Super-Resolution Ultrasound Imaging for Assessing Response to Neoadjuvant Chemotherapy in Breast Cancer
Value of Super-Resolution Ultrasound Imaging in Assessing Response to Neoadjuvant Chemotherapy for Breast Cancer: A Prospective Observational Study
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.
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).
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).
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.
- 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.
調査の概要
状態
条件
詳細な説明
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.
研究の種類
入学 (推定)
連絡先と場所
研究連絡先
- 名前：Yang Yang, MD
- 電話番号：+8615856969563
- メール：yangyang5363@163.com
研究場所
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Anhui
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Hefei、Anhui、中国、230001
- Anhui Provincial Cancer Hospital
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コンタクト：
- Yang Yang
- 電話番号：+8615856969563
- メール：yangyang5363@163.com
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参加基準
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
サンプリング方法
調査対象母集団
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.
説明
Inclusion Criteria
- Age and Gender: Female patients aged 18 to 75 years.
- Diagnosis: Histologically confirmed invasive breast cancer via core needle biopsy.
- Treatment Plan: Scheduled to receive standard neoadjuvant chemotherapy at our institution.
- 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
- Prior Treatment: History of any prior treatment for ipsilateral breast cancer (e.g., surgery, radiotherapy, chemotherapy, or targeted therapy).
- Other Malignancies: Presence of other active malignancies.
- Pregnancy/Lactation: Pregnant or breastfeeding women.
- Health Status: Severe cardiac, hepatic, or renal insufficiency, or psychiatric disorders that preclude cooperation with the examination.
- Image Quality: Poor ultrasound image quality that prevents SR-US analysis.
研究計画
研究はどのように設計されていますか？
デザインの詳細
コホートと介入
グループ/コホート |
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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.
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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.
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この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
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Discriminative Ability of the Super-Resolution Ultrasound Prediction Model for Pathological Complete Response (pCR)
時間枠：Through study completion, an average of 24 weeks
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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.
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Through study completion, an average of 24 weeks
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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
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Diagnostic performance of the model.
時間枠：Through study completion, an average of 24 weeks
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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.
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Through study completion, an average of 24 weeks
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Predictive value of early parameter changes.
時間枠：3 weeks
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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.
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3 weeks
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Diagnostic Accuracy, Sensitivity, and Specificity of SRUS Model for pCR
時間枠：Through study completion, an average of 24 weeks
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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.
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Through study completion, an average of 24 weeks
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Clinical utility of the model.
時間枠：Through study completion, an average of 24 months
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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).
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Through study completion, an average of 24 months
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協力者と研究者
研究記録日
主要日程の研究
研究開始 (推定)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- 2026-LLYJ-0025
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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