Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model:A dual-center study

BACKGROUND Perineural invasion(PNI)has been used as an important pathological indicator and independent prognostic factor for patients with rectal cancer(RC).Preoperative prediction of PNI status is helpful for individualized treatment of RC.Recently,several radiomics studies have been used to predict the PNI status in RC,demonstrating a good predictive effect,but the results lacked generalizability.The preoperative prediction of PNI status is still challenging and needs further study.AIM To establish and validate an optimal radiomics model for predicting PNI status preoperatively in RC patients.METHODS This retrospective study enrolled 244 postoperative patients with pathologically confirmed RC from two independent centers.The patients underwent preoperative high-resolution magnetic resonance imaging(MRI)between May 2019 and August 2022.Quantitative radiomics features were extracted and selected from oblique axial T2-weighted imaging(T2WI)and contrast-enhanced T1WI(T1CE)sequences.The radiomics signatures were constructed using logistic regression analysis and the predictive potential of various sequences was compared(T2WI,T1CE and T2WI+T1CE fusion sequences).A clinical-radiomics(CR)model was established by combining the radiomics features and clinical risk factors.The internal and external validation groups were used to validate the proposed models.The area under the receiver operating characteristic curve(AUC),DeLong test,net reclassification improvement(NRI),integrated discrimination improvement(IDI),calibration curve,and decision curve analysis(DCA)were used to evaluate the model performance.RESULTS Among the radiomics models,the T2WI+T1CE fusion sequences model showed the best predictive performance,in the training and internal validation groups,the AUCs of the fusion sequence model were 0.839[95%confidence interval(CI):0.757-0.921]and 0.787(95%CI:0.650-0.923),which were higher than those of the T2WI and T1CE sequence models.The CR model constructed by combining clinical risk factors had the best predictive performance.In the training and internal and external validation groups,the AUCs of the CR model were 0.889(95%CI:0.824-0.954),0.889(95%CI:0.803-0.976)and 0.894(95%CI:0.814-0.974).Delong test,NRI,and IDI showed that the CR model had significant differences from other models(P<0.05).Calibration curves demonstrated good agreement,and DCA revealed significant benefits of the CR model.CONCLUSION The CR model based on preoperative MRI radiomics features and clinical risk factors can preoperatively predict the PNI status of RC noninvasively,which facilitates individualized treatment of RC patients.

Preoperative prediction of lymphovascular and perineural invasion in gastric cancer using spectral computed tomography imaging and machine learning

BACKGROUND Lymphovascular invasion(LVI)and perineural invasion(PNI)are important prognostic factors for gastric cancer(GC)that indicate an increased risk of metastasis and poor outcomes.Accurate preoperative prediction of LVI/PNI status could help clinicians identify high-risk patients and guide treatment deci-sions.However,prior models using conventional computed tomography(CT)images to predict LVI or PNI separately have had limited accuracy.Spectral CT provides quantitative enhancement parameters that may better capture tumor invasion.We hypothesized that a predictive model combining clinical and spectral CT parameters would accurately preoperatively predict LVI/PNI status in GC patients.AIM To develop and test a machine learning model that fuses spectral CT parameters and clinical indicators to predict LVI/PNI status accurately.METHODS This study used a retrospective dataset involving 257 GC patients(training cohort,n=172;validation cohort,n=85).First,several clinical indicators,including serum tumor markers,CT-TN stages and CT-detected extramural vein invasion(CT-EMVI),were extracted,as were quantitative spectral CT parameters from the delineated tumor regions.Next,a two-step feature selection approach using correlation-based methods and information gain ranking inside a 10-fold cross-validation loop was utilized to select informative clinical and spectral CT parameters.A logistic regression(LR)-based nomogram model was subsequently constructed to predict LVI/PNI status,and its performance was evaluated using the area under the receiver operating characteristic curve(AUC).RESULTS In both the training and validation cohorts,CT T3-4 stage,CT-N positive status,and CT-EMVI positive status are more prevalent in the LVI/PNI-positive group and these differences are statistically significant(P<0.05).LR analysis of the training group showed preoperative CT-T stage,CT-EMVI,single-energy CT values of 70 keV of venous phase(VP-70 keV),and the ratio of standardized iodine concentration of equilibrium phase(EP-NIC)were independent influencing factors.The AUCs of VP-70 keV and EP-NIC were 0.888 and 0.824,respectively,which were slightly greater than those of CT-T and CT-EMVI(AUC=0.793,0.762).The nomogram combining CT-T stage,CT-EMVI,VP-70 keV and EP-NIC yielded AUCs of 0.918(0.866-0.954)and 0.874(0.784-0.936)in the training and validation cohorts,which are significantly higher than using each of single independent factors(P<0.05).CONCLUSION The study found that using portal venous and EP spectral CT parameters allows effective preoperative detection of LVI/PNI in GC,with accuracy boosted by integrating clinical markers.

