Search

Chemotherapy alters the prognostic biomarker histopathological growth pattern (HGP) phenotype in colorectal liver metastases (CRLMs) patients. We aimed to develop a CT-based radiomics model to predict the transformation of the HGP phenotype after chemotherapy. This study included 181 patients with 298 CRLMs who underwent preoperative contrast-enhanced CT followed by partial hepatectomy between January 2007 and July 2022 at two institutions. HGPs were categorized as pure desmoplastic HGP (pdHGP) or non-pdHGP. The samples were allocated to training, internal validation, and external validation cohorts comprising 153, 65, and 29 CRLMs, respectively. Radiomics analysis was performed on pre-enhanced, arterial phase, portal venous phase (PVP), and fused images. The model was used to predict prechemotherapy HGPs in 112 CRLMs, and HGP transformation was analysed by comparing these findings with postchemotherapy HGPs determined pathologically. The prevalence of pdHGP was 19.8% (23/116) and 45.8% (70/153) in chemonaïve and postchemotherapy patients, respectively (P < 0.001). The PVP radiomics signature showed good performance in distinguishing pdHGP from non-pdHGPs (AUCs of 0.906, 0.877, and 0.805 in the training, internal validation, and external validation cohorts, respectively). The prevalence of prechemotherapy pdHGP predicted by the radiomics model was 33.0% (37/112), and the prevalence of postchemotherapy pdHGP according to the pathological analysis was 47.3% (53/112; P = 0.029). The transformation of HGP was bidirectional, with 15.2% (17/112) of CRLMs transforming from prechemotherapy pdHGP to postchemotherapy non-pdHGP and 30.4% (34/112) transforming from prechemotherapy non-pdHGP to postchemotherapy pdHGP (P = 0.005). CT-based radiomics method can be used to effectively predict the HGP transformation in chemotherapy-treated CRLM patients, thereby providing a basis for treatment decisions. [ABSTRACT FROM AUTHOR]

The ability to noninvasively detect and monitor the growth of orthotopic liver transplantation tumors is critical for replicating advanced colorectal cancer liver metastases (CRLMs) in animal models. We assessed the use of high-resolution ultrasound (HRU) to monitor CRLMs transplanted using various cell concentrations. Sixty BALB/c female mice were randomly divided into 3 groups, and murine colonic CT26 cells were injected into the left liver lobe at concentrations of 1 × 102 (group 1), 1 × 103 (group 2), or 1 × 104 (group 3). Tumor presentation, location, number, size, shape, and echogenicity were assessed daily with 24-MHz center frequency HRU starting 6 days after injection. Animals were sacrificed when the largest tumor was ≥ 1 cm in diameter. Sensitivity, specificity, and area under curve (AUC) of CRLMs diagnosed with HRU were calculated using receiver operating characteristic curve analysis. In group 1, 94% of mice formed < 5 tumors, and 41% formed a single tumor. Tumors were first detected with HRU on day 12 in group 1, day 10 in group 2, and day 7 in group 3; tumor volume doubling times were 14–15 days, 11–12 days, and 7–8 days, respectively. With a long diameter threshold of 2.4 mm, diagnostic sensitivity and specificity of HRU were 94.1% and 88.7%, respectively, and the AUC was 0.962. These findings suggest that HRU can be used to accurately detect and monitor the growth of CRLMs in an orthotopic transplantation mouse model, especially when a lower concentration of cells is used. [ABSTRACT FROM AUTHOR]

