A predictive nomogram improved diagnostic accuracy and interobserver agreement of perirectal lymph nodes metastases in rectal cancer

Analysis of Calculated Liver Scores for Long-Term Outcome in 423 Cutaneous Melanoma Patients

Background: Neoadjuvant and adjuvant therapies are currently getting increasingly important in cutaneous melanoma (CM) management. However, there is still a lack of prognostic tools to identify which patients have a poor prognosis. There is increasing evidence that the liver score may be a potential prognostic parameter in different tumour types. The aim was to investigate whether established liver scores can establish the prognosis of CM. Methods: According to established methods, the APRI, the MELD score, the MELD-Na score and the De Ritis ratio were calculated from the laboratory values at the time of the initial diagnosis. Survival was compared with the Kaplan-Meier curve and tested with log-rank tests. Risk factors associated with cutaneous melanoma-specific survival (CMSS) and progression-free survival (PFS) were assessed by using the Cox proportional hazards regression model. To determine the diagnostic accuracy, we performed a time-dependent ROC analysis. Results: A total of 423 patients were included, including 141 patients in AJCC stage (2017) I (33.3%), 82 in stage II (19.4%), 128 in stage III (30.3%) and 72 in stage IV (17%). Median time until melanoma-specific death was 99 months (IQR: 37-126). In addition, 37.6% of patients relapsed with a median time to relapse of 88 months (IQR: 17.5-126). In all stages, tumour thickness and ulceration were independent markers for predicting CMSS and PFS (p < 0.05). The multivariable analysis with all stages showed no significant association with CM outcome for liver scores (p > 0.05). The subgroup analysis revealed that the APRI (≥0.2241) was associated with CMSS and PFS in melanoma stages I and II, independently of tumour thickness, age and ulceration (HR 2.57, 95% CI 1.14-5.75; HR 2.94, 95% CI 1.42-6.09, respectively). Conclusions: The 20-year prognosis of AJCC stage I and II CM was dependent on tumour thickness and the APRI. High tumour thickness and an APRI ≥ 0.2241 at the initial diagnosis were associated with a worse prognosis. Future studies should investigate the independent prognostic value of the APRI in low-stage CM. Furthermore, the APRI score could be a potential biomarker for nomograms.

A radiomics model based on T2WI and clinical indexes for prediction of lateral lymph node metastasis in rectal cancer

OBJECTIVE

The aim of this study was to explore the clinical value of a radiomics prediction model based on T2-weighted imaging (T2WI) and clinical indexes in predicting lateral lymph node (LLN) metastasis in rectal cancer patients.

METHODS

This was a retrospective analysis of 106 rectal cancer patients who had undergone LLN dissection. The clinical risk factors for LLN metastasis were selected by multivariable logistic regression analysis of the clinical indicators of the patients. The LLN radiomics features were extracted from the pelvic T2WI of the patients. The least absolute shrinkage and selection operator algorithm and backward stepwise regression method were adopted for feature selection. Three LLN metastasis prediction models were established through logistic regression analysis based on the clinical risk factors and radiomics features. Model performance was assessed in terms of discriminability and decision curve analysis in the training, verification and test sets.

RESULTS

The model based on the combined T2WI radiomics features and clinical risk factors demonstrated the highest accuracy, surpassing the models based solely on either T2WI radiomics features or clinical risk factors. Specifically, the model achieved an AUC value of 0.836 in the test set. Decision curve analysis revealed that this model had the greatest clinical utility for the vast majority of the threshold probability range from 0.4 to 1.0.

CONCLUSION

Combining T2WI radiomics features with clinical risk factors holds promise for the noninvasive assessment of the biological characteristics of the LLNs in rectal cancer, potentially aiding in therapeutic decision-making and optimizing patient outcomes.