Non-coding RNA as future target for diagnose and treatment of perineural invasion in cancers

Perineural invasion(PNI),a particularly insidious form of tumor metastasis distinct from hematogenous or lymphatic spread,has the capacity to extend well beyond the primary tumor site,infiltrating distant regions devoid of lymphatic or vascular structures.PNI often heralds a decrease in patient survival rates and is recognized as an indicator of an unfavorable prognosis across a variety of cancers.Despite its clinical significance,the underlying molecular mechanisms of PNI remain elusive,complicating the development of specific and efficacious diagnostic and therapeutic strategies.In the realm of cancer research,non-coding RNAs(ncRNAs)have attracted considerable attention due to their multifaceted roles and cancer-specific expression profiles,positioning them as promising candidates for applications in cancer diagnostics,prognostics,and treatment.Among the various types of ncRNAs,microRNAs(miRNAs),long non-coding RNAs(lncRNAs),and circular RNAs(circRNAs)have emerged as influential players in PNI.Their involvement is increasingly recognized as a contributing factor to tumor progression and therapeutic resistance.Our study synthesizes and explores the diverse functions and mechanisms of ncRNAs in relation to PNI in cancer.This comprehensive review aims to shed light on cutting-edge perspectives that could pave the way for innovative diagnostic and therapeutic approaches to address the challenges posed by PNI in oncology.

Prediction of the lymphatic,microvascular,and perineural invasion of pancreatic neuroendocrine tumors using preoperative magnetic resonance imaging

BACKGROUND Significant correlation between lymphatic,microvascular,and perineural invasion(LMPI)and the prognosis of pancreatic neuroendocrine tumors(PENTs)was confirmed by previous studies.There was no previous study reported the relationship between magnetic resonance imaging(MRI)parameters and LMPI.AIM To determine the feasibility of using preoperative MRI of the pancreas to predict LMPI in patients with non-functioning PENTs(NFPNETs).METHODS A total of 61 patients with NFPNETs who underwent MRI scans and lymphadenectomy from May 2011 to June 2018 were included in this retrospective study.The patients were divided into group 1(n=34,LMPI negative)and group 2(n=27,LMPI positive).The clinical characteristics and qualitative MRI features were collected.In order to predict LMPI status in NF-PNETs,a multivariate logistic regression model was constructed.Diagnostic performance was evaluated by calculating the receiver operator characteristic(ROC)curve with area under ROC,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV)and accuracy.RESULTS There were significant differences in the lymph node metastasis stage,tumor grade,neuron-specific enolase levels,tumor margin,main pancreatic ductal dilatation,common bile duct dilatation,enhancement pattern,vascular and adjacent tissue involvement,synchronous liver metastases,the long axis of the largest lymph node,the short axis of the largest lymph node,number of the lymph nodes with short axis>5 or 10 mm,and tumor volume between two groups(P<0.05).Multivariate analysis showed that tumor margin(odds ratio=11.523,P<0.001)was a predictive factor for LMPI of NF-PNETs.The area under the receiver value for the predictive performance of combined predictive factors was 0.855.The sensitivity,specificity,PPV,NPV and accuracy of the model were 48.1%(14/27),97.1%(33/34),97.1%(13/14),70.2%(33/47)and 0.754,respectively.CONCLUSION Using preoperative MRI,ill-defined tumor margins can effectively predict LMPI in patients with NF-PNETs.

