CN113517071A - Index evaluation method for renal tumor partial resection risk and postoperative early prognosis - Google Patents
Index evaluation method for renal tumor partial resection risk and postoperative early prognosis Download PDFInfo
- Publication number
- CN113517071A CN113517071A CN202110980160.7A CN202110980160A CN113517071A CN 113517071 A CN113517071 A CN 113517071A CN 202110980160 A CN202110980160 A CN 202110980160A CN 113517071 A CN113517071 A CN 113517071A
- Authority
- CN
- China
- Prior art keywords
- tumor
- index
- renal
- risk
- prognosis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Pathology (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Apparatus For Radiation Diagnosis (AREA)
Abstract
The invention relates to an index evaluation method for renal tumor partial resection risk and postoperative early prognosis, which is divided into open operation and non-open operation according to different operation modes; according to the imaging data of the CT before the operation of the patient, the sum of the basic size index of the renal tumor and the position index of the tumor is obtained to be used as the index evaluation index before the operation, the operation difficulty and early prognosis for evaluating the renal tumor before the operation according to different operation modes are established, compared with other scoring systems, the method can be more suitable for the current diversified operation modes, and reference suggestions are provided for clinicians. The evaluation system for evaluating the surgical risk and the postoperative early prognosis of the renal tumor resection based on different surgical modes can be more suitable for the current diversified surgical modes compared with other scoring systems; the evaluation system is established through prospective research based on the corresponding disease condition of the patient, and can better evaluate the operation risk and the early postoperative prognosis compared with the prior evaluation system (based on retrospective research).
Description
Technical Field
The invention relates to a tumor prediction technology, in particular to an index evaluation method for renal tumor partial resection risk and postoperative early prognosis.
Background
Renal cell carcinoma is one of the common malignant tumors in the urinary system, and the incidence rate of the renal cell carcinoma tends to increase year by year. Surgical resection is currently the primary treatment modality for localized and locally advanced kidney cancers. However, approximately 20-30% of patients will develop recurrence or metastasis after surgery, with a median post-operative recurrence metastasis time of 1-2 years. In order to evaluate clinical outcome and guide treatment schemes, accurate and early prediction of the prognosis of renal cancer patients is of great importance.
In 2001, Zisman a et al proposed a UISS scoring system, the first model used to systematically assess survival of metastatic and non-metastatic RCC patients after nephrectomy, which contained prognostic risk factors including TNM staging, Fuhrman staging and PS scoring. Whereas for patients with unresectable metastatic renal cancer, the MSKCC score and the Heng's score can be used to assess the prognosis of patients with metastatic renal cancer receiving IFN-alpha therapy and targeted therapy, respectively. According to the previous report aiming at the renal cancer prognosis factors, the prognosis influencing factors are mainly focused on the aspects of anatomy, histology and clinical characteristics.
The anatomical factors influencing the prognosis of the kidney cancer are mainly reflected in the stage of TNM (renal cancer), and the prognosis of a kidney cancer patient is influenced by the tumor size, the renal vein and inferior vena cava affected condition, the invasion condition of renal envelope and perirenal fat, the adrenal affected condition, the lymph node and distant metastasis conditions according to the 2010 AJCC renal cancer TNM stage standard. At present, the main standard for judging the anatomical factors of kidney cancer lies in postoperative pathological specimens, and preoperative imaging examination results can give clinical stages, but experience differences and measurement errors of radiologists often have differences with pathological stages, so that it is difficult to perform prognostic scoring according to imaging indexes before operation.
