Noninvasive prediction of perineural invasion in intrahepatic cholangiocarcinoma by clinicoradiological features and computed tomography radiomics based on interpretable machine learning: a multicenter cohort study.

BACKGROUND: Perineural invasion (PNI) of intrahepatic cholangiocarcinoma (ICC) is a strong independent risk factor for tumour recurrence and long-term patient survival. However, there is a lack of noninvasive tools for accurately predicting the PNI status. The authors develop and validate a combined model incorporating radiomics signature and clinicoradiological features based on machine learning for predicting PNI in ICC, and used the Shapley Additive explanation (SHAP) to visualize the prediction process for clinical application. METHODS: This retrospective and prospective study included 243 patients with pathologically diagnosed ICC (training, n =136; external validation, n =81; prospective, n =26, respectively) who underwent preoperative contrast-enhanced computed tomography between January 2012 and May 2023 at three institutions (three tertiary referral centres in Guangdong Province, China). The ElasticNet was applied to select radiomics features and construct signature derived from computed tomography images, and univariate and multivariate analyses by logistic regression were used to identify the significant clinical and radiological variables with PNI. A robust combined model incorporating radiomics signature and clinicoradiological features based on machine learning was developed and the SHAP was used to visualize the prediction process. A Kaplan-Meier survival analysis was performed to compare prognostic differences between PNI-positive and PNI-negative groups and was conducted to explore the prognostic information of the combined model. RESULTS: Among 243 patients (mean age, 61.2 years ± 11.0 (SD); 152 men and 91 women), 108 (44.4%) were diagnosed as PNI-positive. The radiomics signature was constructed by seven radiomics features, with areas under the curves of 0.792, 0.748, and 0.729 in the training, external validation, and prospective cohorts, respectively. Three significant clinicoradiological features were selected and combined with radiomics signature to construct a combined model using machine learning. The eXtreme Gradient Boosting exhibited improved accuracy and robustness (areas under the curves of 0.884, 0.831, and 0.831, respectively). Survival analysis showed the construction combined model could be used to stratify relapse-free survival (hazard ratio, 1.933; 95% CI: 1.093-3.418; P =0.021). CONCLUSIONS: We developed and validated a robust combined model incorporating radiomics signature and clinicoradiological features based on machine learning to accurately identify the PNI statuses of ICC, and visualize the prediction process through SHAP for clinical application.

Nomogram development and validation to predict Ki-67 expression of hepatocellular carcinoma derived from Gd-EOB-DTPA-enhanced MRI combined with T1 mapping.

Objective: As an important biomarker to reflect tumor cell proliferation and tumor aggressiveness, Ki-67 is closely related to the high early recurrence rate and poor prognosis, and pretreatment evaluation of Ki-67 expression possibly provides a more accurate prognosis assessment and more better treatment plan. We aimed to develop a nomogram based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) combined with T1 mapping to predict Ki-67 expression in hepatocellular carcinoma (HCC). Methods: This two-center study retrospectively enrolled 148 consecutive patients who underwent preoperative Gd-EOB-DTPA-enhanced MRI T1 mapping and surgically confirmed HCC from July 2019 to December 2020. The correlation between quantitative parameters from T1 mapping, ADC, and Ki-67 was explored. Three cohorts were constructed: a training cohort (n = 73) and an internal validation cohort (n = 31) from Shunde Hospital of Southern Medical University, and an external validation cohort (n = 44) from the Sixth Affiliated Hospital, South China University of Technology. The clinical variables and MRI qualitative and quantitative parameters associational with Ki-67 expression were analyzed by univariate and multivariate logistic regression analyses. A nomogram was developed based on these associated with Ki-67 expression in the training cohort and validated in the internal and external validation cohorts. Results: T1rt-Pre and T1rt-20min were strongly positively correlated with Ki-67 (r = 0.627, r = 0.607, P < 0.001); the apparent diffusion coefficient value was moderately negatively correlated with Ki-67 (r = -0.401, P < 0.001). Predictors of Ki-67 expression included in the nomogram were peritumoral enhancement, peritumoral hypointensity, T1rt-20min, and tumor margin, while arterial phase hyperenhancement (APHE) was not a significant predictor even included in the regression model. The nomograms achieved good concordance indices in predicting Ki-67 expression in the training and two validation cohorts (0.919, 0.925, 0.850), respectively. Conclusions: T1rt-Pre and T1rt-20min had a strong positive correlation with the Ki-67 expression in HCC, and Gd-EOB-DTPA enhanced MRI combined with T1 mapping-based nomogram effectively predicts high Ki-67 expression in HCC.