Diagnostic value of a radiomics model based on CT and MRI for prediction of lateral lymph node metastasis of rectal cancer

This study aimed to develop a radiomics model for predicting lateral lymph node (LLN) metastasis in rectal cancer patients using MR-T2WI and CT images, and assess its clinical value. This prospective study included rectal cancer patients with complete MR-T2WI and portal enhanced CT images who underwent LLN dissection at Tianjin Union Medical Center between June 2017 and November 2022. Primary lesions and LLN were segmented using 3D slicer. Radiomics features were extracted from the region of interest using pyradiomics in Python. Least absolute shrinkage and selection operator algorithm and backward stepwise regression were employed for feature selection. Three LLN metastasis radiomics prediction models were established via multivariable logistic regression analysis. The performance of the model was evaluated using receiver operating characteristic curve analysis, and the area under the curve (AUC), sensitivity, specificity were calculated for the training, validation, and test sets. A nomogram was constructed for visualization, and decision curve analysis (DCA) was performed to evaluate clinical value. We included 94 eligible patients in the analysis. For each patient, we extracted a total of 1344 radiomics features. The CT combined with MR-T2WI model had the highest AUC for all sets compared to CT and MR-T2WI models. AUC values for the CT combined with MR-T2WI model in the training, validation, and test sets were 0.957, 0.901, and 0.936, respectively. DCA revealed high prediction value for the combined MR-T2WI and CT model. A radiomics model based on CT and MR-T2WI data effectively predicted LLN metastasis in rectal cancer patients preoperatively.

Intra- and interobserver agreement of rectal cancer staging with MRI

Background

Reliable preoperative staging of rectal cancers is crucial for treatment decision making.

Purpose

To assess the intra- and inter-observer agreement of rectal cancer staging, including the sub-categories, with magnetic resonance imaging (MRI).

Material and Methods

The study includes 85 patients (35.3% women; mean age = 62.2 ± 11.2 years) who underwent MRI for rectal cancer staging between August 2020 and April 2021. All the stored images were evaluated independently by two radiologists with 10–15 years of experience. For intra-observer agreement, the evaluations were done two months apart. Analyses were made using kappa, prevalence and bias-adjusted kappa (PABAK), and intraclass correlation coefficient (ICC), where appropriate.

Results

There was a substantial inter-observer agreement for tumor localization (kappa = 0.665, PABAK = 0.682), mesorectal fascia invasion (kappa = 0.663, PABAK = 0.822), internal and external sphincter involvement (kappa 0.804 and 0.751, PABAK 0.859 and 0.929, respectively), and moderate to substantial agreement for M-staging (kappa = 0.451, PABAK = 0.742) and extramural vascular invasion (kappa = 0.569, PABAK = 0.741). There was also a good inter-observer agreement for T staging and N staging (ICC = 0.862, 95% confidence interval [CI] = 0.788–0.911; and ICC = 0.841, 95% CI = 0.595–0.922, respectively). As expected, intra-observer agreement was better than inter-observer agreement.

Conclusion

Intra- and inter-observer agreement for MRI staging of rectal cancers using the structured reporting template is good.

Magnetic resonance imaging (MRI) radiomics of papillary thyroid cancer (PTC): a comparison of predictive performance of multiple classifiers modeling to identify cervical lymph node metastases before surgery

PURPOSE

To compare predictive efficiency of multiple classifiers modeling and establish a combined magnetic resonance imaging (MRI) radiomics model for identifying lymph node (LN) metastases of papillary thyroid cancer (PTC) preoperatively.

MATERIALS AND METHODS

A retrospective analysis based on the preoperative MRI scans of 109 PTC patients including 77 patients with LN metastases and 32 patients without metastases was conducted, and we divided enroll cases into trained group and validation group. Radiomics signatures were selected from fat-suppressed T2-weighted MRI images, and the optimal characteristics were confirmed by spearman correlation test, hypothesis testing and random forest methods, and then, eight predictive models were constructed by eight classifiers. The receiver operating characteristic (ROC) curves analysis were performed to demonstrate the effectiveness of the models.