Histological factors affecting renal cancer include nuclear grade, histological subtype, sarcoid-like features, microvascular infiltration, tumor necrosis, tumor margin and aggregate system invasion. In 2013, ISUP/WHO replaced Fuhrman grading as a new pathological grading system, which greatly helped to predict renal cancer prognosis. The histological subtypes of renal cancer are mainly classified into three types, clear cell carcinoma, chromophobe cell carcinoma and papillary cell carcinoma, and the prognosis of patients with clear cell carcinoma is generally considered to be the worst. In a follow-up study of Bradley C.Leibovich and the like on different subtype renal cancers, the 15-year non-progression survival rates of renal clear cell carcinoma, chromophobe cell carcinoma and papillary renal cell carcinoma are 60%, 77% and 86% respectively, and the 15-year tumor specific survival rates are 70%, 88% and 90% respectively, and a plurality of studies have been carried out to incorporate the renal cancer histological subtype as an independent risk factor into a prognosis evaluation model. Currently, nephrectomy is the main treatment mode of renal cancer at stage T1, and compared with radical nephrectomy, the operation mode can retain partial nephrons and delay the progress of renal insufficiency of postoperative patients, but research finds that tumor margin positive is also a high risk factor of relapse of early renal cancer patients. Although the pathology is the gold standard for kidney cancer diagnosis, due to the limitation of pathological material selection and heterogeneity of tumor tissues, local histological features are difficult to represent the overall microenvironment of the tumor, so that the accuracy in prognosis evaluation is still lacking.
In recent years, molecular prediction models of kidney cancer gradually become a research hotspot, Samira A.Brooks and the like establish Clearcode34 risk prediction models according to 34 gene expression markers, renal clear cell carcinoma patients are divided into two subtypes of ccA and ccB, and the ccB patients have high postoperative recurrence and death risks. In a prognostic study of clear cell renal carcinoma in stages I-III, Rini B et al analyzed 732 genes that are likely to be associated with the prognosis of renal carcinoma, and finally concluded 16 genes that are highly associated with the prognosis of clear cell renal carcinoma, and the authors found that these genes regulate biological pathways that are important to the biology of clear cell renal carcinoma, namely, vascular, immune response, inflammation, cell cycle division and cell growth pathways.
However, the molecular marker is not applied to clinical practice, and on one hand, the detection cost is too high, and on the other hand, the detection of molecular expression is greatly limited due to inaccuracy of sample material taking parts and heterogeneity of renal tumors, so that a macroscopic and overall evaluation mode is lacking.
Disclosure of Invention
Aiming at effectively evaluating the operation difficulty and early prognosis problems of a renal tumor patient, the method provides an index evaluation method for partial renal tumor resection risk and postoperative early prognosis.
The technical scheme of the invention is as follows: an index evaluation method for renal tumor partial resection risk and postoperative early prognosis comprises dividing the renal tumor partial resection risk into open operation and non-open operation according to different operation modes; acquiring the sum of a basic index Rx of the renal tumor and a position index of the tumor as a preoperative index evaluation index according to the imaging data of preoperative CT of a patient; wherein Rx is the product of the maximum diameter a of the portion of the tumor within the kidney and the diameter B perpendicular to the maximum diameter; the position index of the tumor in the open surgery is ML, the ML is the edge position index of the tumor, the position index of the tumor in the non-open surgery is LL, and the LL is the longitudinal position index of the tumor.
Further, the marginal position index ML of the tumor is judged according to the score of the tumor inside or outside the kidney; the boundary between the inside and outside is defined as the line connecting the renal cortex and the renal calyx on both sides, and the boundary touching or located inside the boundary but not touching the renal portal vessels is defined as the renal tumor located inside, otherwise, it is located outside, 2 points inside and 1 point outside.
Further, the location index of the tumor for the non-open surgery is LL, LL is the longitudinal location index of the tumor, LL is a score according to D, E two polar lines on the coronal plane of the kidney, D line is the horizontal line of the superior border of the hilum, E line is the horizontal line of the inferior border of the hilum; score 1 is obtained if the tumor is completely above or below the polar line, and score 2 is obtained if the middle of the polar line is involved.
Further, the pre-operation index evaluation index is used for evaluating the operation risk and the early post-operation prognosis of the renal tumor partial resection with different operation modes.
