Prediction of histologic grade of hepatocellular carcinoma using dual-layer spectral-detector computed tomography (CT): comparison of two region of interest plotting methods

Background

Multi-parameter imaging technology, which is based on substance separation, helps to predict the pathological grade of tumors. When using dual-layer spectral-detector computed tomography (DLCT) to quantify tumor properties, different methods of placing regions of interest (ROIs) directly impact the measurement of parameters, thus affecting the clinical diagnosis of lesions. Consequently, in this study, we aimed to compare the performance of 2 different ROI plotting methods on DLCT in differentiating the histologic grade of hepatocellular carcinoma (HCC).

Methods

This retrospective study included 48 consecutive patients with pathologically confirmed HCC, who underwent DLCT from May 2022 to March 2023. The attenuation value of conventional computed tomography (CT), electron density relative to water (EDW), normalized effective atomic number (NZeff), and normalized iodine density (NID) were measured by 2 radiologists using the conventional planar sketching (PS) method and the volumetric analysis method, respectively. The differences in parameters between the arterial phase (AP) and venous phase (VP) were calculated for each parameter (∆CT, ∆EDW, ∆NZeff, ∆NID). We used 2-sample t-test or Mann-Whitney U test was used to compare the differences in parameters between the 2 methods. Spearman correlation analysis was used to determine the correlation between each parameter and histologic grade. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance.

Results

The mean values for the spectral quantitative parameters (CTAP, NZeffAP, NIDAP) and the difference between the arterial phase and venous phase (AP-VP) of parameters (∆CT, ∆EDW, ∆NZeff) measured using the volumetric analysis method were significantly lower than those of the PS method (P<0.05). For the ∆NZeff, the volumetric analysis method achieved the highest area under the curve (AUC) with a value of 0.918 [95% confidence interval (CI): 0.847-0.988], followed by the PS method (AUC =0.853, 95% CI: 0.743-0.963).

Conclusions

The spectral parameters of DLCT provide a novel quantitative method for evaluating histological differentiation in patients with HCC, which is worthy of clinical recommendation. Different ROI plotting methods significantly impact the measurement of spectral parameters. Therefore, the whole tumor region should be covered in the parameter measurement of HCC lesions as much as feasible, which is more helpful in predicting the histological grading of tumors before treatment.

Clinical features and outcomes of young patients with low-grade non-rhabdomyosarcoma soft tissue sarcomas treated with a risk-based strategy: A report from Children's Oncology Group study ARST0332

BACKGROUND

In retrospective analyses, the Pediatric Oncology Group [POG) and the Federation National des Centres de Lutte Contre le Cancer (FNCLCC) histologic grade predict outcome in pediatric non-rhabdomyosarcoma soft tissue sarcoma (NRSTS), but prospective data on grading, clinical features, and outcomes of low-grade NRSTS are limited.

METHODS

We analyzed patients less than 30 years of age enrolled on Children's Oncology Group (COG) study ARST0332 (NCT00346164) with POG grade 1 or 2 NRSTS. Low-risk patients were treated with surgery alone. Intermediate-/high-risk patients received ifosfamide/doxorubicin and radiotherapy, with definitive resection either before or after 12 weeks of chemoradiotherapy.

RESULTS

Estimated 5-year event-free and overall survival were 90% and 100% low risk (n = 80), 55% and 78% intermediate risk (n = 15), and 25% and 25% high risk (n = 4). In low-risk patients, only local recurrence was seen in 10%; none with margins greater than 1 mm recurred locally. Sixteen of 17 intermediate-/high-risk patients who completed neoadjuvant chemoradiotherapy underwent gross total tumor resection, 80% with negative margins. Intermediate-/high-risk group events included one local and seven metastatic recurrences. Had the FNCLCC grading system been used to direct treatment, 29% of low-risk (surgery alone) patients would have received radiotherapy ± chemotherapy.

CONCLUSIONS

Most low-risk patients with completely resected POG low-grade NRSTS are successfully treated with surgery alone, and surgical margins greater than 1 mm may be sufficient to prevent local recurrence. Patients with intermediate- and high-risk low-grade NRSTS have outcomes similar to patients with high-grade histology, and require more effective therapies. Use of the current FNCLCC grading system may result in overtreatment of low-risk NRSTS curable with surgery alone.