RESULTS

The area under the curve (AUC) of ROC based on MRI texture diagnosed LN status by naked eye was 0.739 (sensitivity = 0.571, specificity = 0.906). Based on the 5 optimal signatures, the best AUC of MRI radiomics model by logistics regression classifier had a considerable prediction performance with AUCs 0.805 in trained group and 0.760 in validation group, respectively, and a combination of best radiomics model with visual diagnosis of MRI texture had a high AUC as 0.969 (sensitivity = 0.938, specificity = 1.000), suggesting combined model had a preferable diagnostic efficiency in evaluating LN metastases of PTC.

CONCLUSION

Our combined radiomics model with visual diagnosis could be a potentially effective strategy to preoperatively predict LN metastases in PTC patients before clinical intervention.

Prediction of lymph node metastasis in rectal cancer: comparison between shear-wave elastography based ultrasomics and MRI

PURPOSE

We aimed to explore the diagnostic efficiency of shear-wave elastography (SWE) ultrasomics in the preoperative prediction of lymph node (LN) metastasis in rectal cancer.

METHODS

This study included 87 patients with pathologically confirmed rectal cancer, with data gathered from August 2017 to August 2018. A total of 1044 ultrasomics features of rectal tumor were collected with AK software from the SWE examinations. The least absolute shrinkage and selection operator (LASSO) regression model was used for feature selection and building a SWE ultrasomics signature. The diagnostic performance was evaluated with an area under the receiver operating characteristic curve (AUC) analysis. Then, the diagnostic performance of the SWE ultrasomics signature was compared with magnetic resonance imaging (MRI).

RESULTS

Of the 87 patients, 40 (46.0%) had LN metastasis. Thirteen ultrasomics features of rectal tumor were selected as the most significant features. The SWE ultrasomics signature correlated with LN metastasis (p < 0.001). Patients with LN metastasis had higher signature than patients without LN metastasis. In terms of diagnostic performance, SWE ultrasomics signature was significantly superior to MRI (AUC, 0.883 vs. 0.760, p = 0.034). The diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of SWE ultrasomics signature were 82.8%, 87.5%, 78.8%, 77.8%, and 88.1%, respectively, while those of MRI were 75.9%, 77.5%, 74.5%, 72.1%, and 79.6%, respectively.

CONCLUSION

SWE ultrasomics is a more accurate predictive method for identifying LN metastasis preoperatively than MRI. Thus, SWE ultrasomics might be used to better guide preoperative individual therapies for patients with rectal cancer.

MRI-detected extramural vascular invasion potentiates the risk for pathological metastasis to the lateral lymph nodes in rectal cancer

PURPOSE

Multidisciplinary treatment for locally advanced rectal cancer requires an accurate assessment of the risk of metastasis to the lateral lymph nodes (LNs). We herein aimed to stratify the risk of pathological metastasis to lateral LNs based on the preoperatively detected malignant features.

METHODS

All patients with rectal cancer who underwent surgery from January 2016 to July 2020 were identified. We recorded the TNM factors; perirectal and lateral LN sizes; and MRI findings, including mesorectal fascia involvement, extramural vascular invasion (EMVI), tumor site, and tumor distance from the anal verge.

RESULTS

101 patients underwent rectal resection with lateral lymph node dissection, of whom 16 (15.8%) exhibited pathological metastases to the lateral LNs. Univariate analyses demonstrated that lateral LN metastasis was significantly correlated with mrEMVI positivity (p = 0.0023) and a baseline lateral LN short-axis length of ≥ 5 mm (p < 0.0001). These significant associations were confirmed by a multivariate analysis (p = 0.0254 and 0.0027, respectively). The lateral LN metastasis rate was as high as 44% in cases bearing both risk factors, compared to 0% in cases lacking both risk factors.

CONCLUSION

The results elucidated in this study may contribute to risk stratification, which can be used when determining the indications for lateral lymph node dissection.

