is dose-dependent with considerable inter-individual variation in LDL-C reduction, statins generally reduce LDL-C levels by approximately 30% to 50%²⁷⁾.

Several studies have investigated the effects of statins on coronary plaques. Most of these studies used IVUS to assess changes in plaque burden, and VH-IVUS, OCT, and NIRS have been used to assess plaque composition. The degree of plaque regression correlates with the extent of LDL-C reduction, similar to the association between ischemic risk reduction and serum LDL-C levels²⁸⁾.

In 1997, Takagi et al. first reported a beneficial effect of statins on coronary plaques as assessed by IVUS²⁹⁾. Patients treated with pravastatin 10 mg (n=13) had a significant reduction in plaque area at 36 months compared with patients treated with dietary stabilization alone (n=12) (% change in plaque area: -7±23 vs. +41±23, P＜0.0005). Since then, numerous clinical trials have been conducted to investigate the effects of lipid-lowering therapy on coronary plaques. Greater plaque volume reduction induced by high-intensity statins versus low-intensity statins has been consistently demonstrated in a number of previous RCTs. The REVERSAL trial in 2004 reported that atorvastatin 80 mg compared with pravastatin 40 mg reduced progression of coronary atherosclerosis by IVUS at 18 months among 654 patients with coronary artery disease (CAD) (% change in TAV: -0.4% vs. +2.7%; P=0.02)³⁰⁾. The SATURN trial in 2011 compared atorvastatin 80 mg with rosuvastatin 40 mg among 1039 patients with CAD and reported that both regimens resulted in significant reductions in the PAV at 24 months (-0.99% vs. -1.22%, P=0.17)³¹⁾. The JAPAN ACS trial in 2009 reported that pitavastatin 4 mg and atorvastatin 20 mg similarly resulted in significant regression of coronary plaque volume at 9 months among 307 Japanese acute coronary syndrome (ACS) patients (change in %plaque volume: -5.7% vs. -6.3%, P=0.5)³²⁾. The YOKOHAMA ACS study in 2016 investigated the effects of 4 different statins on coronary plaques in 118 Japanese ACS patients. At 10 months, a greater reduction in plaque volume was confirmed in the atorvastatin 20 mg and pitavastatin 4 mg groups than in the pravastatin 10 mg and fluvastatin 30 mg groups (change in %plaque volume: -3.6% vs. -2.9% vs. +1.5% vs. +0.4%, P=0.02)³³⁾.

The effects of statins on plaque composition have been assessed in several studies using VH-IVUS, IB-IVUS, OCT, and NIRS. VH- and IB-IVUS studies have generally demonstrated plaque stabilization, including increases in fibrous and calcified plaque volumes, and reductions in necrotic core and noncalcified plaque volumes. Among the OCT trials, the 2014 EASY-FIT trial investigated the effect of atorvastatin 20 mg on plaque stabilization compared with atorvastatin 5 mg in 70 patients with unstable angina. At 1 year, atorvastatin 20 mg provided a greater increase in minimum FCT (+73 µm vs. +19 µm, P=0.002) and reduction in lipid arc (-50° vs. -10°, P＜0.001)³⁴⁾. The IBIS-4 observational study in 2018 showed that rosuvastatin 40 mg resulted in a significant increase in minimum FCT (+24 µm) and reduction in macrophage arc (-3°) at 1 year among 103 patients with ST-elevation myocardial infaction³⁵⁾. Using NIRS, the YELLOW trial demonstrated a significant reduction in maxLCBI_4mm at 7 weeks in the rosuvastatin 40 mg group compared with the standard therapy group (-149 vs. +2.4, P=0.01)³⁶⁾.

Several CTA studies have demonstrated that lipid-lowering therapy with statins attenuates plaque volume progression^37-39). The PARADIGM study in 2018 investigated the impact of statins on coronary plaques as assessed by CTA in 1255 patients without a history of CAD. Compared with lesions in statin-naïve patients, those in statin-taking patients showed a slower rate of overall PAV progression (1.76%±2.40% per year vs. 2.04%±2.37% per year, P=0.002) but more rapid progression of calcified PAV (1.27%±1.54% per year vs. 0.98%±1.27% per year, P＜0.001)³⁸⁾.

