Multimodal Radiomics Model (18F-FAPI PET/CT + CMR) for AL Cardiac Amyloidosis Prognosis (AL-CA)

A Prospective Study on the Prognostic Assessment of Light Chain Type Cardiac Amyloidosis (AL-CA) Based on Multimodal Fusion Radiomics Model of 18F-FAPI PET/CT and 3D CMR

1. Goal of the Study:

   The goal of this prospective observational study is to develop and validate a novel, non-invasive method for predicting the prognosis of patients with light-chain cardiac amyloidosis (AL-CA). This method integrates advanced multi-modal imaging techniques and artificial intelligence (radiomics) to provide early and accurate assessment of treatment response and survival outcomes.

2. Main Question:

   Can a multi-modal radiomics model, based on the fusion of [¹⁸F]FAPI PET/CT (assessing fibroblast activation) and 3D Cardiac MRI (CMR) (assessing structural damage) imaging data, accurately predict 12-month all-cause mortality and dynamically track disease progression in patients with AL-CA receiving standard care?

3. Participants:

   Population: Patients diagnosed with AL-CA (confirmed by endomyocardial biopsy or extracardiac biopsy plus specific cardiac criteria: NT-proBNP >332 pg/mL, mean left ventricular wall thickness >12 mm, excluding hypertension/other causes).

   Setting: Single-center study at Beijing Anzhen Hospital, Capital Medical University.

   Number: 49 patients (calculated sample size accounting for dropouts).

   Key Criteria:

   Inclusion: Confirmed AL-CA diagnosis, receiving standard AL-CA treatment (chemotherapy e.g., Daratumumab-based regimen + supportive cardiac care).

   Exclusion: Active infection, advanced malignancy (life expectancy <12 months), severe cognitive impairment/immobility affecting imaging compliance/follow-up.

4. Study Design & Procedures:

   Design: Single-center prospective cohort study.

   Intervention: Participants receive standard-of-care treatment for AL-CA as per guidelines (chemotherapy regimen based on Daratumumab, Bortezomib, Cyclophosphamide, Dexamethasone; tailored cardiac support including diuretics, rate control, anticoagulation if needed).

   Procedures:

   Baseline: Upon enrollment, participants undergo comprehensive assessment: [¹⁸F]FAPI PET/CT scan, 3D CMR scan, blood tests (NT-proBNP, troponin, free light chains, etc.), clinical staging (Mayo 2012), functional assessment (NYHA class), quality of life questionnaire (KCCQ).

   Imaging: Specialized software (Siemens True D) performs cross-platform fusion of PET/CT and 3D CMR images. Radiomics features are extracted from the fused images using dedicated software (Siemens FeAture Explorer).

   Follow-up:

   Clinical: Every 3 months (symptoms, medication adherence, adverse events, lab tests including NT-proBNP).

   Imaging: Repeat [¹⁸F]FAPI PET/CT and 3D CMR scans at 6 months post-baseline. Radiomics features are extracted again.

   Endpoints: Primary endpoint is 12-month all-cause mortality. Secondary endpoints include re-hospitalization rates and changes in NYHA class. Follow-up continues until the 12-month endpoint for all participants.

   Data Analysis: Machine learning (LASSO-Cox regression) is used to select key radiomics features from baseline and 6-month scans and integrate them with quantitative imaging parameters (FAPI uptake volume, SUVmax, LGE burden, ECV) and clinical data to build prognostic models predicting 12-month survival.

5. Comparison:

Researchers will compare the predictive performance of the developed multi-modal radiomics model against:

• Traditional clinical biomarkers: NT-proBNP levels and Mayo Clinic staging.
• Standard quantitative imaging parameters alone: Such as myocardial FAPI uptake volume, SUVmax, or CMR-derived extracellular volume (ECV) measured at baseline and 6 months.

The goal is to demonstrate superior accuracy in predicting 12-month all-cause mortality using the integrated radiomics approach.