The invention has the beneficial effects that: the invention relates to an index evaluation method for partial resection risk of renal tumor and early prognosis after operation, which establishes an operation difficulty and early prognosis for preoperative evaluation of renal tumor according to different operation modes, can be more suitable for the current diversified operation modes compared with other scoring systems, and provides reference suggestions for clinicians. The evaluation system for evaluating the surgical risk and the postoperative early prognosis of the renal tumor resection based on different surgical modes can be more suitable for the current diversified surgical modes compared with other scoring systems; the evaluation system is established through prospective research based on the corresponding disease condition of the patient, and can better evaluate the operation risk and the early postoperative prognosis compared with the prior evaluation system (based on retrospective research).
Drawings
FIG. 1 is a schematic diagram showing the tumor margin position in the method for evaluating the risk of renal tumor resection and the early prognosis after surgery according to the present invention;
FIG. 2 is a longitudinal position diagram of the tumor in the method for evaluating the risk of partial renal tumor resection and the early postoperative prognosis index according to the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
In order to evaluate the operation difficulty and early prognosis of a renal tumor patient, a team establishes an anatomical renal tumor complexity evaluation system of the first Chinese based on clinical big data, along with the progress and development of clinical technology, endoscopic surgery and a da vinci robot assisted laparoscopic partial nephrectomy become more and more operation selection modes gradually, diversification of operation modes requires an improvement evaluation system, and a brand new renal tumor complexity evaluation system capable of evaluating the operation difficulty and early prognosis of the renal tumor patient in different operation modes is further established through prospective research. On the basis of big data, earlier work searches for and summarizes and fully considers the influence of different operation modes on tumor assessment and prognosis, the operation risk and the early postoperative prognosis are judged through indexes, the method is different from the current prediction model and depends on the combination of data and an algorithm.
The follow-up study of later data under different operation modes is a prospective study, and years of studies find that risk factors in the open partial nephrectomy and the early prognosis of an operation patient are mainly related to the size of a tumor in a kidney and the transverse position of the tumor on a coronal plane; whereas the risk factors in non-open nephrectomy (endoscopic and robot-assisted endoscopic nephrectomy) and the early prognosis of the patient are mainly related to the size of the tumor in the kidney and the longitudinal position on the coronal plane. Therefore, for different surgical modes, we find that the two parameters of Rx and ML can better evaluate the surgical risk (the p value is less than 0.05) in the open kidney resection operation through the multi-factor regression analysis. And the Rx and LL parameters can better evaluate the risk of the endoscopic surgery (the p value is less than 0.05).
The main application scenario of the kidney tumor Zhongshan score is preoperative evaluation of a patient diagnosed with a kidney tumor, which is firstly divided into two cases according to different operation modes: open surgery and non-open surgery (endoscopic and robot-assisted laparoscopic partial nephrectomy). According to the imaging data of the CT before the operation of the patient, a basic index Rx for the evaluation of the renal tumor is obtained, wherein Rx is the product of the maximum diameter (A) of the part of the tumor in the kidney and the diameter (B) vertical to the maximum diameter. The other evaluation index is a tumor position index, and for the tumor position index in the open surgery, which is ML, the ML is the tumor edge position index, the score judgment is carried out according to the tumor positions at the inner side (2 scores) and the outer side (1 score) of the kidney; the medial-lateral boundary is defined as the line connecting the bilateral renal cortex and the renal calyx (line C in FIG. 1), and the boundary touched, or located inside the boundary but not touching the renal portal vessels, is defined as the renal tumor located inside (score 2), otherwise outside (score 1); for the non-open surgery, the tumor position index is LL, LL is the longitudinal position index of the tumor, and the score is based on two epipolar lines on the coronal plane of the kidney, as shown by line D, E in FIG. 2, line D is the horizontal line of the superior border of the hilum, and line E is the horizontal line of the inferior border of the hilum. Score 1 is obtained if the tumor is completely above or below the polar line, and score 2 is obtained if the middle of the polar line is involved. In open surgery, renal tumors score Rx + ML; in non-open surgery, renal tumors scored as Rx + LL (see table 1 for details). The score can be applied to preoperative auxiliary operation type selection of a renal tumor patient so as to avoid postoperative complications to the maximum extent. The urologist needs to perfect the score before surgery and fully inform the patient and family members of the corresponding risks and then carefully select the surgery mode of the patient, so as to avoid the possibility of postoperative complications of the patient to the greatest extent.