Ezetimibe

Ezetimibe inhibits the intestinal uptake of dietary and biliary cholesterol at the level of the brush border of the intestine without affecting the absorption of fat-soluble nutrients, resulting in a reduction in the amount of cholesterol delivered to the liver. Upregulation of LDL receptor expression on the surface of liver cells in response to reduced cholesterol delivery leads to increased clearance of LDL-C from the blood. When added to ongoing statin therapy, ezetimibe reduces LDL-C levels by an additional 21%-27% in patients with dyslipidemia with or without established CAD²⁷⁾.

Several randomized trials using IVUS have assessed the benefit of ezetimibe 10 mg in addition to statin on coronary plaque regression and have consistently shown plaque regression (change in PAV) ranging from -0.4% to -2.9%. The HEAVEN trial in 2012 showed that ezetimibe 10 mg in addition to atorvastatin 80 mg significantly reduced PAV at 1 year (–0.4% vs. +1.4, P=0.014) compared with standard therapy (i.e. statin alone) in 89 patients with stable CAD⁴⁰⁾. Masuda et al. in 2015 demonstrated that ezetimibe combined with rosuvastatin 5 mg significantly reduced TAV at 6 months (-13.2% vs. -3.1%; P=0.05) compared with rosuvastatin 5 mg alone in 51 Japanese patients with stable CAD⁴¹⁾. The PRECISE-IVUS in 2015 similarly showed the significant plaque regression of atorvastatin plus ezetimibe compared with atorvastatin alone in 202 Japanese patients undergoing percutaneous coronary intervention (PCI) (change in PAV: -1.4% vs. -0.3%, P=0.001)⁴²⁾. Other trials, including the ZEUS (2014)⁴³⁾ and OCTIVUS (2016)⁴⁴⁾ trials as well as studies by Hibi et al. (2018)⁴⁵⁾ and Oh et al. (2021)⁴⁶⁾, showed numerically greater plaque regression among patients with ezetimibe combined with statin than those treated with statin alone; however, these differences were not statistically significant. The effect of ezetimibe in addition to statin therapy on plaque composition was assessed using VH-IVUS^{40, 44)}, IB-IVUS⁴⁵⁾, and NIRS-IVUS⁴⁶⁾, but no significant difference was observed between the treatment groups. The ZIPANGU study in 2017 reported that the yellow color grade by angioscopy (with a higher grade indicating more lipids) decreased significantly in both combination (atorvastatin 10–20 mg plus ezetimibe) and monotherapy (atorvastatin 10–20 mg) groups among 131 Japanese patients with stable CAD, but there was no significant difference between treatment groups⁴⁷⁾.

PCSK9 Inhibitors

An increased concentration or function of PCSK9 in the plasma reduces the LDL receptor expression by promoting lysosomal catabolism, resulting in an increase in plasma LDL concentrations. Therapeutic strategies have been developed mainly using human monoclonal antibodies against PCSK9, which bind specifically to human PCSK9 to inhibit its effects on the LDL receptor, resulting in a reduction of LDL-C by up to 60%. Inclisiran is a novel small interfering RNA-based therapy that inhibits the synthesis of PCSK9 and results in the reduction of LDL-C by up to 50%^27); however, evidence concerning its effects on plaque regression is currently limited to anti-human PCSK9 monoclonal antibody.

The GLAGOV trial in 2016 investigated the effect of evolocumab in addition to statins on coronary plaques as assessed by IVUS⁴⁸⁾. Among 968 patients undergoing coronary angiography, there was a significant reduction in the PAV at 76 weeks in the evolocumab group compared with placebo (-0.95% vs. +0.05%, P＜0.01). The ODYSSEY J-IVUS trial in 2019 evaluated the effect of alirocumab 75 mg on coronary plaques in 206 Japanese patients with recent ACS using IVUS⁴⁹⁾. There was no significant difference in % change in the normalized TAV at 36 weeks between the alirocumab and standard-care groups (-4.8% vs. -3.1%, P=0.23). The PACMAN-AMI trial in 2022 investigated the effects of alirocumab added to statin therapy on coronary atherosclerosis using NIRS-IVUS and OCT⁵⁰⁾ and other pleiotropic effects^51-53) in 300 patients with acute myocardial infarction. At 1 year, alirocumab resulted in greater plaque volume reduction than placebo (change in PAV: -2.13% vs. -0.92%, P＜0.001). Furthermore, alirocumab exerted a favorable effect on plaque composition (maxLCBI_4mm by NIRS: −79.42 vs. −37.60, P=0.006, minimum FCT by OCT: 62.67 µm vs. 33.19 µm, P＜0.001)⁵⁴⁾. A substudy of the PACMAN-AMI study reported that alirocumab treatment and higher baseline maxLCBI_4mm were independent predictors of “triple regression” (i.e. the combined presence of PAV reduction, maxLCBI_4mm reduction, and minimum FCT increase), which was associated with a reduced risk of MACE⁵⁵⁾. Similarly, the HUYGENS trial in 2022 reported that evolocumab resulted in a greater increase in minimum FCT (+42.7 vs. +21.5 µm, P=0.015) at 1 year than placebo in 161 patients with non-ST elevation MI⁵⁶⁾.

