이 페이지는 자동 번역되었으며 번역의 정확성을 보장하지 않습니다. 참조하십시오 영문판 원본 텍스트의 경우.

Super-Resolution Ultrasound Imaging for Assessing Response to Neoadjuvant Chemotherapy in Breast Cancer

2026년 5월 28일 업데이트: Wang Xiaojing, Anhui Provincial Cancer Hospital

Value of Super-Resolution Ultrasound Imaging in Assessing Response to Neoadjuvant Chemotherapy for Breast Cancer: A Prospective Observational Study

  1. Study Design Overview Study Type: Single-center, prospective, observational, diagnostic study. Primary Objective: To validate whether Super-Resolution Ultrasound Imaging (SRUS) can accurately predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer at an early stage (after the first cycle of chemotherapy).

    Sample Size: A total of 150 patients are planned to be enrolled. Study Period: March 2026 - March 2028.

  2. Core Methodology: Cohort Allocation This study employs a classic "Model Development-Validation" cohort design to construct a predictive model and verify its generalizability.

    Allocation Method: Systematic random allocation. Allocation Ratio: 7:3. Randomization: Patients will be assigned based on the sequence of enrollment using a computer-generated random sequence.

    Blinding Principle: Allocation information will be concealed (blinded) from patients and the clinical treatment team. Only the research coordinators and statisticians will have access to the grouping data to prevent information leakage.

    Validation Set (Independent Validation Cohort): Comprising 30% of the sample (45 cases). The data will remain "sealed" until model construction is finalized. It will be used for unbiased, objective performance evaluation of the final model (e.g., calculating AUC, sensitivity).

  3. Study Procedures and Visits

    The study workflow strictly adheres to the chemotherapy timeline, with core data collection points focused on the early phase of treatment:

    V0 (Screening): Confirmation of eligibility criteria. V1 (Baseline, Pre-chemotherapy): Initial SRUS examination to acquire baseline tumor data.

    V2 (Early Visit, 48-72 hours after the 1st cycle): The critical data point for the predictive model; the first follow-up examination.

    V3 (Mid-term Visit, Pre-4th cycle): The second follow-up examination. V4 (Surgery, 3-4 weeks after the last cycle): Radical surgery is performed. V5 (Endpoint Assessment, 2-4 weeks post-surgery): Acquisition of pathological results to confirm pCR status (the gold standard).

  4. Key Technology and Statistics Key Technology: The Mindray Resona A20 ultrasound system will be used in conjunction with Sulfur Hexafluoride (SF6) microbubble contrast agents to extract quantitative parameters such as tumor microvascular density and blood volume.

    Statistical Analysis:

    In the Training Set: LASSO regression will be used for feature selection to construct a logistic regression predictive model.

    In the Validation Set: The formula derived from the training set will be directly applied to calculate the Area Under the ROC Curve (AUC), calibration curves, and other metrics to evaluate model performance.

  5. Eligibility Criteria Inclusion Criteria: Females aged 18-75, histologically confirmed invasive breast cancer, scheduled for standard neoadjuvant chemotherapy, with lesions clearly visible on baseline ultrasound.

Exclusion Criteria: History of prior breast cancer treatment (surgery, radiotherapy, chemotherapy), presence of other active malignancies, pregnancy or lactation, severe organ dysfunction, or poor image quality.

연구 개요

상태

아직 모집하지 않음

정황

상세 설명

Background and Rationale Breast cancer is the most common malignancy among women worldwide. Neoadjuvant chemotherapy (NAC) is standard for locally advanced breast cancer, aiming to downstage tumors and increase surgical options. Conventional imaging modalities (ultrasound, MRI) have limitations in detecting early microvascular changes and residual disease. Super-resolution ultrasound imaging (SRUS) is an emerging technique based on ultrasound localization microscopy, enabling visualization of microvasculature at micron-scale resolution. It provides quantitative parameters including vessel density, blood volume, vascular complexity, perfusion index, and intensity analysis. Preliminary evidence suggests SRUS can detect early microvascular alterations before morphological changes become apparent, but prospective data in breast cancer NAC response prediction are lacking.

Study Design Single-center, prospective, observational, diagnostic study. Patients receive standard NAC per clinical guidelines; no treatment intervention is imposed. The study involves additional SRUS examinations at predefined time points.