Pleiotrophin promotes perineural invasion in pancreatic cancer

Perineural invasion(PNI)in pancreatic cancer is an important cause of local recurrence,but little is known about its mechanism.Pleiotrophin(PTN)is an important neurotrophic factor.It is of interest that our recent experimental data showed its involvement in PNI of pancreatic cancer.PTN strongly presents in the cytoplasm of pancreatic cancer cells,and high expression of PTN and its receptor may contribute to the high PNI of pancreatic cancer.Correspondingly,PNI is prone to happen in PTN-positive tumors.We thus hypothesize that,as a neurite growth-promoting factor,PTN may promote PNI in pancreatic cancer.PTN is released at the time of tumor cell necrosis,and binds with its highaffinity receptor,N-syndecan on pancreatic nerves,to promote neural growth in pancreatic cancer.Furthermore,neural destruction leads to a distorted neural homeostasis.Neurons and Schwann cells produce more N-syndecan in an effort to repair the pancreatic nerves.However,the abundance of N-syndecan attracts further PTN-positive cancer cells to the site of injury,creating a vicious cycle.Ultimately,increased PTN and N-syndecan levels,due to the continuous nerve injury,may promote cancer invasion and propagation along the neural structures.Therefore,it is meaningful to discuss the relationship between PTN/N-syndecan signaling and PNI in pancreatic cancer,which may lead to a better understanding of the mechanism of PNI in pancreatic cancer.

Relationship between autophagy and perineural invasion, clinicopathological features, and prognosis in pancreatic cancer

AIM To investigate the relationship between autophagy and perineural invasion(PNI), clinical features, and prognosis in patients with pancreatic cancer. METHODS Clinical and pathological data were retrospectively collected from 109 patients with pancreatic ductal adenocarcinoma who underwent radical resection at the First Affiliated Hospital of Zhengzhou University from January 2011 to August 2016. Expression levels of the autophagy-related protein microtubuleassociated protein 1 A/1 B-light chain 3(LC3) and PNI marker ubiquitin carboxy-terminal hydrolase(UCH) in pancreatic cancer tissues were detected by immunohistochemistry. The correlations among LC3 expression, PNI, and clinical pathological features in pancreatic cancer were analyzed. The patients were followed for further survival analysis. RESULTS In 109 cases of pancreatic cancer, 68.8%(75/109) had evidence of PNI and 61.5%(67/109) had high LC3 expression. PNI was associated with lymph node metastasis, pancreatitis, and CA19-9 levels(P < 0.05). LC3 expression was related to lymph node metastasis(P < 0.05) and was positively correlated with neural invasion(P < 0.05, r = 0.227). Multivariate logistic regression analysis indicated that LC3 expression, lymph node metastasis, pancreatitis, and CA19-9 level were factors that influenced neural invasion, whereas only neural invasion itself was an independent factor for high LC3 expression. Univariate analysis showed that LC3 expression, neural invasion, and CA19-9 level were related to the overall survival of pancreatic cancer patients(P < 0.05). Multivariate COX regression analysis indicated that PNI and LC3 expression were independent risk factors for poor prognosis in pancreatic cancer(P < 0.05). CONCLUSION PNI in patients with pancreatic cancer is positively related to autophagy. Neural invasion and LC3 expression are independent risk factors for pancreatic cancer with a poor prognosis.

Preliminary study correlating CX3CL1/CX3CR1 expression with gastric carcinoma and gastric carcinoma perineural invasion

AIM: To study the relationship between the CX3CL1 chemokine, its receptor CX3CR1, and gastric carcinoma/gastric carcinoma perineural invasion (PNI).