Purpose: To develop and evaluate a preoperative risk stratification model for predicting disease-free survival (DFS) based on contrast-enhanced multidetector computed tomography (ceMDCT) images in patients with gastric cancer (GC) undergoing radical surgery. Methods: We retrospectively enrolled patients with GC who underwent ceMDCT followed by radical surgery. A preoperative risk stratification model was constructed (including risk factor selection, risk status scoring, and risk level assignment) using Cox proportional hazard regression and log-rank analyses in the training cohort; the model was tested in the validation cohort. A nomogram was used to compare the preoperative risk stratification model with a postoperative DFS prediction model. Results: A total of 462 patients (training/validation: 271/191) were included. The ceMDCT features of T category (score of 0 or 2), N category (0, 1, 2, or 3), extramural vessel invasion (0 or 2), and tumor location (0 or 1) were selected to construct the preoperative risk stratification model, with 4 risk levels defined based on risk score. There were significant differences in DFS among the risk levels in both cohorts (p < 0.001). The predictive value of the preoperative model was similar to that of the postoperative model, with concordance indices of 0.791 (95% CI, 0.743–0.837) and 0.739 (95% CI, 0.666–0.812), respectively, in the training cohort and 0.762 (95% CI, 0.696–0.828) and 0.738 (95% CI, 0.684–0.792), respectively, in the validation cohort. Conclusion: A preoperative risk stratification model based on ceMDCT images could be used to predict DFS and thus classify GC cases into various risk levels. [ABSTRACT FROM AUTHOR]

Objective: To analyze the clinical features and outcomes of the patients with anti-glycyl tRNA synthetase (anti-EJ) syndrome in a large Chinese cohort. Methods: The medical records, imaging, and serologic data of patients with anti-EJ antibodies from the China-Japan Friendship Hospital database were retrospectively investigated. Anti-EJ antibodies were identified using immunoblot assay. Long-term follow-up was conducted. Results: Anti-EJ antibodies were present in 46 (19.7%) of the 234 patients with antisynthetase syndrome (ASS), preceded by anti-Jo-1 and anti-PL-7 antibodies. The mean age of disease onset was 51.2 ± 15.9 years, and 69.6% of these patients were female. The most prevalent clinical feature was interstitial lung disease (ILD) (96.7%), which was also the most common initial manifestation, followed by fever (60.9%), mechanic's hands (56.5%), muscle involvement (50%), and Raynaud phenomenon (8.7%). Ten (21.7%) patients developed rapidly progressive ILD (RP-ILD). Organizing pneumonia (OP) on high-resolution computed tomography (HRCT) scans (OR = 37.5, p = 0.006) and a higher C-reactive protein-to-albumin ratio (CAR) (OR = 28.3, p = 0.01) were independent risk factors for RP-ILD. Muscular pathological features were heterogeneous. Concomitant infection was noted in 63.0% of the patients during the disease course. Hypoalbuminemia (OR = 0.759, p = 0.002) was an independent risk factor for concomitant infection. Patients responded well to glucocorticoid therapy. The 5- and 10-year survival rates of the patients with anti-EJ were 97.8% and 88%, respectively. Conclusion: Anti-EJ syndrome was found to be a relatively common ASS subtype, with a favorable outcome. A notable proportion of the patients experienced RP-ILD, which was prone to OP on HRCT and a higher CAR, and needed aggressive management. Key Points • ILD was the most common initial manifestation of anti-glycyl tRNA synthetase syndrome. • RP-ILD was notable in anti-EJ positive patients. • Anti-EJ positive patients possessed a favorable long-term prognosis, but easily relapsed. [ABSTRACT FROM AUTHOR]

Purpose: The study investigated potential correlations between the expression levels of ADAMTS1 and HSPG2 in cumulus cells (CCs) and controlled ovarian hyperstimulation (COH) outcomes. Methods: RT-PCR was used to determine ADAMTS1 and HSPG2 mRNA levels in mice CCs at different timepoints (0, 4, 8, 12, and 16 h) after human chorionic gonadotropin (hCG) injection, and in CCs after RNAi treatment. Women with polycystic ovary syndrome (PCOS) (n = 45) and normal ovulatory controls (n = 103) undergoing IVF/ICSI were recruited. Relative ADAMTS1 and HSPG2 mRNA levels were measured by RT-PCR. Moreover, correlations of ADAMTS1 and HSPG2 levels with COH outcomes were analyzed. Results: At different timepoints after hCG treatment, ADAMTS1 mRNA had the highest level at 12 h, whereas HSPG2 showed opposite profiles to ADAMTS1 with the lowest level