Study Overview

• Status: Enrolling by invitation
• Conditions: Cardiac Amyloidosis; AL Amyloidosis (AL)

Detailed Description

Light-chain cardiac amyloidosis (AL-CA) is an important cardiac manifestation of systemic light-chain amyloidosis and may lead to progressive myocardial involvement, impaired cardiac function, and poor prognosis. The extent of cardiac involvement and treatment response are important determinants of clinical outcomes in patients with AL-CA. Currently, risk assessment and treatment monitoring mainly rely on cardiac biomarkers, disease staging, and conventional cardiac imaging. However, conventional clinical biomarkers and quantitative imaging parameters may not fully characterize the biological activity, tissue remodeling, and longitudinal changes occurring within the myocardium. Therefore, the development of a non-invasive multimodal imaging approach capable of simultaneously characterizing myocardial biological activity, tissue properties, structural remodeling, and functional changes may improve disease monitoring and prognostic assessment in patients with AL-CA.

This prospective observational study will investigate the value of multimodal imaging integrating [18F]FAPI PET/CT and three-dimensional cardiac magnetic resonance (3D CMR), together with radiomics analysis, for the non-invasive assessment, longitudinal monitoring, and prognostic evaluation of AL-CA. [18F]FAPI PET/CT will provide information related to myocardial fibroblast activation and disease-associated biological activity, whereas 3D CMR will provide complementary information regarding cardiac morphology, function, myocardial tissue characteristics, and fibrosis. By integrating the complementary information provided by these imaging modalities and extracting high-dimensional imaging features that may not be identified by conventional visual assessment, multimodal radiomics may provide a more comprehensive characterization of myocardial involvement and its longitudinal changes in patients with AL-CA.

[18F]FAPI PET/CT imaging will be performed using a Siemens Biograph mCT PET/CT system. Myocardial imaging will be performed approximately 60 minutes after intravenous administration of the [18F]FAPI tracer. Participants will undergo image acquisition in the supine position. PET images will be reconstructed using the TrueX+TOF Ultral HD iterative reconstruction method and post-processed on a Siemens Syngo multimodality workstation. Cedars QPS/QGS software will be used for myocardial image analysis, generating left ventricular vertical long-axis, horizontal long-axis, and short-axis images, as well as short-axis polar maps for the assessment of myocardial tracer uptake characteristics and distribution patterns.

For PET/CT image analysis, volumetric regions of interest will be delineated throughout the left ventricular myocardium from the base to the apex on fused PET/CT images for quantitative and semi-quantitative assessment of myocardial [18F]FAPI uptake. The primary imaging parameters will include the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), and standardized uptake value ratio (SUVR). SUVR will be defined as the ratio of the SUVmean within the myocardial volume of interest to the SUVmean within a reference volume of interest placed in the descending aorta. Myocardial FAPI uptake volume and uptake distribution patterns will also be assessed. To further quantify the cardiac fibroblast activation protein burden, cardiac fibroblast activation protein volume (CFV) and total cardiac FAP (TCF) will be analyzed. CFV will be calculated based on the volume of myocardial voxels meeting the predefined SUV threshold, and TCF will be derived from myocardial uptake intensity and FAP uptake volume. In the absence of visually apparent abnormal uptake, a standardized region of interest will be used for semi-quantitative assessment.

3D CMR imaging will be performed using a Philips 3T magnetic resonance system equipped with a dedicated cardiac coil. Participants will undergo imaging in the supine position. Balanced steady-state free precession (bSSFP) sequences will be used to acquire left ventricular long-axis and contiguous short-axis images for the assessment of cardiac morphology and function. High-resolution three-dimensional late gadolinium enhancement (LGE) imaging will be performed following gadolinium contrast administration to characterize myocardial tissue abnormalities and fibrosis-related changes. The 3D LGE acquisition will incorporate image navigation (iNAV), compressed sensing (CS), and Dixon water-fat separation techniques to improve spatial resolution and image quality and to reduce the effects of respiratory and other motion-related artifacts.