Midkine promotes perineural invasion in human pancreatic cancer

AIM: To investigate midkine (MK) and syndecan-3 protein expression in pancreatic cancer by immunohistochemistry, and to analyze their correlation with clinicopathological features, perineural invasion, and prognosis.

Radiomics for predicting perineural invasion status in rectal cancer

BACKGROUND Perineural invasion(PNI),as a key pathological feature of tumor spread,has emerged as an independent prognostic factor in patients with rectal cancer(RC).The preoperative stratification of RC patients according to PNI status is beneficial for individualized treatment and improved prognosis.However,the preoperative evaluation of PNI status is still challenging.AIM To establish a radiomics model for evaluating PNI status preoperatively in RC patients.METHODS This retrospective study enrolled 303 RC patients in a single institution from March 2018 to October 2019.These patients were classified as the training cohort(n=242)and validation cohort(n=61)at a ratio of 8:2.A large number of intraand peritumoral radiomics features were extracted from portal venous phase images of computed tomography(CT).After deleting redundant features,we tested different feature selection(n=6)and machine-learning(n=14)methods to form 84 classifiers.The best performing classifier was then selected to establish Rad-score.Finally,the clinicoradiological model(combined model)was developed by combining Rad-score with clinical factors.These models for predicting PNI were compared using receiver operating characteristic curve(ROC)analysis and area under the ROC curve(AUC).RESULTS One hundred and forty-four of the 303 patients were eventually found to be PNIpositive.Clinical factors including CT-reported T stage(cT),N stage(cN),and carcinoembryonic antigen(CEA)level were independent risk factors for predicting PNI preoperatively.We established Rad-score by logistic regression analysis after selecting features with the L1-based method.The combined model was developed by combining Rad-score with cT,cN,and CEA.The combined model showed good performance to predict PNI status,with an AUC of 0.828[95%confidence interval(CI):0.774-0.873]in the training cohort and 0.801(95%CI:0.679-0.892)in the validation cohort.For comparison of the models,the combined model achieved a higher AUC than the clinical model(cT+cN+CEA)achieved(P<0.001 in the training cohort,and P=0.045 in the validation cohort).CONCLUSION The combined model incorporating Rad-score and clinical factors can provide an individualized evaluation of PNI status and help clinicians guide individualized treatment of RC patients.

Muscarinic acetylcholine receptor M3 in proliferation and perineural invasion of cholangiocarcinoma cells

BACKGROUND:Cholangiocarcinoma,a type of malignant tumor,originates from epithelial cells of the bile duct.Perineural invasion is common path for cholangiocarcinoma metastasis,and it is highly correlated with postoperative recurrence and poor prognosis.It has been reported that muscarinic acetylcholine receptor M3(mAChR M3) is widely expressed in digestive tract cancer,and may play an important role in the proliferation,differentiation,transformation and carcinogenesis of tumors.This study was to explore the effect of mAChR M3 on the growth of cholangiocarcinoma cells in vitro and provide a new approach to the pathogenesis and treatment of cholangiocarcinoma.METHODS:Streptavidin-biotin complex immunohistochemistry was carried out to assess the expression of mAChR M3 in surgical specimens of cholangiocarcinomas(40 cases) and normal bile duct tissues(9),as well as to investigate nerve infiltration.The cholangiocarcinoma cells were treated with different concentrations of selective M-receptor agonist pilocarpine and M-receptor blocker atropine sulfate to induce changes in cell proliferation.The experimental data were analyzed by the Chi-square test.RESULTS:The strongly-positive expression rate of mAChR M3 was much higher in poorly-differentiated(69%,9/13) than in well-and moderately-differentiated cholangiocarcinomas(30%,8/27)(χ 2 =5.631,P<0.05).The strongly-positive mAChR M3 expression rate in hilar cholangiocarcinoma(50%,14/28) was higher than that in cholangiocarcinomas from the middle and lower common bile duct(25%,3/12)(χ 2 =2.148,P<0.05).Cholangiocarcinomas with distant metastasis had a stronglypositive expression rate(75%,9/12),which was much higher than those without distant metastasis(29%,8/28)(χ 2 =7.410,P<0.01).The absorbance value in the pilocarpine+atropine group was significantly higher than the corresponding value in the pilocarpine group.CONCLUSIONS:The expression of mAChR M3 is influenced by the extent of differentiation,distant metastasis and the site of cholangiocarcinoma.It also plays a key role in the proliferation and metastasis of cholangiocarcinoma.