at 12 h. HSPG2 expression was upregulated after ADAMTS1 RNAi treatment The PCOS group had higher HSPG2 and lower ADAMTS1 expression levels than controls. In normal ovulatory women (control group), a higher expression of ADAMTS1 and lower expression of HSPG2 were associated with more mature oocytes, transplantable embryos, and good quality embryos, whereas higher transplantable embryo rates and good quality embryo rates were obtained only with lower HSPG2 expression. ROC curves showed the co-measurement of ADAMTS1 and HSPG2 had a better predictive power than separate analyses. Conclusion: The dynamic profiles of ADAMTS1 and HSPG2 were inversely correlated in CCs. In PCOS and normal ovulatory patients, higher ADAMTS1 and lower HSPG2 expression levels in CCs were related to better COH outcomes. [ABSTRACT FROM AUTHOR]

Objectives: To predict histopathologic growth patterns (HGPs) in colorectal liver metastases (CRLMs) with a noninvasive radiomics model. Methods: Patients with chemotherapy-naive CRLMs who underwent abdominal contrast-enhanced multidetector CT (MDCT) followed by partial hepatectomy between January 2007 and January 2019 from two institutions were included in this retrospective study. Hematoxylin- and eosin-stained histopathologic sections of CRLMs were reviewed, with HGPs defined according to international consensus. Lesions were divided into training and validation datasets based on patients' sources. Radiomic features were extracted from pre- and post-contrast (arterial and portal venous) phase MDCT images, with review focusing on the segmented tumor–liver interface zones of CRLMs. Minimum redundancy maximum relevance and decision tree methods were used for radiomics modeling. Multivariable logistic regression analyses and ROC curves were used to assess the predictive performance of these models in predicting HGP types. Results: A total of 126 CRLMs with histopathologic-demonstrated desmoplastic (n = 68) or replacement (n = 58) HGPs were assessed. The radiomics signature consisted of 20 features of each phase selected. The 3 phases fused radiomics signature demonstrated the best predictive performance in distinguishing between replacement and desmoplastic HGPs (AUCs of 0.926 and 0.939 in the training and external validation cohorts, respectively). The clinical-radiomics combined model showed good discrimination (C-indices of 0.941 and 0.833 in the training and external validation cohorts, respectively). Conclusions: A radiomics model derived from MDCT images may effectively predict the HGP of CRLMs, thus providing a basis for prognostic stratification and therapeutic decision-making. [ABSTRACT FROM AUTHOR]

Purpose: To determine the 1-year progression-free survival (PFS) of extramural venous invasion (EMVI), detected with contrast-enhanced multiple-row detector computed tomography (ceMDCT), in patients with stage III gastric cancer. Methods: Between January 2009 and December 2013, 117 patients with pathological-proved stage III gastric cancer based on the criteria of the AJCC 7th were included in this retrospective study. All patients underwent adjuvant chemotherapy postoperatively and had been monitored with the follow-up chest/abdomen/pelvis ceMDCT on 3, 6, and 12 months post-operation. Two radiologists reviewed preoperative images regarding the presence of EMVI, categories of tumor and categories of lymph node. Conventional prognostic histological factors including pathological T/N status, tumor location/growth pattern, histological type/tumor differentiation, and tumor size were also recorded. Disease progression was defined as the presence of radiological or/and pathology-confirmed metachronous metastases, local recurrence, or gastric cancer-related death. The 1-year PFS for both EMVI-positive and EMVI-negative was calculated using the Kaplan-Meier product limit. Hazard ratios for 1-year PFS were generated using a Cox proportional hazard regression on ceMDCT tumor characteristics. Results: The prevalence of EMVI detected with ceMDCT was 43.6% (51/117) in patients with stage