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

Histogram analysis based on intravoxel incoherent motion diffusion-weighted imaging for determining the perineural invasion status of rectal cancer

Background

Unfortunately, the morphologic magnetic resonance imaging (MRI) is unable to determine perineural invasion (PNI) status. This study applied histogram analysis of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the assessment of PNI status of rectal cancer (RC).

Methods

The retrospective analysis enrolled 175 patients with RC confirmed by postoperative pathology in The First Affiliated Hospital of Shandong First Medical University from January 2019 to December 2021. All patients underwent preoperative rectal MRI. Whole-tumor volume histogram features from IVIM-DWI were extracted using open-source software. Univariate analysis and multivariate logistic regression analysis were used to compare the differences in histogram parameters and clinical features between the PNI-positive group and PNI-negative group. Receiver operating characteristic curve analysis was used to evaluate the diagnostic performance, while the Delong test was used to compare the area under the curve of the models.

Results

The interobserver agreement of the histogram features derived from DWI, including apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), water molecular diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC) were good to excellent. A total of eight histogram features including DWI_maximum, DWI_skewness, D_kurtosis, D_minimum, D_skewness, D*_energy, D*_skewness, and f_minimum were significantly different between the PNI-positive and PNI-negative groups in the univariate analysis (P<0.05); among the clinicoradiologic factors, percentage of rectal wall circumference invasion (PCI) was significantly different between the two groups (P<0.05). Multivariate analysis demonstrated that the values of D*_energy, D*_skewness, and f_minimum differed significantly between the PNI-positive patients and PNI-negative patients (P<0.05), with the independent risk factors being D*_skewness [odds ratio (OR) =1.157; 95% confidence interval (CI): 1.050-1.276; P=0.003] and PCI (OR =11.108, 95% CI: 1.767-69.838; P=0.0002). The area under the curve of the model combining the three histogram features and PCI to assess PNI status in RC was 0.807 (95% CI: 0.741-0.863). The results of the Delong test showed that the combined model was significantly different from each single-parameter model (P<0.05).

Conclusions

The combined model constructed on the basis of IVIM-DWI histogram features may help to assess the status of RC PNI.

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 pre-operative 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.

Perineural invasion in colorectal cancer: mechanisms of action and clinical relevance

BACKGROUND

In recent years, the significance of the nervous system in the tumor microenvironment has gained increasing attention. The bidirectional communication between nerves and cancer cells plays a critical role in tumor initiation and progression. Perineural invasion (PNI) occurs when tumor cells invade the nerve sheath and/or encircle more than 33% of the nerve circumference. PNI is a common feature in various malignancies and is associated with tumor invasion, metastasis, cancer-related pain, and unfavorable clinical outcomes. The colon and rectum are highly innervated organs, and accumulating studies support PNI as a histopathologic feature of colorectal cancer (CRC). Therefore, it is essential to investigate the role of nerves in CRC and comprehend the mechanisms of PNI to impede tumor progression and improve patient survival.

CONCLUSION

This review elucidates the clinical significance of PNI, summarizes the underlying cellular and molecular mechanisms, introduces various experimental models suitable for studying PNI, and discusses the therapeutic potential of targeting this phenomenon. By delving into the intricate interactions between nerves and tumor cells, we hope this review can provide valuable insights for the future development of CRC treatments.

Bioinformatics analysis of markers based on m6A related to prognosis combined with immune invasion of rectal adenocarcinoma

BACKGROUND

Colorectal cancer (CRC) is a common form of cancer, with rectal cancer accounting for approximately one-third of all cases. Among rectal cancers, 95% are classified as rectal adenocarcinoma (READ). Emerging evidence suggests that long noncoding RNAs (lncRNAs) play a significant role in the development and progression of various cancers. In our study, we aimed to identify differentially expressed lncRNAs potentially associated with m6A and establish a risk assessment model to predict clinical outcomes for READ patients.

METHODS

The READ dataset from the TCGA database was utilized in this study to synergistically and logically integrate m6A and lncRNA, while employing bioinformatics technology for the identification of suitable biomarkers. A risk prediction model comprising m6A-associated lncRNAs was constructed to investigate the prognostic, diagnostic, and biological functional relevance of these m6A-related lncRNAs.

RESULTS

Our research builds a composed of three related to m6A lncRNA rectal gland cancer prognosis model, and the model has been proved in the multi-dimensional can serve as the potential of the prognosis of rectal gland cancer biomarkers. Our study constructed a prognostic model of rectal adenocarcinoma consisting of three related m6A lncRNAs: linc00702, ac106900.1 and al583785.1.

CONCLUSION

The model has been validated as a potential prognostic biomarker for rectal cancer in multiple dimensions, aiming to provide clinicians with an indicator to assess the duration of straight adenocarcinoma. This enables early detection of rectal cancer and offers a promising target for immunotherapy.