Perineural invasion of hilar cholangiocarcinoma in Chinese population: One center’s experience

BACKGROUND Hilar cholangiocarcinoma(HCCA)often produces perineural invasion(PNI)extending to extra-biliary sites,while significant confusion in the incidence of PNI in HCCA has occurred in the literature,and the mechanism of that procedure remains unclear.AIM To summarize the incidence of PNI in HCCA and to provide the distribution of nerve plexuses around hepatic portal to clinical surgeons.METHODS Reported series with PNI in HCCA since 1996 were reviewed.A clinicopathological study was conducted on sections from 75 patients with HCCA to summarize the incidence and modes of PNI.Immunohistochemical stains for CD34 and D2-40 in the cancer tissue were performed to clarify the association of PNI with microvessel and lymph duct.Sections of the hepatoduodenal ligament from autopsy cases were scanned and handled by computer to display the distribution of nerve plexuses around the hepatic portal.RESULTS The overall incidence of PNI in this study was 92%(69 of 75 patients),while the rate of PNI in HCCA in the literature ranging from 38%to 100%.The incidence of PNI did not show any remarkable differences among various differentiated groups and Bismuth-Corlette classification groups.Logistic regression analysis identified the depth of tumor invasion was the only factor that correlated significantly with PNI(P<0.01).In spite of finding tumor cells that could invade microvessels and lymph ducts in HCCA,we did not find tumor cells invaded nerves via microvessels or lymph ducts.Three nerve plexuses in the hepatoduodenal ligament and Glisson’s sheath were classified,and they all surrounded the great vessels very closely.CONCLUSION The incidence of PNI of HCCA in Chinese population is around 92%and correlated significantly with a depth of tumor invasion.It also should be considered when stratifying HCCA patients for further treatment.

Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model

Objective： To develop and validate a radiomics prediction model for individualized prediction of perineural invasion（PNI） in colorectal cancer（CRC）.Methods： After computed tomography（CT） radiomics features extraction, a radiomics signature was constructed in derivation cohort（346 CRC patients）. A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen（CEA） level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation（separate from the cohort used to build the model） was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram.Results： The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell＇s concordance index（c-index）： 0.817; 95% confidence interval（95% CI）： 0.811–0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination（c-index： 0.803; 95% CI： 0.794–0.812）.Conclusions： Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

Pleiotrophin and N-syndecan promote perineural invasion and tumor progression in an orthotopic mouse model of pancreatic cancer

AIM To detect the expression of pleiotrophin(PTN) and N-syndecan in pancreatic cancer and analyze their association with tumor progression and perineural invasion(PNI).METHODS An orthotopic mouse model of pancreatic cancer was created by injecting tumor cells subcapsularly in a root region of the pancreas beneath the spleen. Pancreatic cancer tissues were taken from 36 mice that survived for more than 90 d. PTN and N-syndecan proteins were detected by immunohistochemistry and analyzed for their correlation with pathological features, PNI, and prognosis.RESULTS The expression rates of PTN and N-syndecan proteinswere 66.7% and 61.1%, respectively, in cancer tissue. PTN and N-syndecan expression was associated with PNI(P = 0.019 and P = 0.032, respectively). High PTN expression was closely associated with large bloody ascites(P = 0.009), liver metastasis(P = 0.035), and decreased survival time(P = 0.022). N-syndecan expression was significantly associated with tumor size(P = 0.025), but not with survival time(P = 0.539). CONCLUSION High PTN and N-syndecan expression was closely associated with metastasis and poor prognosis, suggesting that they may promote tumor progression and PNI in the orthotopic mouse model of pancreatic cancer.