Outcome Analysis of a Series of Mixed-Grade, Non-muscle Invasive, Papillary Carcinomas of the Bladder

Introduction. Papillary urothelial carcinomas are currently graded as either low- or high-grade tumors based on World Health Organization (WHO) 2022 guidelines for genitourinary tumors. However, a minority of tumors are mixed-grade tumors, composed predominantly of low-grade cancer with a minor high-grade component. In the 2022 WHO these cancers are recognized as having outcomes comparable to low-grade cancers, although data to date has been limited. Methods. The pathology records of a large academic institution were searched for mixed-grade, non-muscle invasive papillary carcinomas of the bladder and ureter in order to characterize prognosis of these cancers. Results. Of 136 cancers, the majority (n = 104, 76.5%) were solitary, mixed-grade tumors, while 21 (15.4%) had a concurrent low-grade cancer and 11 (8.1%) had multiple mixed-grade tumors at the time of diagnosis. At follow-up (median 48.3 months, range = 1.3 months-18.1 years), 71 cancers recurred (52.2%): 52 (38.2%) as low- or mixed-grade cancers and 18 (13.2%) as high-grade cancers. There were no instances of stage-progression to >pT2. Conclusions. The clinical outcome of mixed-grade carcinomas was similar to what has been reported for low-grade carcinomas. Based on our results, and prior congruent studies of mixed-grade lesions, these lesions may be regarded as a distinct sub-category with a better prognosis than high-grade tumors.

Role of magnetic resonance imaging in the prediction of histological grade in soft tissue sarcomas

BACKGROUND

Soft tissue sarcomas are rare malignant tumors with significant heterogeneity. The importance of classifying histological grades is fundamental to defining the treatment approach.

OBJECTIVE

To evaluate magnetic resonance imaging (MRI) in predicting the histological grade of soft tissue sarcomas.

METHODS

A retrospective observational study included patients over 18 years undergoing MRI and primary tumor surgery at AC Camargo Cancer Center from January 2015 to June 2022. Two radiologists evaluated MRI criteria (size, margin definition, heterogeneity of the T2 signal, high-intensity peritumoral signal on T2, and postperitumoral contrast), and a grading prediction score was calculated. χ2 and logistic regression analyses were conducted.

RESULTS

Sixty-eight patients were included (38 men; median: 48 years). Moreover, 52 high-grade and 16 low-grade tumors were observed. The MRI criteria associated with histological grade were peritumoral high-intensity T2-weighted signals (p < 0.001) and peritumoral postcontrast enhancement (p = 0.006). Logistic regression confirmed their significance (odds ratio [OR]: 11.8 and 8.8, respectively). Each score point increment doubled the chance of high-grade tumors (OR: 2.0; p = 0.014).

CONCLUSION

MRI effectively predicts histological grades of soft tissue sarcomas. Peritumoral high-intensity T2-weighted signals and peritumoral postcontrast enhancement are valuable indicators of high-grade tumors. This highlights MRI's importance in treatment decision-making for sarcoma patients.

Differentiation grade as a risk factor for lymph node metastasis in T1 colorectal cancer

Objectives

Japanese guidelines include high-grade (poorly differentiated) tumors as a risk factor for lymph node metastasis (LNM) in T1 colorectal cancer (CRC). However, whether the grading is based on the least or most predominant component when the lesion consists of two or more levels of differentiation varies among institutions. This study aimed to investigate which method is optimal for assessing the risk of LNM in T1 CRC.

Methods

We retrospectively evaluated 971 consecutive patients with T1 CRC who underwent initial or additional surgical resection from 2001 to 2021 at our institution. Tumor grading was divided into low-grade (well- to moderately differentiated) and high-grade based on the least or predominant differentiation analyses. We investigated the correlations between LNM and these two grading analyses.

Results

LNM was present in 9.8% of patients. High-grade tumors, as determined by least differentiation analysis, accounted for 17.0%, compared to 0.8% identified by predominant differentiation analysis. A significant association with LNM was noted for the least differentiation method (p < 0.05), while no such association was found for predominant differentiation (p = 0.18). In multivariate logistic regression, grading based on least differentiation was an independent predictor of LNM (p = 0.04, odds ratio 1.68, 95% confidence interval 1.00-2.83). Sensitivity and specificity for detecting LNM were 27.4% and 84.1% for least differentiation, and 2.1% and 99.3% for predominant differentiation, respectively.

Conclusions

Tumor grading via least differentiation analysis proved to be a more reliable measure for assessing LNM risk in T1 CRC compared to grading by predominant differentiation.

Descriptive analysis of prostate cancer pathology data from diagnosis and surgery in men from the 45 and Up Study

Information available from the New South Wales Cancer Registry (NSWCR) about the aggressiveness of prostate cancer is limited to the summary stage variable 'degree of spread', which contains a high proportion of cases defined as 'unknown'. In this study we demonstrate the feasibility of obtaining and analysing prostate cancer pathology data from stored pathology records. Pathology data were extracted from stored pathology records of incident prostate cancer cases in men participating in the 45 and Up Study, a large Australian prospective cohort study, who were diagnosed between January 2006 and December 2013. Baseline questionnaires from the 45 and Up Study were linked to the NSWCR. Demographic and pathology items were tabulated and associations described. We evaluated the completeness of pathological characteristics by degree of spread of cancer at diagnosis. Among the 123,921 men enrolled in the 45 and Up Study, 5,091 had incident prostate cancer and 5,085 were linked to a pathology record. The most complete variables included grade group of diagnostic (85.8%) and surgical (99.8%) specimens, margin status (98.1%), extraprostatic extension (95.1%) and seminal vesicle invasion (96.8%). Most diagnostic specimens were grade group 1 (26.6%) or 2 (23.5%). Of the 5,085 cases, 30.8% were classified by the NSWCR with unknown degree of spread; a pathology record could be extracted for 99.4% of these. The unknown degree of spread cases had similar levels of completeness and distribution of diagnostic and surgical pathology features to those with a localised degree of spread. This study demonstrated the feasibility of obtaining and analysing data derived from pathology reports from centralised state-based cancer registry notifications. Supplementing degree of spread information with pathology data from diagnosis and surgery will improve both the quality of research and policy aimed at improving the lives of men with prostate cancer.