Triglyceride-Lowering Agents

Although a high TG level (＞150 mg/dL) is known to be a potential CVD risk factor, the current guidelines recommend that the use of drugs to lower TG levels only be considered in high-risk patients when TGs are ＞200 mg/dL and cannot be sufficiently lowered by lifestyle measures alone²⁷⁾.

Several studies have investigated the impact of eicosapentaenoic acid (EPA) on coronary plaques using IVUS, OCT, and CTA and have shown mixed results. The CHERRY study in 2017 reported that a combination of pitavastatin 4 mg and EPA 1800 mg/day significantly reduced TAV by IB-IVUS at 8 months compared with pitavastatin 4 mg alone in 193 patients undergoing PCI⁵⁷⁾. The EVAPORATE trial in 2020 demonstrated a greater reduction in % change in plaque volume by CTA at 18 months in the icosapent ethyl (IPE) 4 g/day group than in the placebo group (-9% vs. +11%, P=0.0019) in 80 patients with CAD. However, the high baseline plaque volume in the IPE group and the use of a mineral oil as placebo, which has an adverse effect on inflammation and lipid profile, need to be carefully considered⁵⁸⁾. The other two RCTs using IB-IVUS (Niki et al. 2016) and CTA (Alfaddagh et al. 2017) showed no significant differences in change in plaque volume^{59, 60)}. Nishio et al. in 2014 reported that the addition of EPA 1800 mg/day to rosuvastatin significantly increased FCT by OCT at 9 months compared with rosuvastatin alone (+54.8 µm vs. +23.5 µm, P＜0.001) in 30 patients undergoing PCI⁶¹⁾, while Kita et al. in 2020 reported that EPA or EPA+docosahexaenoic acid (DHA) therapy in addition to statin therapy did not significantly increase FCT⁶²⁾.

To date, no studies investigating the effect of fibrates on coronary plaque regression have been reported. Currently, a randomized trial investigating the effect of pemafibrate on coronary plaques and the renal function in patients with CAD and elevated fasting TG levels (PEMA-CORE study) is ongoing (jRCT:031210067).

Factors Associated with Blunted Plaque Regression

Several studies have consistently reported that the presence of diabetes mellitus was associated with blunted regression of coronary plaques by lipid-lowering therapy^63-67). A previous meta-analysis of 5 RCTs including 2237 patients undergoing serial IVUS imaging to assess the impact of several medications on coronary plaque progression demonstrated greater plaque progression in patients with diabetes than in those without diabetes (PAV: +0.6% vs. +0.05%, P=0.0001, TAV: -0.6% vs. -2.7%, P=0.03)⁶³⁾. The effect of lipid-lowering therapy on plaque regression may be attenuated by the presence of diabetes.

The effect of lipoprotein (a) (Lp[a]) on plaque regression is controversial. A sub-analysis of the YOKOHAMA-ACS study reported attenuated plaque regression in patients with Lp(a) ＞20 mg/dl compared to those with Lp(a) ≤ 20 mg/dl (% change in plaque volume: +2.5% vs. -6.8%, p=0.02)⁶⁸⁾, while a sub-analysis of the SATURN study showed that Lp(a) levels were not associated with changes in the PAV⁶⁹⁾.

Summary and Future Perspective

Several imaging techniques have been applied in clinical trials to determine the effect of lipid-lowering therapy on coronary plaque burden and composition. Although IVUS has been the most extensively used modality to assess plaque burden, other invasive modalities, such as OCT and NIRS, provide relevant data on plaque vulnerability, and CTA non-invasively detects both plaque volume and characteristics. A large body of evidence supports the notion that LDL-C reduction by statins alone or in combination with ezetimibe and PCSK9 inhibitors consistently results in improvements in plaque burden and favorable morphological changes. Future studies should focus on the effect of novel treatment options for emerging therapeutic targets, including Lp(a), TGs, and inflammation on coronary plaques, although definitive clinical endpoint trials will be required to confirm the clinical efficacy and potential adverse effects. Furthermore, given the causal relationship between plaque regression and reduced CV events, direct plaque imaging to monitor temporal changes in atherosclerotic plaque volume and composition may have a relevant role in guiding treatment decisions in primary and secondary prevention. Whether or not optimal medical therapy guided by routine plaque imaging actually improves the clinical outcomes requires further investigation.

Acknowledgements:

None.

Funding:

None.

Conflict of Interest Statement:

Dr. Ueki reports grants from Astellas Pharma and personal fees from Abbott Vascular, Amgen, Bayer, Daiichi Sankyo, Kowa, NIPRO, and Novartis, outside the submitted work.

Dr. Kuwahara has received lecture fees from Astellas Pharma Inc., AstraZeneca K.K., MSD K.K., Otsuka Pharmaceutical Co., Ltd., Ono Pharmaceutical Co., Ltd., Kyowa Kirin Co., Ltd., Kowa Co., Ltd., Sanofi K.K., Sumitomo Dainippon Pharma Co., Ltd. (Sumitomo Pharma Co., Ltd.), Mitsubishi Tanabe Pharma Corp., Eli Lilly Japan K.K., Nippon Boehringer Ingelheim Co., Ltd., Novartis Pharma K.K., Novo Nordisk Pharma Ltd., Bayer Yakuhin, Ltd., Pfizer Japan Inc., and Janssen Pharmaceutical K.K.; funded research or joint research expenses from Kowa Co., Ltd., AstraZeneca K.K., Daiichi Sankyo Co., Ltd., Novo Nordisk Pharma Ltd., Amgen, Janssen Pharmaceutical K.K., Parexel International Inc., and Astellas Pharma Inc. His affiliated institution (Shinshu University School of Medicine) has received grants from Otsuka Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Corp., Nippon Boehringer Ingelheim Co., Ltd., and Kyowa Kirin Co., Ltd., and his department has endowed chairs from Medtronic Japan Co. Ltd., Boston Scientific Japan K.K., Abbott Japan LLC, Japan Lifeline Co.,Ltd., Biotronik Japan, Terumo Corporation, Nipro Corporation, and Cordis Japan G.K.

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41)Komukai K, Kubo T, Kitabata H, Matsuo Y, Ozaki Y, Takarada S, Okumoto Y, Shiono Y, Orii M, Shimamura K, Ueno S, Yamano T, Tanimoto T, Ino Y, Yamaguchi T, Kumiko H, Tanaka A, Imanishi T, Akagi H, Akasaka T. Effect of atorvastatin therapy on fibrous cap thickness in coronary atherosclerotic plaque as assessed by optical coherence tomography: the EASY-FIT study. J Am Coll Cardiol, 2014; 64: 2207-2217

42)Raber L, Koskinas KC, Yamaji K, Taniwaki M, Roffi M, Holmvang L, Garcia Garcia HM, Zanchin T, Maldonado R, Moschovitis A, Pedrazzini G, Zaugg S, Dijkstra J, Matter CM, Serruys PW, Luscher TF, Kelbaek H, Karagiannis A, Radu MD, Windecker S. Changes in Coronary Plaque Composition in Patients With Acute Myocardial Infarction Treated With High-Intensity Statin Therapy (IBIS-4): A Serial Optical Coherence Tomography Study. JACC Cardiovasc Imaging, 2018;

43)Nishiguchi T, Kubo T, Tanimoto T, Ino Y, Matsuo Y, Yamano T, Terada K, Emori H, Katayama Y, Taruya A, Ozaki Y, Shiono Y, Shimamura K, Kameyama T, Kitabata H, Yamaguchi T, Tanaka A, Hozumi T, Akasaka T. Effect of Early Pitavastatin Therapy on Coronary Fibrous-Cap Thickness Assessed by Optical Coherence Tomography in Patients With Acute Coronary Syndrome: The ESCORT Study. JACC Cardiovasc Imaging, 2018; 11: 829-838

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