Perineural invasion as a prognostic factor in patients with stage Ⅰ-Ⅲ rectal cancer –5-year follow up

BACKGROUND Rectal cancer(RC)is one of the most common diagnosed cancers,and one of the major causes of cancer-related death nowadays.Majority of the current guidelines rely on TNM classification regarding therapy regiments,however recent studies suggest that additional histopathological findings could affect the disease course.AIM To determine whether perineural invasion alone or in combination with lymphovascular invasion have an effect on 5-years overall survival(OS)of RC patients.METHODS A prospective study included newly diagnosed stage I-III RC patients treated and followed at the Digestive Surgery Clinic,Clinical Center of Serbia,between the years of 2014–2016.All patients had their diagnosis histologically confirmed in accordance with both TMN and Dukes classification.In addition,the patient’s demographics,surgical details,postoperative pathological details,differentiation degree and their correlation with OS was investigated.RESULTS Of 245 included patients with stage Ⅰ-Ⅲ RC,lymphovascular invasion(LVI)was identified in 92 patients(38%),whereas perineural invasion(PNI)was present in 46 patients(19%).Using Kaplan-Meier analysis for overall survival rate,we have found that both LVI and PNI were associated with lower survival rates(P<0.01).Moreover when Cox multiple regression model was used,LVI,PNI,older age,male gender were predictors of poor prognosis(HR=5.49;95%CI:2.889-10.429;P<0.05).CONCLUSION LVI and PNI were significant factors predicting worse prognosis in early and intermediate RC patients,hence more aggressive therapy should be reserved for these patients after curative resection.

Relationship between cachexia and perineural invasion in pancreatic adenocarcinoma

BACKGROUND Cachexia is responsible for the low quality of life in pancreatic adenocarcinoma(PDAC).The rapid disease progression and patient deterioration seems related to perineural invasion,but the relationship between cachexia and perineural invasion for the evolution of the disease has been rarely studied.As perineural invasion is difficult to be highlighted,a biomarker such as the neurotrophic factor Midkine(MK)which promotes the neuronal differentiation and the cell migration could be helpful.Also,Activin(ACV)has been described as cachexia related to PDAC.However,their role for assessing and predicting the disease course in daily practice is not known.AIM To assess the relationship between perineural invasion and cachexia and their biomarkers,MK and ACV,respectively,and their prognostic value.METHODS This study included prospectively enrolled patients with proven adenocarcinoma and a matched group of controls without any malignancies.Patients with other causes of malnutrition were excluded.The plasma levels of ACV and MK were analyzed using western blotting and were correlated with the clinicopathological features and survival data.These results were validated by immunohistochemical analyses of the pancreatic tumor tissue of the patients included in the study and a supplementary group of surgically resected specimens from patients with a benign disease.RESULTS The study comprised 114 patients with PDAC,125 controls and a supplementary group of 14 benign pancreatic tissue samples.ACV and MK were both overexpressed more frequently in the plasma of patients with PDAC than in the controls(63% vs 32% for ACV,P<0.001;47%vs 16%for MK,P<0.001),with similar levels in pancreatic tissue the MK protein expression was closely related to the advanced clinical stage(P=0.006),the presence of metastasis(P=0.04),perineural invasion(P=0.03)and diabetes(P=0.002),but with no influence on survival.No correlation between clinicopathological factors and ACV expression was noted.Cachexia,present in 19%of patients,was unrelated to ACV or MK level.Higher ACV expression was associated with a shorter survival(P=0.008).CONCLUSION The MK was a biomarker of perineural invasion,associated with tumor stage and diabetes,but without prognostic value as ACV.Cachexia was unrelated to perineural invasion,ACV level or survival.