Glioma Tumor Grading Using Radiomics on Conventional MRI: A Comparative Study of WHO 2021 and WHO 2016 Classification of Central Nervous Tumors

BACKGROUND

Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics-based machine learning (ML) classifiers remains unexplored.

PURPOSE

To assess the performance of ML in classifying glioma tumor grades based on various WHO criteria.

STUDY TYPE

Retrospective.

SUBJECTS

A neuropathologist regraded gliomas of 237 patients into WHO 2016 and 2021 from 2007 criteria.

FIELD STRENGTH/SEQUENCE

Multicentric 0.5 to 3 Tesla; pre- and post-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery.

ASSESSMENT

Radiomic features were selected using random forest-recursive feature elimination. The synthetic minority over-sampling technique (SMOTE) was implemented for data augmentation. Stratified 10-fold cross-validation with and without SMOTE was used to evaluate 11 classifiers for 3-grade (2, 3, and 4; WHO 2016 and 2021) and 2-grade (low and high grade; WHO 2007 and 2021) classification. Additionally, we developed the models on data randomly divided into training and test sets (mixed-data analysis), or data divided based on the centers (independent-data analysis).

STATISTICAL TESTS

We assessed ML classifiers using sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). Top performances were compared with a t-test and categorical data with the chi-square test using a significance level of P < 0.05.

RESULTS

In the mixed-data analysis, Stacking Classifier without SMOTE achieved the highest accuracy (0.86) and AUC (0.92) in 3-grade WHO 2021 grouping. The results of WHO 2021 were significantly better than WHO 2016 (P-value<0.0001). In the 2-grade analysis, ML achieved 1.00 in all metrics. In the independent-data analysis, ML classifiers showed strong discrimination between grade 2 and 4, despite lower performance metrics than the mixed analysis.

DATA CONCLUSION

ML algorithms performed better in glioma tumor grading based on WHO 2021 criteria. Nonetheless, the clinical use of ML classifiers needs further investigation.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Prognosis and survival study in patients with gastric adenocarcinoma and its relationship with pRb expression alteration: A retrospective IHC-based study

Background and Objective

Among cancers, gastric cancer has the fifth highest incidence worldwide and is the third most common mortality factor, which may have been due to inadequate knowledge of its molecular pathogenesis. The retinoblastoma gene (RB1), a tumor suppressor gene, may have a role in gastric cancer. This research aims to assess Rb expression as a prognostic marker to obtain more insight regarding gastric cancer.

Methods

This retrospective analytical study was done on 61 patients (45 males and 16 females) with gastric adenocarcinoma admitted from 2010 to 2012 in Shahid Sadoughi and Mortaz hospitals, Yazd, Iran. Demographic data, including age, gender, clinical signs and symptoms, and pathology reports, were retrieved from patients' hospital folders. Then, the altered Retinoblastoma gene expression was evaluated by immunohistochemistry studies. Acquired data were analyzed by SPSS software v.16. p < 0.05 was statistically considered meaningful.

Results

In this study, the ratio of men to women was higher (2.81:1), and the mean age of patients was 62.44 years. About 90.2% of patients died during the study. There was no meaningful relationship between the presence of pRb, the intensity of staining, the percentage of staining with patients' age, gender, tumor grading, and survival rate (p > 0.05). There was only a meaningful relationship between the grade of tumors and survival rate (p = 0.039).

Conclusion

Altered pRB expression is not common in gastric cancer and does not impact the survival and grading of tumors. Poorly differentiated tumors had an ominous outcome with the lowest survival time.

Association of Lymphovascular Space Invasion (LVSI) with Histological Tumor Grade and Myometrial Invasion in Endometrial Carcinoma: A Review Study

Endometrial carcinoma is one of the most frequent gynecological cancers in developed countries. Lymphovascular space invasion (LVSI), histological grade, and myometrial invasion (MMI) are important prognostic factors of endometrial carcinoma. LVSI is considered an independent poor prognostic factor in endometrial carcinoma. Based on the importance of LVSI, this study aimed to discuss the association of LVSI with tumor grade and MMI. A search of PubMed, EMBASE, Web of Science, Scopus, Google Scholar, and Cochrane Library was carried out to collect related studies. Consequently, most studies showed that LVSI is significantly associated with higher histologic grade and deep MMI.