TABLE 1
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (4)
1. An index evaluation method for renal tumor partial resection risk and postoperative early prognosis is characterized in that firstly, the renal tumor partial resection risk and postoperative early prognosis index are divided into open operation and non-open operation according to different operation modes; acquiring the sum of a basic index Rx of the renal tumor and a position index of the tumor as a preoperative index evaluation index according to the imaging data of preoperative CT of a patient; wherein Rx is the product of the maximum diameter a of the portion of the tumor within the kidney and the diameter B perpendicular to the maximum diameter; the position index of the tumor in the open surgery is ML, the ML is the edge position index of the tumor, the position index of the tumor in the non-open surgery is LL, and the LL is the longitudinal position index of the tumor.
2. The method of claim 1, wherein the tumor margin index ML is a score of a tumor located inside or outside a kidney; the boundary between the inside and outside is defined as the line connecting the renal cortex and the renal calyx on both sides, and the boundary touching or located inside the boundary but not touching the renal portal vessels is defined as the renal tumor located inside, otherwise, it is located outside, 2 points inside and 1 point outside.
3. The method of claim 1 or 2, wherein the tumor location index for non-open surgery is LL, LL is the tumor longitudinal location index LL is scored according to D, E two epipolar lines on the coronal plane of the kidney, D is the horizontal line of the superior border of the renal hilum, and E is the horizontal line of the inferior border of the renal hilum; score 1 is obtained if the tumor is completely above or below the polar line, and score 2 is obtained if the middle of the polar line is involved.
4. The method of claim 3, wherein the pre-operative index evaluation index is used for evaluating the risk of renal tumor resection and the early prognosis after surgery in different ways.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110980160.7A CN113517071A (en) | 2021-08-25 | 2021-08-25 | Index evaluation method for renal tumor partial resection risk and postoperative early prognosis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110980160.7A CN113517071A (en) | 2021-08-25 | 2021-08-25 | Index evaluation method for renal tumor partial resection risk and postoperative early prognosis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113517071A true CN113517071A (en) | 2021-10-19 |
Family
ID=78062807
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110980160.7A Pending CN113517071A (en) | 2021-08-25 | 2021-08-25 | Index evaluation method for renal tumor partial resection risk and postoperative early prognosis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113517071A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102982238A (en) * | 2012-11-13 | 2013-03-20 | 深圳市环球博洋机电科技有限公司 | Three-dimensional kidney neoplasm surgery simulation method and platform based on computed tomography (CT) film |
| CN109727679A (en) * | 2018-07-30 | 2019-05-07 | 中国医学科学院肿瘤医院 | A kind of scoring of cervical anastomosis Resection of Esophageal Carcinoma surgical site infection risk profile and system |
| CN113223723A (en) * | 2021-05-11 | 2021-08-06 | 胡敏雄 | Method for predicting multi-modal kidney tumor kidney protection operation difficulty and complications |
-
2021
- 2021-08-25 CN CN202110980160.7A patent/CN113517071A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102982238A (en) * | 2012-11-13 | 2013-03-20 | 深圳市环球博洋机电科技有限公司 | Three-dimensional kidney neoplasm surgery simulation method and platform based on computed tomography (CT) film |
| CN109727679A (en) * | 2018-07-30 | 2019-05-07 | 中国医学科学院肿瘤医院 | A kind of scoring of cervical anastomosis Resection of Esophageal Carcinoma surgical site infection risk profile and system |