Analysis of petrous apex meningocele associated with meningioma: is there any relation with chronic intracranial hypertension?

PURPOSE: Petrous apex meningocele (PAM) is an uncommon cystic lesion involving the petrous apex. The underlying cause of PAM may be related to chronic elevated intracranial pressure. The aim of the study was to explore the relationship between PAM and meningioma and between PAM and other intracranial hypertension findings. METHODS: Two hundred seventy-eight consecutive patients with meningiomas were retrospectively studied. Fifty age- and gender-matched controls were also enrolled in this study. The incidence of PAM, empty sella, tortuosity of the optic nerve, and hydrops of optic nerve sheath was evaluated. The maximum width, area, volume of each PAM, or Meckel's cave and volume of meningioma were measured in controls and patients, separately. RESULTS: One hundred fifty-nine (57.19%) patients were detected with coexistent PAMs. One hundred twenty-five patients had bilateral PAMs, 34 had unilateral lesions, and the remaining 119 did not have PAM. Two subjects (4/50) had unilateral PAMs in normal controls. The maximum width, area, volume of PAM, or Meckel's cave were significantly larger in the patients with bilateral PAM group than those in the unilateral PAM group, in the group without PAM, and those in control group (p = 0.000). The volume of meningioma was positively correlated with the PAM volume (r = 0.48). There was a positive correlation for the incidence between PAM and (1) empty sella (r = 0.901) and (2) tortuosity of the optic nerves and hydrops of the optic sheath (r = 0.825). CONCLUSION: Coexistence of PAMs with meningiomas is not rare in incidence, and it suggests a potential role for chronically elevated intracranial pressure and disturbance of CSF circulation in their pathophysiology.

Delayed leukoencephalopathy of non-small cell lung cancer patients with brain metastases underwent whole brain radiation therapy.

To explore the incidence, MR imaging findings, dynamic developing process of delayed leukoencephalopathy (DLE) in non-small cell lung cancer (NSCLC) patients with brain metastases patients who undergone whole brain radiation (WBRT) therapy, we retrospectively reviewed 48 NSCLC patients who underwent WBRT for brain metastases from January 2010 through June 2015 and had evaluable magnetic resonance imaging after treatment. The DLE were graded using a scale to evaluate T2-FLAIR (fluid attenuated image recovery) images: grade 1 = little or no white matter hyperintensity, grade 2 = limited periventricular hyperintensity and grade 3 = diffuse white matter hyperintensity. 48 NSCLC patients with brain metastases were enrolled. The median age of these patients was 55.7 years (range 33-75 years). The median follow-up was 12 months. The characteristic MR imaging of DLE in those patients was bilaterally diffuse white matter T2 hyperintensity around the periventricular areas without enhancement, sparing from U-fiber, callosum and gray matter structure. The incidence of DLE developed 6.25% (3/48), 30.00% (12/40), 48.39% (15/31), 61.90% (13/21), 85.71% (6/7), 100% (3/3) in those patients who were followed up for 3, 6, 9, 12, 24, 36 months, respectively. Through increased understanding of it, it may be possible to help clinicians develop further therapeutic strategies to maximize benefit while limiting potential long term toxicities. These data supplement existing reports regarding the late effects of WBRT in NSCLC patients with brain metastasis.