Radiomic Features of the Edema Region May Contribute to Grading Meningiomas With Peritumoral Edema

BACKGROUND

Meningiomas are frequently accompanied by peritumoral edema (PTE). The potential value of radiomic features of edema region in meningioma grading has not been investigated.

PURPOSE

To investigate whether radiomic features of edema region contribute to grading meningiomas with PTE.

STUDY TYPE

Retrospective.

POPULATION

A total of 444 patients including 196 grade II and 248 WHO grade I meningiomas: 356 patients for training, 88 for validation.

FIELD STRENGTH/SEQUENCE

A 1.5-T/3.0-T, noncontrast T1-weighted (T1WI), T2-weighted (T2WI), contrast-enhanced T1-weighted (T1CE) spin echo sequences.

ASSESSMENT

A total of 851 radiomic features were extracted from each sequence on each region (tumor and edema region). These features were integrated by region respectively. Three subsets of clinical-radiomic features were constructed by joining clinical information (sex, age, tumor volume, and edema volume) and radiomic features of three regions: tumor, edema, and combined subsets. For each subset, features were filtered by the least absolute shrinkage and selection operator (LASSO) and Random Forest algorithm. Top 20 features of each subset were finally selected.

STATISTICAL TESTS

Stochastic Gradient Boosting, Random Forest, and Bagged AdaBoost predictive models were built based on each subset. Discriminative abilities of models were quantified using receiver operating characteristics (ROC) and the area under the curve (AUC). A P value < 0.05 was considered statistically significant.

RESULTS

Random Forest model based on combined subset (AUC [95% CI] = 0.880 [0.807-0.953]) had the best discriminative ability in grading meningiomas among the final models. The best model of edema subset and tumor subset were Random Forest model (AUC [95% CI] = 0.864 [0.791-0.938]) and Stochastic Gradient Boosting model (AUC [95% CI] = 0.844 [0.760-0.928]), respectively.

DATA CONCLUSION

Radiomic features of edema region may contribute to grading meningiomas with PTE. The Random Forest model based on combined subset surpasses the best model based on tumor or edema subset regarding grading meningiomas with PTE.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 3.

Role of MRI-Derived Radiomics Features in Determining Degree of Tumor Differentiation of Hepatocellular Carcinoma

Background: To investigate radiomics ability in predicting hepatocellular carcinoma histological degree of differentiation by using volumetric MR imaging parameters. Methods: Volumetric venous enhancement and apparent diffusion coefficient were calculated on baseline MRI of 171 lesions. Ninety-five radiomics features were extracted, then random forest classification identified the performance of the texture features in classifying tumor degree of differentiation based on their histopathological features. The Gini index was used for split criterion, and the random forest was optimized to have a minimum of nine participants per leaf node. Predictor importance was estimated based on the minimal depth of the maximal subtree. Results: Out of 95 radiomics features, four top performers were apparent diffusion coefficient (ADC) features. The mean ADC and venous enhancement map alone had an overall error rate of 39.8%. The error decreased to 32.8% with the addition of the radiomics features in the multi-class model. The area under the receiver-operator curve (AUC) improved from 75.2% to 83.2% with the addition of the radiomics features for distinguishing well- from moderately/poorly differentiated HCCs in the multi-class model. Conclusions: The addition of radiomics-based texture analysis improved classification over that of ADC or venous enhancement values alone. Radiomics help us move closer to non-invasive histologic tumor grading of HCC.

A Novel Preoperative Prediction Model Based on Deep Learning to Predict Neoplasm T Staging and Grading in Patients with Upper Tract Urothelial Carcinoma

Objectives: To create a novel preoperative prediction model based on a deep learning algorithm to predict neoplasm T staging and grading in patients with upper tract urothelial carcinoma (UTUC). Methods: We performed a retrospective cohort study of patients diagnosed with UTUC between 2001 and 2012 at our institution. Five deep learning algorithms (CGRU, BiGRU, CNN-BiGRU, CBiLSTM, and CNN-BiLSTM) were used to develop a preoperative prediction model for neoplasm T staging and grading. The Matthews correlation coefficient (MMC) and the receiver-operating characteristic curve with the area under the curve (AUC) were used to evaluate the performance of each prediction model. Results: The clinical data of a total of 884 patients with pathologically confirmed UTUC were collected. The T-staging prediction model based on CNN-BiGRU achieved the best performance, and the MMC and AUC were 0.598 (0.592–0.604) and 0.760 (0.755–0.765), respectively. The grading prediction model [1973 World Health Organization (WHO) grading system] based on CNN-BiGRU achieved the best performance, and the MMC and AUC were 0.612 (0.609–0.615) and 0.804 (0.801–0.807), respectively. The grading prediction model [2004 WHO grading system] based on BiGRU achieved the best performance, and the MMC and AUC were 0.621 (0.616–0.626) and 0.824 (0.819–0.829), respectively. Conclusions: We developed an accurate UTUC preoperative prediction model to predict neoplasm T staging and grading based on deep learning algorithms, which will help urologists to make appropriate treatment decisions in the early stage.