| CN113223723A (en) * | 2021-05-11 | 2021-08-06 | 胡敏雄 | Method for predicting multi-modal kidney tumor kidney protection operation difficulty and complications |
Non-Patent Citations (4)
| Title |
|---|
| SYLVIA MONTAG等: "Reproducibility and Fidelity of the R．E．N．A．L．Nephrometry Score", 《J ENDOUROL》 * |
| VINCENZO FICARRA等: "Preoperative Aspects and Dimensions Used for an Anatomical(PADUA)Classification of Renal Turnours in Patients who are Candidates for Nephron—Sparing Surgery", 《EUR UROL》 * |
| 吴岩: "肾动脉CTA在后腹腔镜肾癌根治术及保留肾单位术中的应用价值研究", 《中国优秀硕士学位论文全文数据库》 * |
| 时代: "基于CT的R.E.N.A.L.肾肿瘤评分对保留肾单位手术价值的研究", 《中国优秀硕士学位论文全文数据库（电子期刊）》, pages 23 - 24 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Fine et al. | A contemporary update on pathology reporting for prostate cancer: biopsy and radical prostatectomy specimens | |
| CN105319364B (en) | For predicting that the Combining diagnosis of microhepatia cancer recurrence is marked | |
| Silverstein et al. | Ductal carcinoma in situ: USC/Van Nuys Prognostic Index and the impact of margin status | |
| Yuh et al. | Robotic extended pelvic lymphadenectomy for intermediate-and high-risk prostate cancer | |
| Yuh et al. | Analysis of regional lymph nodes in periprostatic fat following robot‐assisted radical prostatectomy | |
| Kusuda et al. | Gender as a significant predictor of intravesical recurrence in patients with urothelial carcinoma of the upper urinary tract following nephroureterectomy | |
| CN111916154B (en) | Diagnostic marker for predicting intestinal cancer liver metastasis and application thereof | |
| Tay et al. | Active surveillance for prostate cancer: can we modernize contemporary protocols to improve patient selection and outcomes in the focal therapy era? | |
| Tan et al. | The sick lobe hypothesis, field cancerisation and the new era of precision breast surgery | |
| Li et al. | Risk factors of positive resection margin differ in pancreaticoduodenectomy and distal pancreatosplenectomy for pancreatic ductal adenocarcinoma undergoing upfront surgery | |
| Maino et al. | Radiomics and liver: Where we are and where we are headed? | |
| Li et al. | Safety and efficacy of left colic artery preservation in laparoscopic anterior resection for lower rectal cancer | |
| González et al. | Adenoma-like adenocarcinoma: clinicopathologic characterization of a newly recognized subtype of colorectal carcinoma | |
| Faus et al. | The role of the pathologist in rectal cancer diagnosis and staging and surgical quality assessment | |
| CN113517071A (en) | Index evaluation method for renal tumor partial resection risk and postoperative early prognosis | |
| Cui et al. | Construction and clinical significance of a predictive system for prognosis of hepatocellular carcinoma | |
| Tannapfel et al. | The prediction of lymph node metastases in colorectal cancer by expression of the nucleoside diphosphate kinase/nm23-H1 and histopathological variables. | |
| Falzarano et al. | Staging prostate cancer and its relationship to prognosis | |
| Wang et al. | THROBVS Score–A Comprehensive Model to Predict the Surgical Complexity of Renal Cell Carcinoma With Tumor Thrombus | |
| Ficarra et al. | Staging system of renal cell carcinoma: current issues | |
| Peng et al. | Progress in the diagnosis of lymph node metastasis in rectal cancer: a review | |
| Eminaga et al. | Preoperative serum prostate-specific antigen levels vary according to the topographical distribution of prostate cancer in prostatectomy specimens | |
| Xia et al. | A novel nomogram to predict resectable gastric cancer based on preoperative circulating tumor cell (CTC) | |
| Aragon-Ching et al. | Formidable scenarios in urothelial and variant cancers of the urinary tract | |
| Lv et al. | [Retracted] Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |