Development and External Validation of an Imaging-Clinical Multimodal Fusion Model for Predicting Postoperative Prognosis After Partial Nephrectomy in Patients With Endophytic Renal Cell Carcinoma
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 406
- 试验地点
- 1
- 主要终点
- Modified Pentafecta Achievement After Partial Nephrectomy
研究概览
简要总结
This retrospective observational cohort study aims to develop and externally validate an imaging-clinical multimodal fusion model for predicting postoperative prognosis in patients with endophytic renal cell carcinoma undergoing partial nephrectomy. Preoperative computed tomography imaging features, three-dimensional reconstruction-derived tumor characteristics, radiomics features, and clinical variables will be integrated using machine learning and deep learning approaches. The primary objective is to evaluate whether the multimodal model improves prediction of postoperative prognostic outcomes compared with single-modality models based on clinical or imaging features alone.
详细描述
Partial nephrectomy is a standard nephron-sparing treatment for localized renal cell carcinoma. However, postoperative functional and oncologic outcomes remain heterogeneous, especially in patients with endophytic renal tumors, in whom tumor complexity may increase surgical difficulty and affect postoperative recovery. Conventional clinical variables and anatomical scoring systems may not fully capture the multidimensional risk profile of these patients.
This study will retrospectively collect clinical, pathological, perioperative, and imaging data from patients with endophytic renal cell carcinoma who underwent partial nephrectomy. Preoperative multiphase computed tomography images will be used for radiomics feature extraction and deep learning-based image representation. Three-dimensional reconstruction-derived tumor features and conventional clinical variables will also be incorporated.
The study will develop and validate multimodal prediction models, including clinical models, radiomics models, deep learning imaging models, and imaging-clinical fusion models. Model performance will be assessed using discrimination, calibration, and clinical utility metrics, including the area under the receiver operating characteristic curve, calibration curves, decision curve analysis, and external validation across independent cohorts.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients diagnosed with renal cell carcinoma. Patients with endophytic renal tumors based on preoperative imaging assessment. Patients who underwent partial nephrectomy. Available preoperative contrast-enhanced computed tomography images. Available clinical, pathological, perioperative, and postoperative follow-up data.
- •Age 18 years or older at the time of surgery.
排除标准
- •Patients who underwent radical nephrectomy as the primary surgical treatment. Patients with missing or poor-quality preoperative imaging data. Patients with incomplete key clinical, pathological, or follow-up information. Patients with hereditary renal cancer syndromes. Patients with bilateral renal tumors or solitary kidney. Patients who received neoadjuvant systemic therapy before partial nephrectomy.
研究组 & 干预措施
Development Cohort
Patients with endophytic renal cell carcinoma who underwent partial nephrectomy and were included for model development and internal validation.
干预措施: Imaging-clinical multimodal prognostic modeling (Other)
External Validation Cohort 1
An independent cohort of patients with endophytic renal cell carcinoma who underwent partial nephrectomy and were used for external validation of the prediction model.
干预措施: Imaging-clinical multimodal prognostic modeling (Other)
External Validation Cohort 2
An independent validation cohort used to evaluate the generalizability of the multimodal prognostic prediction model.
干预措施: Imaging-clinical multimodal prognostic modeling (Other)
External Validation Cohort 3
An additional independent validation cohort used to assess model robustness across different patient populations or institutions.
干预措施: Imaging-clinical multimodal prognostic modeling (Other)
结局指标
主要结局
Modified Pentafecta Achievement After Partial Nephrectomy
时间窗: From the date of partial nephrectomy to the last available postoperative follow-up, up to 12 months after surgery.
Modified pentafecta achievement will be defined as the simultaneous fulfillment of predefined postoperative outcome criteria, including negative surgical margin, absence of major postoperative complications, preservation of renal function, absence of significant perioperative adverse events, and absence of early tumor recurrence or other prespecified unfavorable outcomes. Patients who do not meet all criteria will be classified as modified pentafecta failure.
次要结局
- Positive Surgical Margin(At final pathological evaluation after partial nephrectomy)
- Area Under the Receiver Operating Characteristic Curve of the Multimodal Model(At completion of model development and external validation, using postoperative outcome data up to 12 months after surgery.)
- Postoperative eGFR Decline Greater Than 20%(From baseline to 3-12 months after partial nephrectomy)
- Major Postoperative Complications(Within 30 or 90 days after partial nephrectomy)