Developing a Predictive Grading Model for Children with Gliomas Based on Diffusion Kurtosis Imaging Metrics: Accuracy and Clinical Correlations with Patient Survival

Purpose: To develop a predictive grading model based on diffusion kurtosis imaging (DKI) metrics in children affected by gliomas, and to investigate the clinical impact of the predictive model by correlating with overall survival and progression-free survival. Materials and methods: 59 patients with a histological diagnosis of glioma were retrospectively studied (33 M, 26 F, median age 7.2 years). Patients were studied on a 3T scanner with a standardized MR protocol, including conventional and DKI sequences. Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), and apparent diffusion coefficient (ADC) maps were obtained. Whole tumour volumes (VOIs) were segmented semi-automatically. Mean DKI values were calculated for each metric. The quantitative values from DKI-derived metrics were used to develop a predictive grading model to develop a probability prediction of a high-grade glioma (pHGG). Three models were tested: DTI-based, DKI-based, and combined (DTI and DKI). The grading accuracy of the resulting probabilities was tested with a receiver operating characteristics (ROC) analysis for each model. In order to account for dataset imbalances between pLGG and pHGG, we applied a random synthetic minority oversampling technique (SMOTE) analysis. Lastly, the most accurate model predictions were correlated with progression-free survival (PFS) and overall survival (OS) using the Kaplan−Meier method. Results: The cohort included 46 patients with pLGG and 13 patients with pHGG. The developed model predictions yielded an AUC of 0.859 (95%CI: 0.752−0.966) for the DTI model, of 0.939 (95%CI: 0.879−1) for the DKI model, and of 0.946 (95%CI: 0.890−1) for the combined model, including input from both DTI and DKI metrics, which resulted in the most accurate model. Sample estimation with the random SMOTE analysis yielded an AUC of 0.98 on the testing set. Model predictions from the combined model were significantly correlated with PFS (25.2 months for pHGG vs. 40.0 months for pLGG, p < 0.001) and OS (28.9 months for pHGG vs. 44.9 months for pLGG, p < 0.001). Conclusions: a DKI-based predictive model was highly accurate for pediatric glioma grading. The combined model, derived from both DTI and DKI metrics, proved that DKI-based model predictions of tumour grade were significantly correlated with progression-free survival and overall survival.

Vimentin and Ki-67 immunolabeling in canine gastric carcinomas and their prognostic value

This study evaluated the expression of vimentin and Ki-67 proliferative index (PI) by immunohistochemistry in 30 canine gastric carcinomas (GCs) and a possible association with clinical and pathological features and patient's survival time. Vimentin immunoreactivity was assessed in neoplastic cells (in primary lesions, emboli, and metastases) and tumor-associated stroma (TAS) of canine GCs. Ki-67 PI was quantified in the neoplastic epithelial component. Vimentin immunolabeling in neoplastic cells was found in 30% of the primary lesions, in 82% of the neoplastic emboli, and in 50% of the metastases; in TAS, it was observed in all cases. A mean of 16% of the TAS was immunolabeled for vimentin. High vimentin immunolabeling in the TAS (>16%) was detected in 40% of cases. The average value of Ki-67 PI was 50%, and 80% of the lesions had Ki-67 PI above 20%. Vimentin immunolabeling in neoplastic cells was more frequent in less-differentiated carcinomas (diffuse [29%] and indeterminate types [75%]) than well-differentiated carcinomas (intestinal type [0%], P = .049). No significant differences were observed in vimentin immunolabeling in the TAS or Ki-67 PI according to histological diagnosis, depth of invasion, presence of neoplastic emboli or metastases. However, vimentin immunolabeling in the TAS was positively correlated with Ki-67 PI (r = .394, P = .031). Furthermore, a moderate negative correlation was observed between Ki-67 PI and survival time (r = -0.540). Our results suggest that vimentin and Ki-67 PI have potential for providing prognostic information in cases of canine GCs.

Comparison of clinical features between patients with bone and soft tissue fibrosarcomas

BACKGROUND AND OBJECTIVES

Fibrosarcomas predominantly arise in soft tissues, but can also develop in bone. Because of their rarity, whether bone development has an impact on clinical features has not been addressed.

METHODS

We included fibrosarcoma patients diagnosed between 1983 and 2016 in the Surveillance, Epidemiology, and End Results database. Differences in clinical features between fibrosarcoma of bone (FS-B) and fibrosarcoma of soft tissue (FS-ST) were investigated.

RESULTS

After excluding patients without information regarding cause of death, site of origin, distant tumor or survival, 1443 patients were included. Of those, 98 patients had FS-B. Patients with FS-B were younger, more frequently male, with fibrosarcomas that more often developed in an extremity and were histologically high-grade. In contrast, no difference in potential to metastasize was observed. Survival was almost equal between FS-B and FS-ST (FS-B/FS-ST: cancer-specific survival, hazard ratio [HR]: 1.2, 95% confidence interval [CI]: 0.8-1.7; overall survival, HR: 1.3, 95% CI: 0.9-1.7).