III gastric cancer. The EMVI-positive patients had significantly lower 1-year PFS rates (45.1%), than the EMVI-negative patients (75.8%), (Log-rank test, P = 0.0008). In a Cox proportional hazards regression analysis, EMVI and tumor location/growth pattern were identified as independent prognostic factors of 1-year PFS with hazard ratio of 2.272 (95% CI 1.133-4.556, P = 0.021) and 1.982 (95% CI 1.040-3.780, P = 0.039), respectively. Conclusion: EMVI status, detected with ceMDCT, could be used to counsel patients regarding ongoing risks of metastatic disease, implications for surveillance, and systemic chemotherapy. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the correlation of the mitotic index (MI) of 1–5 cm gastric gastrointestinal stromal tumors (gGISTs) with CT-identified morphological and first-order radiomics features, incorporating subgroup analysis based on tumor size.We enrolled 344 patients across four institutions, each pathologically diagnosed with 1–5 cm gGISTs and undergoing preoperative contrast-enhanced CT scans. Univariate and multivariate analyses were performed to investigate the independent CT morphological high-risk features of MI. Lesions were categorized into four subgroups based on their pathological LD: 1–2 cm (n = 69), 2–3 cm (n = 96), 3–4 cm (n = 107), and 4–5 cm (n = 72). CT morphological high-risk features of MI were evaluated in each subgroup. In addition, first-order radiomics features were extracted on CT images of the venous phase, and the association between these features and MI was investigated.Tumor size (p = 0.04, odds ratio, 1.41; 95% confidence interval: 1.01–1.96) and invasive margin (p < 0.01, odds ratio, 4.55; 95% confidence interval: 1.77–11.73) emerged as independent high-risk features for MI > 5 of 1–5 cm gGISTs from multivariate analysis. In the subgroup analysis, the invasive margin was correlated with MI > 5 in 3–4 cm and 4–5 cm gGISTs (p = 0.02, p = 0.03), and potentially correlated with MI > 5 in 2–3 cm gGISTs (p = 0.07). The energy was the sole first-order radiomics feature significantly correlated with gGISTs of MI > 5, displaying a strong correlation with CT-detected tumor size (Pearson’s ρ = 0.85, p < 0.01).The invasive margin stands out as the sole independent CT morphological high-risk feature for 1–5 cm gGISTs after tumor size-based subgroup analysis, overshadowing intratumoral morphological characteristics and first-order radiomics features.QuestionHow can accurate preoperative risk stratification of gGISTs be achieved to support treatment decision-making?FindingsInvasive margins may serve as a reliable marker for risk prediction in gGISTs up to 5 cm, rather than surface ulceration, irregular shape, necrosis, or heterogeneous enhancement.Clinical relevanceFor gGISTs measuring up to5 cm, preoperative prediction of the metastatic risk could help select patients who could be treated by endoscopic resection, thereby avoiding overtreatment.Methods: To investigate the correlation of the mitotic index (MI) of 1–5 cm gastric gastrointestinal stromal tumors (gGISTs) with CT-identified morphological and first-order radiomics features, incorporating subgroup analysis based on tumor size.We enrolled 344 patients across four institutions, each pathologically diagnosed with 1–5 cm gGISTs and undergoing preoperative contrast-enhanced CT scans. Univariate and multivariate analyses were performed to investigate the independent CT morphological high-risk features of MI. Lesions were categorized into four subgroups based on their pathological LD: 1–2 cm (n = 69), 2–3 cm (n = 96), 3–4 cm (n = 107), and 4–5 cm (n = 72). CT morphological high-risk features of MI were evaluated in each subgroup. In addition, first-order radiomics features were extracted on CT images of the venous phase, and the association between these features and MI was investigated.Tumor size (p = 0.04, odds ratio, 1.41; 95% confidence interval: 1.01–1.96) and invasive margin (p < 0.01, odds ratio, 4.55; 95% confidence interval: 1.77–11.73) emerged as independent high-risk