Perineural Invasion in Pancreatic Cancer： Advanced Research in the Neuro-cancer Interactions

Pancreatic Cancer （PCa） is characterized by prominently local nerve alterations and perineural invasion （PNI）, which frequently affects the extrapancreatic nerve plexus, causing severe pain and retropancreatic tumor extension. It precludes curative resection, promotes local recurrence, and at the last negatively influences the prognosis of patients. Recent research on PNI in PCa has revealed the critical involvement of numerous nerve- or cancer cell-derived molecules in vitro and in vivo. However, the mechanisms contributing to alteration and invasion of intrapancreatic nerves and the spread of cancer cells along extrapancreatic nerves in pancreatic cancer patients are still poorly understood. This review focuses on perineural invasion in pancreatic cancer and provides an outline of the characteristics and molecular mechanisms of perineural invasion in pancreatic cancer.

Treatment Recommendations among Radiation Oncologists in the Treatment of Cutaneous Squamous Cell Carcinoma with Perineural Invasion

Purpose: Post-operative radiotherapy (PORT) for resected cutaneous squamous cell carcinoma (CSCC) with perineural invasion (PNI) is controversial. Therefore, we conducted a survey to review treatment recommendations among Radiation Oncologists (ROs) in the management of CSCC with PNI. Materials & Methods: In March 2011, we contacted all ROs and trainees in the US through email addresses listed in the 2009 ASTRO directory. Our web-based survey presented clinical vignettes involving Mohs micrographically resected CSCC with microscopic PNI (mPNI) or clinical PNI (cPNI). For each vignette, ROs were asked to indicate if PORT was appropriate and to further specify the dose and volume to treat. Results: Three hundred fifty two responses were completed and analyzed. The majority of ROs (72%) had over 10 years of post residency experience. 64% of the sampled ROs had a special interest in treating head and neck cancers, and 64% treated 4 or more cases per year. Approximately 95% recommended PORT for cPNI whereas 59% recommended PORT for mPNI. Post residency experience (10+ yrs vs. <10 yrs) was associated with a greater propensity to recommend PORT for mPNI (48% vs. 30%, p = 0.005) and for mPNI of deep subcutaneous non-named nerve involvement (80% vs. 60%, p = 0.001). ROs treating 8 or more cases per year (vs. <7) were more likely to recommend PORT for mPNI in immunocompromised patients (74% vs. 57%, p = 0.01). Conclusions: Our study demonstrates significant variability among ROs in the management of CSCC with mPNI. For cases of cPNI, an overwhelming majority recommended PORT. In cases of mPNI, there was no consensus for recommending PORT, although experienced practitioners had a lower threshold for offering treatment. These results indicate the need for prospective clinical studies to clarify the role of PORT in CSCC patients with mPNI.

机器学习优化能谱CT预测胃腺癌的浸润性

目的探讨机器学习(ML)算法结合能谱CT定量参数和临床模型在预测胃腺癌(GAC)患者淋巴血管浸润(LVI)和神经周围浸润(PNI)的潜在价值。方法收集2017年12月—2022年5月经病理证实的GAC患者114例。研究参数涉及血清肿瘤标志物、CT-TN分期、CT评估壁外血管浸润(CT-EMVI)以及能谱CT定量参数。通过WEKA软件的Best-First算法进行特征筛选,并运用贝叶斯网络(BN)及支持向量机(SVM)算法建立模型。结果相较于LVI/PNI阴性组,LVI/PNI阳性组中CT-T_(3~4)期、CT-N阳性、CT-EMVI阳性、血清肿瘤标志物[糖类抗原(CA)72-4和CA19-9]更为常见,能谱CT参数也更高,差别均有统计学意义(P<0.05)。经特征选择,关键变量包括CT-T分期、CT-EMVI、VP-NIC和EP-70 keV CT值。基于这些变量,分别使用BN和SVM构建临床参数模型、能谱CT参数模型和混合模型,共6个模型。6个模型均展现了高预测性能,无过拟合现象。BN的混合模型预测性能最佳,AUC值为0.890~0.933,Delong检验显示其在统计学上具有显著优势(P<0.05);而SVM的混合模型与另外2种模型间的差别无统计学意义(P>0.05)。结论结合临床和能谱CT参数的ML模型能够高效能评估GAC患者的LVI和PNI状态,其中BN混合模型的准确性最高。