CONCLUSIONS

Our results clearly indicated that patient backgrounds differed, such as younger age and greater tendencies to affect males, develop in an extremity and show high-grade tumor in patients with FS-B. In contrast, no differences were observed in distant metastatic potential or survival.

Oncologic Outcomes of Total Length Gleason Pattern 4 on Biopsy in Men with Grade Group 2 Prostate Cancer

PURPOSE

Gleason Score 7 prostate cancer comprises a wide spectrum of disease risk, and precise substratification is paramount. Our group previously demonstrated that the total length of Gleason pattern (GP) 4 is a better predictor than %GP4 for adverse pathological outcomes at radical prostatectomy. We aimed to determine the association of GP4 length on prostate biopsy with post-prostatectomy oncologic outcomes.

MATERIALS AND METHODS

We compared 4 GP4 quantification methods-including maximum %GP4 in any single core, overall %GP4, total length GP4 (mm) across all cores and length GP4 (mm) in the highest volume core-for prediction of biochemical recurrence-free survival after radical prostatectomy using multivariable Cox proportional hazards regression.

RESULTS

A total of 457 men with grade group 2 prostate cancer on biopsy subsequently underwent radical prostatectomy. The 3-year biochemical recurrence-free survival probability was 85% (95% CI 81-88). On multivariable analysis, all 4 GP4 quantification methods were associated with biochemical recurrence-maximum %GP4 (HR=1.30; 95% CI 1.07-1.59; p=0.009), overall %GP4 (HR=1.61; 95% CI 1.21-2.15; p=0.001), total length GP4 (HR=2.48; 95% CI 1.36-4.52; p=0.003) and length GP4 in highest core (HR=1.32; 95% CI 1.11-1.57; p=0.001). However, we were unable to identify differences between methods of quantification with a relatively low event rate.

CONCLUSIONS

These findings support further studies on GP4 quantification in addition to the ratio of GP3 and GP4 to classify prostate cancer risk. Research should also be conducted on whether GP4 quantification could provide a surrogate endpoint for disease progression for trials in active surveillance.

Stromal Tumor Infiltrating Lymphocytes (sTILs) Were Associated with a Higher Grade and a Lower Stage of Indonesian Triple Negative Breast Cancers

OBJECTIVE

This study aimed to investigate the association of sTILs with clinicopathological parameters and overall survival (OS) in patients with triple negative breast cancer (TNBC).

METHODS

One hundred and twenty-five paraffin embedded tissue of patients with TNBC, collected from Dr. Sardjito General Hospital Yogyakarta, Indonesia, between 2008-2017, were used in this study. Stromal TILs were examined from hematoxylin and eosin (H&E)-stained samples, and classified as either low or high score using 20% cut-off. Analysis of the association of sTILs with clinicopathological parameters, relative risk (RR) and OS used 95% confidence interval (CI) with significance set as p<0.05.

RESULTS

The higher proportion of TNBC patients in this study were ≥40 years old (83.3%), high tumor grade (68%), tumor stage >IIIa (56%), alive (50.4%), and with low sTILs (54.4%). The results showed significant association between sTILs and a higher grade or a lower stage of tumor (B = 0.259, 95%CI = 0.090-0.468, p = 0.004 and B = -0.255, 95%CI = -0.433 - -0.080, p = 0.005, respectively ). Meanwhile sTILs were not associated with age at diagnosis (B = 0.027, 95%CI = -0.193 - 0.264  p = 0.758 nor 3-year OS of patients (HR = 0.342, 95%CI = 0.41 - 1.43  p = 0.402).

CONCLUSION

The results indicate that sTILs may serve as an additional pathological parameter for TNBC.

Predictive Performance of Prospectively Applied ISUP and Fuhrman Grade in Nonmetastatic Renal Cell Carcinoma

BACKGROUND/AIM

In 2012, the International Society of Urological Pathology (ISUP) recommended replacing Fuhrman with ISUP for grading renal cell carcinoma (RCC). Our aim was to report recurrence-free survival (RFS) and assess prognostic value of ISUP and Fuhrman for predicting recurrence using original pathology assessment and routine follow-up data.

PATIENTS AND METHODS

In this single-institution retrospective cohort study, 686 patients underwent a single session total or partial nephrectomy due to nonmetastatic RCC (nmRCC). Of those, 564 had tumors prospectively graded according to either ISUP or Fuhrman, which defined the cohorts. RFS was defined as the interval from surgery to local recurrence and/or metastasis. Differences in RFS were calculated with log rank test. Cox models adjusted for risk factors were used for predicting recurrence.