features for MI > 5 of 1–5 cm gGISTs from multivariate analysis. In the subgroup analysis, the invasive margin was correlated with MI > 5 in 3–4 cm and 4–5 cm gGISTs (p = 0.02, p = 0.03), and potentially correlated with MI > 5 in 2–3 cm gGISTs (p = 0.07). The energy was the sole first-order radiomics feature significantly correlated with gGISTs of MI > 5, displaying a strong correlation with CT-detected tumor size (Pearson’s ρ = 0.85, p < 0.01).The invasive margin stands out as the sole independent CT morphological high-risk feature for 1–5 cm gGISTs after tumor size-based subgroup analysis, overshadowing intratumoral morphological characteristics and first-order radiomics features.QuestionHow can accurate preoperative risk stratification of gGISTs be achieved to support treatment decision-making?FindingsInvasive margins may serve as a reliable marker for risk prediction in gGISTs up to 5 cm, rather than surface ulceration, irregular shape, necrosis, or heterogeneous enhancement.Clinical relevanceFor gGISTs measuring up to5 cm, preoperative prediction of the metastatic risk could help select patients who could be treated by endoscopic resection, thereby avoiding overtreatment.Results: To investigate the correlation of the mitotic index (MI) of 1–5 cm gastric gastrointestinal stromal tumors (gGISTs) with CT-identified morphological and first-order radiomics features, incorporating subgroup analysis based on tumor size.We enrolled 344 patients across four institutions, each pathologically diagnosed with 1–5 cm gGISTs and undergoing preoperative contrast-enhanced CT scans. Univariate and multivariate analyses were performed to investigate the independent CT morphological high-risk features of MI. Lesions were categorized into four subgroups based on their pathological LD: 1–2 cm (n = 69), 2–3 cm (n = 96), 3–4 cm (n = 107), and 4–5 cm (n = 72). CT morphological high-risk features of MI were evaluated in each subgroup. In addition, first-order radiomics features were extracted on CT images of the venous phase, and the association between these features and MI was investigated.Tumor size (p = 0.04, odds ratio, 1.41; 95% confidence interval: 1.01–1.96) and invasive margin (p < 0.01, odds ratio, 4.55; 95% confidence interval: 1.77–11.73) emerged as independent high-risk features for MI > 5 of 1–5 cm gGISTs from multivariate analysis. In the subgroup analysis, the invasive margin was correlated with MI > 5 in 3–4 cm and 4–5 cm gGISTs (p = 0.02, p = 0.03), and potentially correlated with MI > 5 in 2–3 cm gGISTs (p = 0.07). The energy was the sole first-order radiomics feature significantly correlated with gGISTs of MI > 5, displaying a strong correlation with CT-detected tumor size (Pearson’s ρ = 0.85, p < 0.01).The invasive margin stands out as the sole independent CT morphological high-risk feature for 1–5 cm gGISTs after tumor size-based subgroup analysis, overshadowing intratumoral morphological characteristics and first-order radiomics features.QuestionHow can accurate preoperative risk stratification of gGISTs be achieved to support treatment decision-making?FindingsInvasive margins may serve as a reliable marker for risk prediction in gGISTs up to 5 cm, rather than surface ulceration, irregular shape, necrosis, or heterogeneous enhancement.Clinical relevanceFor gGISTs measuring up to5 cm, preoperative prediction of the metastatic risk could help select patients who could be treated by endoscopic resection, thereby avoiding overtreatment.Conclusions: To investigate the correlation of the mitotic index (MI) of 1–5 cm gastric gastrointestinal stromal tumors (gGISTs) with CT-identified morphological and first-order radiomics features, incorporating subgroup analysis based on tumor size.We enrolled 344 patients across four institutions, each pathologically diagnosed with 1–5 cm gGISTs and undergoing preoperative contrast-enhanced CT scans. Univariate and multivariate analyses were performed to investigate the independent CT morphological high-risk features of MI. Lesions were categorized into four