Motion-tracking and image-reconstruction techniques will be applied during 3D CMR data acquisition and reconstruction to address motion-related effects. High-resolution 3D LGE images will be reconstructed using compressed sensing and iterative reconstruction approaches to generate three-dimensional water-fat-separated myocardial delayed enhancement images. CVI post-processing software will be used to analyze CMR data and derive parameters reflecting cardiac morphology, function, and myocardial tissue characteristics, including ventricular morphological and functional parameters, LGE burden, native T1, extracellular volume (ECV), and other relevant myocardial tissue parameters. These parameters will be used to characterize myocardial structural remodeling, tissue alterations, and fibrosis and will subsequently be incorporated as conventional imaging variables in the multimodal analysis.

Multimodal image fusion will be performed using the Siemens Ture D multimodality post-processing platform. The purpose of image fusion is to achieve spatial registration, alignment, and integration of [18F]FAPI PET/CT and 3D CMR datasets, thereby combining information on myocardial biological activity and tracer uptake obtained from PET/CT with structural, functional, and tissue characterization obtained from CMR. Differences in spatial resolution, patient positioning, and cardiac motion between imaging modalities will be addressed through image registration. Manual adjustment based on left ventricular myocardial regions of interest will be performed when necessary. The fused datasets will be used to investigate the relationships among myocardial FAPI uptake, tissue characteristics, fibrosis, and structural remodeling.

Radiomics analysis will be performed using Siemens FeAture Explorer (FAE, version 0.5.13). High-dimensional radiomics features will be extracted from PET/CT, 3D CMR, and fused multimodal imaging datasets following standardized image preprocessing and region-of-interest segmentation. Extracted features will include first-order statistical features, morphological features, texture features, gray-level co-occurrence matrix (GLCM) features, gray-level run-length matrix (GLRLM) features, wavelet features, and other relevant image descriptors. Radiomics analysis will further quantify myocardial signal intensity, spatial heterogeneity, texture distribution, and tissue structural characteristics, thereby complementing the information provided by conventional quantitative imaging parameters.

Radiomics features will be integrated with quantitative parameters obtained from PET/CT and CMR, including myocardial FAPI uptake volume and distribution patterns, SUVmax, SUVmean, SUVR, CFV, TCF, LGE burden, native T1, and ECV. Relevant clinical, laboratory, and pathological variables will also be incorporated as appropriate for the planned analyses. The integration of multimodal radiomics features, conventional imaging parameters, and clinical variables will enable the construction of a comprehensive dataset representing different biological and structural dimensions of myocardial involvement in AL-CA.

LASSO-based methods will be used for feature selection to reduce redundancy in high-dimensional radiomics data and identify key variables associated with prognosis. Selected multimodal radiomics features, conventional quantitative imaging parameters, and clinical variables will subsequently be incorporated into predictive models. Machine learning approaches will be used for model development according to the characteristics of the available data and study objectives, and Cox proportional hazards regression models will be used for survival and prognostic analyses. These models will be used to evaluate the incremental predictive value of multimodal imaging features beyond conventional clinical indicators and standard imaging parameters.

Longitudinal multimodal imaging data obtained during follow-up will be analyzed to evaluate dynamic changes in myocardial FAPI uptake, CMR-derived tissue characteristics, and radiomics features. Changes in imaging characteristics between baseline and follow-up examinations will be analyzed in relation to clinical response, disease progression, and survival outcomes. This longitudinal analysis will explore the potential value of multimodal imaging for dynamic monitoring of disease activity and myocardial changes in patients with AL-CA.