RESULTS

During a median follow-up of 36 months in the ISUP group (n=152), 11% developed recurrent disease. RFS was significantly lower for grade 4 compared to 1-3 (p<0.001), but non-significant between 1-3. Grade was the only significant predictor in multivariate analyses. During a median follow-up time of 50 months in the Fuhrman group (n=412), 16% developed recurrent disease. There was a significant difference in RFS between grades 2 and 3 (p=0.003) and between 3 and 4 (p<0.001), but non-significant between 1 and 2 (p=0.063). Grade, positive surgical margin, tumor size ≥4 cm, and pT were significant predictors of recurrence in multivariate analyses.

CONCLUSION

ISUP grading alone is an accurate tool for predicting recurrence in patients with nmRCC.

Time to castration-resistant prostate cancer and prostate cancer death according to PSA response in men with non-metastatic prostate cancer treated with gonadotropin releasing hormone agonists

Objectives: To predict castration-resistant prostate cancer (CRPC) and prostate cancer (Pca) death by use of clinical variables at Pca diagnosis and PSA levels after start of gonadotropin-releasing hormone agonists (GnRH) in men with non-metastatic castration sensitive prostate cancer (nmCSPC).Materials and Methods: PSA values for 1603 men with nmCSPC in the National Prostate Cancer Register of Sweden who received GnRH as primary treatment were retrieved from Uppsala-Örebro PSA Cohort and Stockholm PSA and Biopsy Register. All men had measured PSA before (pre-GnRH PSA) and 3-6 months after (post-GnRH PSA) date of start of GnRH. Unadjusted and adjusted Cox models were used to predict CRPC by PSA levels. PSA levels and ISUP grade were used to construct a risk score to stratify men by tertiles according to risk of CRPC and Pca death.Results: 788 (49%) men reached CRPC and 456 (28%) died of Pca during follow-up. Post-GnRH PSA predicted CRPC regardless of pre-GnRH PSA. CRPC risk increased with higher post-GnRH PSA, HR 4.7 (95% CI: 3.4-6.7) for PSA > 16 ng/mL vs 0-0.25 ng/mL and with ISUP grade, HR 3.7 (95%: 2.5-5.4) for ISUP 5 vs ISUP 1. Risk of Pca death in men above top vs bellow bottom tertile of post-GnRH PSA and ISUP grade was HR 4.1 (95% CI: 3.0-5.5).Conclusion: A risk score based on post-GnRH PSA and ISUP grade could be used for early identification of a target group for future clinical trials on additional therapy to GnRH.

Evaluating the Outcomes of Active Surveillance in Grade Group 2 Prostate Cancer: Prospective Results from the Canary PASS Cohort

PURPOSE

Active surveillance (AS) for grade group (GG) 2 patients is not yet well defined. We sought to compare clinical outcomes of men with GG1 and GG2 prostate cancer undergoing AS in a large prospective North American cohort.

MATERIALS AND METHODS

Participants were prospectively enrolled in an AS study with protocol-directed followup at 10 centers in the U.S. and Canada. We evaluated time from diagnosis to biopsy grade reclassification and time to treatment. In men treated after initial surveillance, adverse pathology and recurrence were also analyzed.

RESULTS

At diagnosis, 154 (9%) had GG2 and 1,574 (91%) had GG1. Five-year reclassification rates were similar between GG2 and GG1 (30% vs 37%, p=0.11). However, more patients with GG2 were treated at 5 years (58% vs 34%, p <0.001) and GG at diagnosis was associated with time to treatment (HR=1.41; p=0.01). Treatment rates were similar in patients who reclassified during AS, but in patients who did not reclassify, those diagnosed with GG2 underwent definitive treatment more often than GG1 (5-year treatment rates 52% and 12%, p <0.0001). In participants who underwent radical prostatectomy after initial surveillance, the adjusted risk of adverse pathology was similar (HR=1.26; p=0.4). Biochemical recurrence within 3 years of treatment for GG2 and GG1 patients was 6% for both groups.

CONCLUSIONS

In patients on AS, the rate of definitive treatment is higher after an initial diagnosis of GG2 than GG1. Adverse pathology after radical prostatectomy and short-term biochemical recurrence after definitive treatment were similar between GG2 and GG1.

Uterine carcinosarcoma vs endometrial serous and clear cell carcinoma: A systematic review and meta-analysis of survival

Background

It is unclear whether uterine carcinosarcoma (UCS) is more aggressive than endometrial serous carcinoma (SC) and clear cell carcinoma (CCC).

Objectives

To compare the prognosis of UCS to that of endometrial SC and CCC, through a systematic review and meta‐analysis.

Methods

Four electronic databases were searched from January 2000 to October 2020. All studies assessing hazard ratio (HR) for death in UCS vs SC and/or CCC. HRs for death with 95% confidence interval were extracted and pooled by using a random‐effect model. A significant P‐value <0.05 was adopted.

Results

Six studies with 11 029 patients (4995 with UCS, 4634 with SC, 1346 with CCC and 54 with either SC or CCC) were included. UCS showed a significantly worse prognosis than SC/CCC both overall (HR = 1.51; P = 0.008) and at early stage (HR = 1.58; P < 0.001). Similar results were found for UCS vs SC (HR = 1.53; P < 0.001) and UCS vs CCC (HR = 1.60; P < 0.001).