subgroups based on their pathological LD: 1–2 cm (n = 69), 2–3 cm (n = 96), 3–4 cm (n = 107), and 4–5 cm (n = 72). CT morphological high-risk features of MI were evaluated in each subgroup. In addition, first-order radiomics features were extracted on CT images of the venous phase, and the association between these features and MI was investigated.Tumor size (p = 0.04, odds ratio, 1.41; 95% confidence interval: 1.01–1.96) and invasive margin (p < 0.01, odds ratio, 4.55; 95% confidence interval: 1.77–11.73) emerged as independent high-risk features for MI > 5 of 1–5 cm gGISTs from multivariate analysis. In the subgroup analysis, the invasive margin was correlated with MI > 5 in 3–4 cm and 4–5 cm gGISTs (p = 0.02, p = 0.03), and potentially correlated with MI > 5 in 2–3 cm gGISTs (p = 0.07). The energy was the sole first-order radiomics feature significantly correlated with gGISTs of MI > 5, displaying a strong correlation with CT-detected tumor size (Pearson’s ρ = 0.85, p < 0.01).The invasive margin stands out as the sole independent CT morphological high-risk feature for 1–5 cm gGISTs after tumor size-based subgroup analysis, overshadowing intratumoral morphological characteristics and first-order radiomics features.QuestionHow can accurate preoperative risk stratification of gGISTs be achieved to support treatment decision-making?FindingsInvasive margins may serve as a reliable marker for risk prediction in gGISTs up to 5 cm, rather than surface ulceration, irregular shape, necrosis, or heterogeneous enhancement.Clinical relevanceFor gGISTs measuring up to5 cm, preoperative prediction of the metastatic risk could help select patients who could be treated by endoscopic resection, thereby avoiding overtreatment.Key Points: To investigate the correlation of the mitotic index (MI) of 1–5 cm gastric gastrointestinal stromal tumors (gGISTs) with CT-identified morphological and first-order radiomics features, incorporating subgroup analysis based on tumor size.We enrolled 344 patients across four institutions, each pathologically diagnosed with 1–5 cm gGISTs and undergoing preoperative contrast-enhanced CT scans. Univariate and multivariate analyses were performed to investigate the independent CT morphological high-risk features of MI. Lesions were categorized into four subgroups based on their pathological LD: 1–2 cm (n = 69), 2–3 cm (n = 96), 3–4 cm (n = 107), and 4–5 cm (n = 72). CT morphological high-risk features of MI were evaluated in each subgroup. In addition, first-order radiomics features were extracted on CT images of the venous phase, and the association between these features and MI was investigated.Tumor size (p = 0.04, odds ratio, 1.41; 95% confidence interval: 1.01–1.96) and invasive margin (p < 0.01, odds ratio, 4.55; 95% confidence interval: 1.77–11.73) emerged as independent high-risk features for MI > 5 of 1–5 cm gGISTs from multivariate analysis. In the subgroup analysis, the invasive margin was correlated with MI > 5 in 3–4 cm and 4–5 cm gGISTs (p = 0.02, p = 0.03), and potentially correlated with MI > 5 in 2–3 cm gGISTs (p = 0.07). The energy was the sole first-order radiomics feature significantly correlated with gGISTs of MI > 5, displaying a strong correlation with CT-detected tumor size (Pearson’s ρ = 0.85, p < 0.01).The invasive margin stands out as the sole independent CT morphological high-risk feature for 1–5 cm gGISTs after tumor size-based subgroup analysis, overshadowing intratumoral morphological characteristics and first-order radiomics features.QuestionHow can accurate preoperative risk stratification of gGISTs be achieved to support treatment decision-making?FindingsInvasive margins may serve as a reliable marker for risk prediction in gGISTs up to 5 cm, rather than surface ulceration, irregular shape, necrosis, or heterogeneous enhancement.Clinical relevanceFor gGISTs measuring up to5 cm, preoperative prediction of the metastatic risk could help select patients who could be treated by endoscopic resection, thereby avoiding overtreatment. [ABSTRACT FROM AUTHOR]