The Incidence of Lymphovascular and Perineural Invasion and their Impact on Survival in Patients with Rectal Cancer

Aim: Lymphovascular Invasion (LVI) and Perineural Invasion (PNI) represent undesirable but still realistic pathological features of rectal cancer, associated with poor prognosis and worse survival. The aim of this study is to assess the incidence of LVI and PNI in patients treated for rectal cancer and the impact of LVI and PNI on patient survival. Material and Methods: This retrospective single center observational study, conducted in the period of 2016-2019, includes patients with rectal cancer treated with/without long-course neoadjuvant chemoradiotherapy (nCRT). Data collection encompassed demographics, tumor characteristics, type of surgery (abdominal perineal rectal resection - APR and low anterior rectal resection - LAR), and LVI/PNI presence. Survival during follow-up was estimated and compared for patients with/without LVI and PNI involvement. Results: A total number of 234 patients (77 females and 157 males) with mean age of 61.3 enrolled in the study. Neoadjuvant CRT was conducted in 170 patients. APR procedure was performed in 67 of them and LAR in 167. LVI presence was noted in 55 (24.4%) and PNI in 77 (34.2%) patients. Mean survival during follow-up was 42.07 months. The use of nCRT influenced on survival (p < 0.033). Patients treated with LAR had better survival outcomes (p = 0.001). Presence of LVI and PNI was associated with a worse prognosis (p < 0.001). Conclusion: PNI was more frequent than the LVI in this study. Patients with nCRT conduction had better overall survival. LVI and PNI presence was associated with poor prognosis in terms of overall survival in patients with rectal cancer.

Perineural Invasion and Spread in Common Abdominopelvic Diseases: Imaging Diagnosis and Clinical Significance

Malignancies and other diseases may spread by multiple pathways, including direct extension, hematogenous spread, or via lymphatic vessels. A less-well-understood route is the peripheral nervous system, which is known as perineural spread (PNS). In addition to accounting for pain and other neurologic symptoms, PNS affects both disease prognosis and management. Although PNS is commonly discussed in relation to head and neck tumors, there is emerging data regarding PNS in abdominopelvic malignancies and other conditions such as endometriosis. Due to improved contrast and spatial resolution, perineural invasion, a finding heretofore diagnosed only at pathologic examination, can be detected at CT, MRI, and PET/CT. PNS most commonly manifests as abnormal soft-tissue attenuation extending along neural structures, and diagnosis of it is aided by optimizing imaging parameters, understanding pertinent anatomy, and becoming familiar with the typical neural pathways of spread that largely depend on the disease type and location. In the abdomen, the celiac plexus is a central structure that innervates the major abdominal organs and is the principal route of PNS in patients with pancreatic and biliary carcinomas. In the pelvis, the lumbosacral plexus and inferior hypogastric plexus are the central structures and principal routes of PNS in patients with pelvic malignancies. Although the imaging findings of PNS may be subtle, a radiologic diagnosis can have a substantial effect on patient care. Knowledge of anatomy and known routes of PNS and optimizing imaging parameters is of utmost importance in providing key information for prognosis and treatment planning. © RSNA, 2023 Supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article. Quiz questions for this article are available through the Online Learning Center.

Predicting perineural invasion using histogram analysis of zoomed EPI diffusion-weighted imaging in rectal cancer

PURPOSE

To investigate the utility of histogram analysis of zoomed EPI diffusion-weighted imaging (DWI) for predicting the perineural invasion (PNI) status of rectal cancer (RC).

METHODS

This prospective study evaluated 94 patients diagnosed with histopathologically confirmed RC between July 2020 and July 2021. Patients underwent preoperative rectal magnetic resonance imaging (MRI) examinations, including the zoomed EPI DWI sequence. Ten whole-tumor histogram parameters of each patient were derived from zoomed EPI DWI. Reproducibility was evaluated according to the intra-class correlation coefficient (ICC). The association of the clinico-radiological and histogram features with PNI status was assessed using univariable analysis for trend and multivariable logistic regression analysis with β value calculation. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance.

RESULTS

Forty-two patients exhibited positive PNI. The inter- and intraobserver agreements were excellent for the histogram parameters (all ICCs > 0.80). The maximum (p = 0.001), energy (p = 0.021), entropy (p = 0.021), kurtosis (p < 0.001), and skewness (p < 0.001) were significantly higher in the positive PNI group than in the negative PNI group. Multivariable analysis showed that higher MRI T stage [β = 2.154, 95% confidence interval (CI) 0.932-3.688; p = 0.002] and skewness (β = 0.779, 95% CI 0.255-1.382; p = 0.006) were associated with positive PNI. The model combining skewness and MRI T stage had an area under the ROC curve of 0.811 (95% CI 0.724-0.899) for predicting PNI status.

CONCLUSION

Histogram parameters in zoomed EPI DWI can help predict the PNI status in RC.