Nodal drainage pathways in primary rectal cancer: anatomy of regional and distant nodal spread

Nodal involvement is a significant prognostic factor in rectal cancer and difficult to assess preoperatively. An understanding of the patterns of nodal spread from different regions of the rectum can assist in this process and is essential for the purposes of surgical planning. In this article we define patterns of spread to mesenteric and pelvic sidewall nodal subgroups and discuss the importance of accurate anatomic localization of nodes for the purposes of staging and surgical planning.

Predictive factors of pathological lateral pelvic lymph node metastasis in patients without clinical lateral pelvic lymph node metastasis (clinical stage II/III): The analysis of data from the clinical trial (JCOG0212)

BACKGROUND

Mesorectal excision (ME) is the standard surgical procedure for lower rectal cancer. However, in Japan, total or tumor-specific ME with lateral pelvic lymph node dissection (LLND) is the standard surgical procedure for patients with clinical stages II or III lower rectal cancer, because lateral pelvic lymph node metastasis occasionally occurs in these patients. The aim of study was to elucidate the predictive factors of pathological lateral pelvic lymph node metastasis in patients without clinical lateral pelvic lymph node metastasis.

METHODS

Data form the clinical trial (JCOG0212) was analyzed. The JCOG0212 was a randomized controlled trial to confirm the non-inferiority of mesorectal excision alone to mesorectal excision with lateral lymph node dissection for clinical stage II/III patients who don't have clinical lateral pelvic lymph node metastasis in terms of relapse free survival. This study was conducted at a multitude of institution33 major hospitals in Japan. Among the 351 patients who underwent lateral lymph node dissection in the JCOG0212 study, 328 patients were included in this study. Associations between pathological lateral pelvic lymph node metastasis and preoperative and postoperative factors were investigated. The preoperative factors were age, sex, clinical stage, tumor location, distance from anal verge, tumor size, and short-axis diameter of lateral pelvic lymph node on computed tomography and the postoperative factors were pathological T, pathological N, and histological grade.

RESULTS

Among the 328 patients, 24 (7.3%) had pathological lateral pelvic lymph node metastasis. In multivariable analysis of the preoperative factors, patient age (p = 0.067), tumor location (p = 0.025), and short-axis diameter of lateral pelvic lymph node (p = 0.002) were significantly associated with pathological lateral pelvic lymph node metastasis.

CONCLUSIONS

Patient age, tumor location, and short-axis diameter of lateral pelvic lymph node were predictive factors of pathological lateral pelvic lymph node metastasis.

Nomograms for predicting long-term overall survival and cancer-specific survival in patients with major salivary gland cancer: a population-based study

In this study, we aimed to develop and validate nomograms for predicting long-term overall survival (OS) and cancer-specific survival (CSS) in major salivary gland cancer (MSGC) patients. These nomograms were developed using a retrospective cohort (N=4218) from the Surveillance, Epidemiology, and End Results (SEER) database, and externally validated using an independent data cohort (N=244). We used univariate, and multivariate analyses, and cumulative incidence function to select the independent prognostic factors of OS and CSS. Index of concordance (c-index) and calibration plots were used to estimate the nomograms’ predictive accuracy. The median follow-up period was 34 months (1–119 months). Of 4218 MSGC patients, 1320 (31.3%) died by the end of the follow-up; of these 1320 patients, 883 (20.9%) died of MSGC. The OS nomogram, which had a c-index of 0.817, was based on nine variables: age, sex, tumor site, tumor grade, surgery performed, radiation therapy and TNM classifications. The CSS nomogram, which had a c-index of 0.829, was based on the same nine variables plus race. External validation c-indexes were 0.829 and 0.807 for OS and CSS, respectively. Based on SEER database, we have developed nomograms predicting five- and eight-years OS and CSS for MSGC patients with perfect accuracy. These nomograms will help clinicians customize treatment and monitoring strategies in MSGC patients.