The predictive performance of the multimodal radiomics models will also be compared with conventional clinical and imaging-based assessment methods. Comparator approaches will include traditional clinical biomarkers, disease staging, and quantitative imaging parameters derived from PET/CT or CMR alone. By evaluating and comparing the predictive performance of different approaches, this study will investigate whether the integration of [18F]FAPI PET/CT, 3D CMR, multimodal image fusion, and radiomics analysis can provide additional prognostic information.

The overall objective of this study is to develop and evaluate a non-invasive imaging-based approach integrating [18F]FAPI PET/CT and 3D CMR multimodal imaging. The study will explore the potential value of radiomics and integrated predictive models for assessing cardiac involvement, monitoring longitudinal disease changes, and evaluating prognosis in patients with AL-CA. The findings may provide more comprehensive and individualized imaging information for patients with AL-CA and offer additional imaging evidence for treatment response monitoring and clinical risk stratification.

• Study Type: Observational
• Enrollment (Estimated): 49

Contacts and Locations

Study Locations

• China
  • Beijing Municipality
    • Beijing, Beijing Municipality, China, 100029
      • Beijing Anzhen Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

Study Design

1. Study Type: Single-center prospective cohort study (evaluating the prognostic value of radiomics parameters under standardized treatment).
2. Study Population: Patients with suspected or confirmed cardiac light-chain amyloidosis (AL-CA) via endocardial or extracardiac biopsy who are admitted to the Department of Hematology, Beijing Anzhen Hospital, from Feburary 2025 to August 2028.

Description

Inclusion Criteria:

• Pathologically confirmed AL cardiac amyloidosis (AL-CA) by endocardial biopsy;
• Pathologically confirmed AL-CA by extracardiac (bone marrow, adipose tissue, tongue muscle, etc.) biopsy, with serum N-terminal pro-brain natriuretic peptide (NT-proBNP) > 332 pg/mL, left ventricular mean wall thickness > 12 mm, and exclusion of hypertension and other secondary causes of left ventricular hypertrophy;
• Receiving standard AL-CA treatment regimens (including chemotherapy and supportive therapy).

Exclusion Criteria:

• Complicated with active infection or advanced malignant tumor (expected survival time < 12 months);
• Presence of severe cognitive impairment, limited mobility, or other conditions that affect compliance with imaging examinations or the completeness of follow-up.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Rationale: AL-CA: Clearly identifies the disease population (Light-chain Cardiac Amyloidosis). Mul

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
12-month survival	12 months

Collaborators and Investigators

• Sponsor: Beijing Anzhen Hospital
• Investigators: Principal Investigator: wei dong, MD,PHD, Beijing Anzhen Hospital

Study record dates

Study Major Dates

• Study Start (Actual): February 13, 2025
• Primary Completion (Estimated): February 1, 2028
• Study Completion (Estimated): February 1, 2028

Study Registration Dates

• First Submitted: July 29, 2025
• First Submitted That Met QC Criteria: July 29, 2025
• First Posted (Actual): August 5, 2025

Study Record Updates

• Last Update Posted (Actual): September 10, 2026
• Last Update Submitted That Met QC Criteria: September 6, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Nervous System Diseases; Neoplasms; Neuromuscular Diseases; Metabolism, Inborn Errors; Genetic Diseases, Inborn; Metabolic Diseases; Immune System Diseases; Peripheral Nervous System Diseases; Neoplasms by Histologic Type; Neurodegenerative Diseases; Lymphoproliferative Disorders; Immunoproliferative Disorders; Heredodegenerative Disorders, Nervous System; Neoplasms, Plasma Cell; Paraproteinemias; Proteostasis Deficiencies; Amyloid Neuropathies; Amyloidosis, Familial; Amyloidosis; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Nutritional and Metabolic Diseases; Immunoglobulin Light-chain Amyloidosis; Amyloid Neuropathies, Familial
• Other Study ID Numbers: BeijingAnzhen dongwei; High Level research funding (Other Grant/Funding Number: Beijing Anzhen Hospital)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No