Pathologic Implications of Radial Resection Margin and Perineural Invasion to Adjuvant Chemotherapy after Preoperative Chemoradiotherapy and Surgery for Rectal Cancer: A Multi-Institutional and Case-Matched Control Study

We assessed the exact role of adjuvant chemotherapy after neoadjuvant chemoradiotherapy (CRT) and surgery in rectal cancer patients with positive surgical margin or perineural invasion (PNI). This multi-institutional study included 1799 patients with rectal cancer at cT3-4N0-2M0 stages. Patients were divided into two groups. The high-risk group had a positive margin and/or perineural invasion. The low-risk group showed no positive margin or PNI. Propensity-score matching analysis was performed, and a total of 928 patients, with 464 in each arm, were evaluated. The high-risk group showed significant differences in overall survival (OS, 73.4% vs. 53.9%, p < 0.01) and recurrence-free survival (RFS, 52.7% vs. 40.9%, p = 0.01) at five years between the adjuvant chemotherapy arm and observation arm. The low-risk group showed no significant differences in 5-year OS (p = 0.61) and RFS (p = 0.75) between the two arms. Multivariate analyses showed that age, pathologic N stage, and adjuvant chemotherapy were significantly correlated with OS and RFS in the high-risk group (all p < 0.05). Adjuvant chemotherapy improved OS and RFS more significantly in rectal cancer patients with positive surgical margin or PNI than in those with negative surgical margin and PNI.

The value of 18F-FDG PET/CT-based radiomics in predicting perineural invasion and outcome in non-metastatic colorectal cancer

PURPOSE

Perineural invasion (PNI) has been recognized as an important prognosis factor in patients with colorectal cancer (CRC). The purpose of this retrospective study was to investigate the value of ¹⁸F-FDG PET/CT-based radiomics integrating clinical information, PET/CT features, and metabolic parameters for preoperatively predicting PNI and outcome in non-metastatic CRC and establish an easy-to-use nomogram.

METHODS

A total of 131 patients with non-metastatic CRC who undergo PET/CT scan were retrospectively enrolled. Univariate analysis was used to compare the differences between PNI-present and PNI-absent groups. Multivariate logistic regression was performed to select the independent predictors for PNI status. Akaike information criterion (AIC) was used to select the best prediction models for PNI status. CT radiomics signatures (RSs) and PET-RSs were selected by maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator algorithm (LASSO) regression and radiomics scores (Rad-scores) were calculated for each patient. The prediction models with or without Rad-score were established. According to the nomogram, nomogram scores (Nomo-scores) were calculated for each patient. The performance of different models was assessed with the area under the curve (AUC), specificity, and sensitivity. The clinical usefulness was assessed by decision curve (DCA). Multivariate Cox regression was used to selected independent predictors of progression-free survival (PFS).

RESULTS

Among all the clinical information, PET/CT features, and metabolic parameters, CEA, lymph node metastatic on PET/CT (N stage), and total lesion glycolysis (TLG) were independent predictors for PNI (p < 0.05). Six CT-RSs and 12 PET-RSs were selected as the most valuable factors to predict PNI. The Rad-score calculated with these RSs was significantly different between PNI-present and PNI-absent groups (p < 0.001). The AUC of the constructed model was 0.90 (95%CI: 0.83-0.97) in the training cohort and 0.80 (95%CI: 0.65-0.95) in the test cohort. The nomogram's predicting sensitivity was 0.84 and the specificity was 0.83 in the training cohort. The clinical model's predicting sensitivity and specificity were 0.66 and 0.85 in the training cohort, respectively. Besides, DCA showed that patients with non-metastatic CRC could get more benefit with our model. The results also indicated that N stage, PNI status, and the Nomo-score were independent predictors of PFS in patients with non-metastatic CRC.

CONCLUSION

The nomogram, integrating clinical data, PET/CT features, metabolic parameters, and radiomics, performs well in predicting PNI status and is associated with the outcome in patients with non-metastatic CRC.

The Role of Transanal Endoscopic Surgery for Early Rectal Cancer

Transanal endoscopic surgery (TES), which is performed through a variety of transanal endoluminal multitasking surgical platforms, was developed to facilitate endoscopic en bloc excision of rectal lesions as a minimally invasive alternative to radical proctectomy. Although the oncologic safety of TES in the treatment of malignant rectal tumors has been an area of vigorous controversy over the past two decades, TES is currently accepted as an oncologically safe approach for the treatment of carefully selected early and superficial rectal cancers. TES can also serve as both a diagnostic and potentially curative treatment of partially resected unsuspected malignant polyps. In this article, indications and contraindications for transanal endoscopic excision of early rectal cancer lesions are reviewed, as well as selection criteria for the most appropriate transanal excisional approach. Preoperative preparation and surgical technique for complications of TES will be reviewed, as well as recommended surveillance and management of upstaged tumors.