Model Development and Validation

Consecutive eligible patients are enrolled and randomly assigned (7:3 ratio using computer-generated sequence) to:

Training set (70%, n=105): for model development, feature selection, and internal optimization.

Validation set (30%, n=45): for independent, unbiased performance validation.

Allocation is concealed from patients and clinical care team. Analysis of SRUS images and pathological assessment are blinded to clinical data and group assignment.

Technical Procedures

Equipment: Mindray Resona A20 ultrasound system, probe frequency 5-18 MHz.

Contrast agent: 4.8 mL sulfur hexafluoride microbubbles (SonoVue) injected intravenously, followed by 5 mL saline flush.

Acquisition: Dynamic image sequences (6 seconds each) are acquired during early arterial phase (10-30 s) and late arterial phase (20-45 s) with breath-holding.

Post-processing: SRIPlatform software extracts quantitative parameters: vessel density, blood volume, vascular complexity, perfusion index, intensity, and velocity. Changes from baseline (Δ%) are calculated.

Study Timeline

V1 (Baseline, within 1 week before NAC): Baseline SRUS.

V2 (Early response, 48-72 hours after cycle 1): First follow-up SRUS (key predictive time point).

V3 (Mid-treatment, before cycle 4): Second follow-up SRUS.

V4 (Surgery, 3-4 weeks after last NAC): Radical breast surgery.

V5 (Pathology, 2-4 weeks post-surgery): Pathological complete response (pCR) determination (reference standard).

Sample Size Based on an assumed pCR rate of 30%, a two-sided 95% confidence interval width of 0.15 for sensitivity (expected 80%), 10% dropout, and 30% allocation to validation set, total enrollment is 150 patients. The training set provides ~32 pCR events, supporting evaluation of 3-5 candidate predictors (event-per-variable rule: 10:1).

Statistical Analysis

Software: R 4.3.0 (glmnet, rms, pROC, rmda).

Variable screening: Univariate analysis (p<0.10), then LASSO regression with 10-fold cross-validation (λ.1se) for dimension reduction.

Model building: Multivariate logistic regression; coefficients, OR, 95% CI.

Internal validation: Bootstrap optimism-corrected AUC.

External validation: Apply final model to validation set; assess discrimination, calibration, and clinical utility (decision curve analysis).

Reporting: Adherence to TRIPOD statement.

Safety and Risk Mitigation SRUS is non-invasive with output within safe limits, equivalent to conventional ultrasound. Risks are minimal (mild discomfort, potential privacy breach). Data are anonymized and stored on encrypted hospital servers.

Quality Control

Standardized operating procedures for image acquisition and post-processing.

Operator training and inter-operator consistency testing.

Image quality review by core laboratory (signal-to-noise ratio, tracking stability, coverage of inflow-washout phases).

100% source data verification for key variables.

Quarterly internal audits.

Ethics and Dissemination Approved by the Institutional Ethics Committee of the First Affiliated Hospital of USTC (West District, Anhui Provincial Cancer Hospital). Conducted in accordance with the Declaration of Helsinki. Written informed consent obtained from all participants. Results will be submitted for publication in peer-reviewed journals regardless of outcome.

Study Period March 2026 - March 2028.

연구 유형

관찰

등록 (추정된)

150

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 연락처

연구 장소

  • 중국
    • Anhui
      • Hefei, Anhui, 중국, 230001
        • Anhui Provincial Cancer Hospital
        • 연락하다:

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

아니

샘플링 방법

비확률 샘플

연구 인구

This study will enroll female patients aged 18 to 75 years with histologically confirmed invasive breast cancer who are scheduled to receive neoadjuvant chemotherapy (NAC) prior to surgery.

Participants must have at least one measurable tumor lesion suitable for super-resolution ultrasound imaging. Patients with evidence of distant metastasis (Stage IV) or those who have received prior systemic therapy for the current cancer diagnosis will be excluded.

The study aims to recruit approximately 150 participants from the Anhui Provincial Cancer Hospital. This population represents a typical cohort of locally advanced breast cancer patients undergoing standard NAC protocols.