Conclusions

Compared to SC and CCC, UCS has a significantly worse prognosis, with a 1.5–1.6‐fold increased risk of death. This might justify a more aggressive treatment for UCS compared to SC and CCC. Further studies are necessary to define the prognostic impact of different molecular subgroups.

Uterine carcinosarcoma shows worse prognosis than serous and clear cell carcinoma; this could impact patient management.

Brain Metastasis in Soft Tissue Sarcoma at Initial Presentation

BACKGROUND/AIM

Brain metastasis is a rare condition among patients with soft tissue sarcoma (STS), and its precise incidence remains unclear. The aim of this study was to investigate which patients should be screened for brain metastasis.

PATIENTS AND METHODS

We identified all patients with STS diagnosed between 2010 and 2015 in the SEER database. Incidence of brain metastasis at initial presentation and higher incidence of brain metastasis by histological subtype were investigated. In addition, risk factors for brain metastasis were examined.

RESULTS

A total of 26,676 patients were included for analysis, of whom 162 patients (0.6%) had brain metastasis. Alveolar soft part sarcoma (6.3%), malignant hemangioendothelioma (3.1%) and malignant schwannoma (2.6%) showed higher incidence of brain metastasis. Deep-rooted tumor, trunk tumor, and histological high-grade tumor tended to show higher incidence of brain metastasis.

CONCLUSION

Risk factors for brain metastasis were deep location, trunk development and histologically high-grade tumor, or specific histological subtypes.

How Much Reliable Is the Current Belief on Grade Group 1 Prostate Cancer?

Objective: To evaluate the clinicopathological characteristics of grade group 1 (GG1) prostate cancer in Korean populations.

Methods: We retrospectively analyzed 492 consecutive radical prostatectomy specimens from our institution, which included those from 322 men with clinical GG1 and 170 with clinical GG2 tumors between years 2009 and 2018. The incidence of Gleason score (GS) upgrading, extraprostatic extension (EPE), and seminal vesicle invasion (SVI) were evaluated in patients with clinical GG1. In pathological GG1 cases, the distribution of adverse pathological features including EPE, lymphovascular invasion (LVI), perineural invasion (PNI), and biochemical recurrence (BCR) was analyzed.

Results: Altogether, 78 (24.2%) out of 322 men in the clinical GG1 group demonstrated upgrading of GS, including 19 men with pathological Gleason score 4 + 3 = 7 and 6 with ≥ pathological Gleason score 4 + 4 = 8 cases. EPE was found in 37 (11.5%) and 22 (8.9%) men in clinical GG1 and pathological GG1 group, respectively. The incidence of LVI and PNI in the pathological GG1 cases was 2.8% (n = 7) and 28.6% (n = 71), respectively. BCR was observed in 4 men in pathological GG1 T2 (n = 226) and 2 men in GG1 T3 (n = 22) group. When we compared the pathological features between pathological GG1 T3 vs. GG2 T2, there was no statistical differences in the incidence of LVI and PNI between the two groups.

Conclusions: Contrary to the current concept that GG1 is almost always clinically insignificant, it seems that GG1 still possess its respectable position as a group of cancer with aggressiveness. These findings should be kept in mind when deciding on treatment options for prostate cancer patients in the Asian populations.

Grading of Multifocal Prostate Cancer Cases in which the Largest Volume and the Highest Grade Do Not Coincide within One Lesion

PURPOSE

In general, the index lesion of prostate cancer has the largest tumor volume, the highest Grade Group (GG), and the highest stage (concordant cases). However, these factors sometimes do not coincide within one lesion (discordant cases). In such discordant cases, the largest tumor may not be of biological significance and the secondary tumor may more greatly impact the prognosis.

MATERIALS AND METHODS

We retrospectively reviewed the medical records of patients who underwent radical prostatectomy, and we identified 580 (85.3%) concordant cases and 100 (14.7%) discordant cases. The end point of this study was biochemical recurrence, and median followup was 4.2 years.

RESULTS

Among discordant cases in which GGs of the largest tumor and the highest GG tumor differed, the majority (67 patients) had the largest tumor of GG 2, and we set them as the study cohort. On the other hand, we regarded 212 concordant cases with an index tumor of GG 2 as the control cohort. The study cohort comprised 48 (71.6%) patients with a secondary tumor of GG 3 and 19 (28.4%) with a secondary tumor of GG 4/5. Kaplan-Meier curves revealed that the 5-year biochemical recurrence-free survival rates were 76%, and 67%, respectively. The 5-year biochemical recurrence-free survival rate of the control cohort was 91%, which was significantly better than that of the study cohort (p=0.013 and p=0.014, respectively).

CONCLUSIONS

Our study suggests that the prognosis of discordant cases is better determined by the secondary cancer lesion with the highest GG instead of the largest lesion.