光谱CT多参数成像术前预测结肠癌神经及脉管侵犯状态的价值

目的:探讨光谱CT多参数成像术前预测结肠癌神经侵犯(PNI)及脉管侵犯(LVI)状态的价值。方法:搜集2021年9月至2022年9月在昆明医科大学第一附属医院行光谱CT扫描并经术后病理确诊为结肠癌的64例患者的临床及影像资料,根据术后病理中PNI/LVI的状态分为阳性组(29例)和阴性组(35例)。测量光谱CT动脉期、静脉期40 keV、90 keV单能级图像上病灶的CT值(CT40keV、CT90keV)、碘浓度(IC)、标准化碘浓度(NIC)、有效原子序数(Zeff)及标准化有效原子序数(NZeff),并计算光谱曲线斜率λ。比较两组间各光谱参数的差异,绘制受试者工作特征(ROC)曲线并计算曲线下面积(AUC)、敏感度、特异度及最佳阈值,以评估各参数的预测效能。结果:结肠癌PNI/LVI阳性组的动脉期和静脉期光谱CT定量参数CT40keV、IC、NIC、Zeff、NZeff及λ均高于阴性组,差异均有统计学意义(P均<0.05),而两组间动脉期和静脉期的CT90keV差异无统计学意义(P均>0.05)。ROC曲线分析结果显示,动脉期各参数预测结肠癌PNI/LVI状态的效能高于静脉期,其中以动脉期IC的预测效能最佳,其AUC值、敏感度和特异度分别为0.783(95%CI:0.672~0.894)、82.76%和65.71%。结论:光谱CT定量参数CT40keV、IC、NIC、Zeff、NZeff及λ在术前预测结肠癌PNI/LVI状态中具有一定价值,以动脉期IC的预测效能最佳。

基于增强CT的胆囊癌神经浸润危险因素分析及预测模型构建

目的基于术前增强CT影像特征构建胆囊癌(gallbladder carcinoma,GBC)神经浸润(perineural invasion,PNI)的预测模型并评价其预测效能。方法回顾性分析180例行根治术的GBC患者的临床、影像及病理资料。根据是否存在PNI分为阳性组与阴性组。由2位影像科医师评估术前增强CT影像特征(包括有无胆囊结石、影像肝侵犯、血管侵犯、T分期及肝门部或腹膜后淋巴结转移)。采用独立样本t检验、Mann-Whitney U检验及χ^(2)检验比较CT征象与PNI的相关性,采用Logistics回归分析筛选独立危险因素并建立预测模型公式,采用受试者工作特征(ROC)曲线评估预测模型的预测效能并计算相应的曲线下面积(AUC),采用Hosmer-Lemeshow拟合优度检验对预测模型进行验证。结果单因素分析结果显示CA199、CA125和影像肝侵犯、血管侵犯(肝动脉或门静脉)、T分期及肝门部或腹膜后淋巴结转移与PNI相关(P<0.05)。Logistics多因素分析结果显示CA199、影像血管侵犯(肝动脉或门静脉)、影像T分期是PNI的独立危险因素。依据上述独立危险因素建立预测模型公式并绘制ROC曲线,AUC为0.807(95%CI:0.734~0.879),灵敏度为0.792,特异度为0.697。Hosmer-Lemeshow拟合优度检验卡方值为0.594,P=0.997,提示模型的预测值与实际值接近。结论联合CA199、影像血管侵犯、T分期等术前临床-增强CT特征建立预测模型,能够有效预测GBC术后PNI。