설명

Inclusion Criteria

  1. Age and Gender: Female patients aged 18 to 75 years.
  2. Diagnosis: Histologically confirmed invasive breast cancer via core needle biopsy.
  3. Treatment Plan: Scheduled to receive standard neoadjuvant chemotherapy at our institution.
  4. Imaging: The lesion is clearly visible on baseline ultrasound. Consent: Willing to participate in the study and sign the written informed consent form.

Exclusion Criteria

  1. Prior Treatment: History of any prior treatment for ipsilateral breast cancer (e.g., surgery, radiotherapy, chemotherapy, or targeted therapy).
  2. Other Malignancies: Presence of other active malignancies.
  3. Pregnancy/Lactation: Pregnant or breastfeeding women.
  4. Health Status: Severe cardiac, hepatic, or renal insufficiency, or psychiatric disorders that preclude cooperation with the examination.
  5. Image Quality: Poor ultrasound image quality that prevents SR-US analysis.

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

코호트 및 개입

그룹/코호트
Training set (development queue)
70% of the total sample size (planned to include 105 cases) will be used for constructing predictive models, feature screening (such as using LASSO regression), and internal optimization.
Verification set (independent verification queue)
Training Set (Development Cohort): Participants assigned to this group constitute 70% of the total sample (n=105). Data from this group are used for model development, feature selection, and internal optimization. Allocation is performed by a computer-generated random sequence (7:3 ratio) at enrollment. The group assignment is concealed from patients and the clinical care team. Validation Set (Independent Validation Cohort): Participants assigned to this group constitute 30% of the total sample (n=45). Data from this group are reserved for unbiased, independent performance validation of the final prediction model. Allocation is performed by a computer-generated random sequence (7:3 ratio) at enrollment. The group assignment is concealed from patients and the clinical care team.

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
Discriminative Ability of the Super-Resolution Ultrasound Prediction Model for Pathological Complete Response (pCR)
기간: Through study completion, an average of 24 weeks
The discriminative ability of the final prediction model (derived from super-resolution ultrasound parameters) in identifying pCR, assessed in the independent validation cohort. Performance is quantified by the Area Under the Receiver Operating Characteristic Curve (AUC). An AUC value closer to 1 indicates stronger discriminative ability.
Through study completion, an average of 24 weeks

2차 결과 측정

결과 측정
측정값 설명
기간
Diagnostic performance of the model.
기간: Through study completion, an average of 24 weeks
In the validation set, the optimal cutoff value is determined using the Youden index. Performance metrics including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) are calculated.
Through study completion, an average of 24 weeks
Predictive value of early parameter changes.
기간: 3 weeks
The ability of early changes in super-resolution ultrasound parameters (measured after the first chemotherapy cycle) to predict final pCR status. Evaluated using univariate ROC analysis to calculate the AUC.
3 weeks
Diagnostic Accuracy, Sensitivity, and Specificity of SRUS Model for pCR
기간: Through study completion, an average of 24 weeks
The secondary outcomes include the diagnostic accuracy, sensitivity, and specificity of the SRUS prediction model. These metrics will be calculated based on the confusion matrix derived from the independent validation cohort.
Through study completion, an average of 24 weeks
Clinical utility of the model.
기간: Through study completion, an average of 24 months
The net clinical benefit of using the prediction model to guide clinical decision-making, assessed across a range of threshold probabilities. Evaluated using Decision Curve Analysis (DCA).
Through study completion, an average of 24 months

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

스폰서

Anhui Provincial Cancer Hospital

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (추정된)

2026년 6월 1일

기본 완료 (추정된)

2028년 3월 1일

연구 완료 (추정된)

2028년 7월 1일

연구 등록 날짜

최초 제출

2026년 5월 7일

QC 기준을 충족하는 최초 제출

2026년 5월 28일

처음 게시됨 (실제)

2026년 6월 3일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 6월 3일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 5월 28일

마지막으로 확인됨

2026년 5월 1일

추가 정보

이 연구와 관련된 용어

키워드

추가 관련 MeSH 약관

기타 연구 ID 번호

  • 2026-LLYJ-0025

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .

유방암에 대한 임상 시험

유사한 임상시험 검색

스폰서 및 공동 작업자

건강 상태

약물 개입

CROs by country

CROs in Ghana

정황

희귀 질병

약물 개입

식이 보충제

스폰서 / 협력자

위치

구독하다