Prediction of Organ-confined Prostate Cancer: Incremental Value of MR Imaging and MR Spectroscopic Imaging to Staging Nomograms

Comparison of Diagnostic Value between 99mTechnetium-Methylene Diphosphate Bone Scan and 99mTechnetium-Prostate-specific Membrane Antigen Scan in Patients with Prostate Cancer with Osseous Metastases

Background

Prostate cancer (PCa) ranks as the second most prevalent cancer among men globally. The utilization of efficient and cost-effective diagnostic and therapeutic approaches holds paramount importance in the diagnosis and treatment of these patients, significantly impacting treatment outcomes. This study focuses on the investigation and comparison of two commonly employed scans within the treatment process for these patients.

Methods

In this prospective study, which spanned over 2 years, 40 patients diagnosed with PCa underwent examination using two scans: 99m Technetium-Prostate-specific Membrane Antigen (99mTC-PSMA) Scan and between Technetium-Methylene Diphosphate (99mTC-MDP) Bone Scan. The findings of these scans were then compared with each other, as well as with the results obtained from magnetic resonance imaging and the prostate-specific antigen level. The analysis of the results was conducted utilizing SPSS 22 software, and descriptive statistical methods were employed to present the findings.

Results

In this prospective study, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the 99mTC-MDP Bone Scan were found to be 88.2%, 83.3%, 96.7%, 55.5%, and 87.5%, respectively. Similarly, for the 99mTC-PSMA Scan, the corresponding values were 94.1%, 83.3%, 96.4%, 83.3%, and 92.5%, respectively.

Conclusions

Based on the findings of this study, it can be concluded that the diagnostic accuracy of the 99mTC-PSMA Scan is marginally higher compared to the 99mTC-MDP Bone Scan. Therefore, for patients who are limited to only one scan, the 99mTC-PSMA Scan appears to be the preferable choice.

Multiparametric MRI is not sufficient for prostate cancer staging: A single institutional experience validated by a multi-institutional regional collaborative

OBJECTIVE

Multiparametric magnetic resonance imaging (mpMRI) has been increasingly utilized in prostate cancer (CaP) diagnosis and staging. While Level 1 data supports MRI utility in CaP diagnosis, there is less data on staging utility. We sought to evaluate the real-world accuracy of mpMRI in staging localized CaP.

MATERIALS AND METHODS

Men who underwent radical prostatectomy (RP) for CaP in 2021 at our institution were identified. Sensitivity, specificity, positive predictive value and negative predictive value of mpMRI in predicting pT2N0 organ confined disease , extracapsular extension , seminal vesicle invasion , lymph node involvement, and bladder neck invasion were evaluated. Associations between MRI accuracy and AUA risk stratification (AUA RS), MRI institution (MRI-I), MRI strength (1.5 vs. 3T) (MRI-S), and MRI timing (MRI-T) were assessed. These analyses were repeated using Pennsylvania Urologic Regional Collaborative (PURC) data.

RESULTS

Institutional and community mpMRI CaP staging data demonstrated poor sensitivity (2.9%-49.2%% vs. 16.8%-24.4%), positive predictive value (40%-100% vs. 35.8%-68.2%), and negative predictive value (56.3%-94.3% vs. 68.4%-96.2%) in predicting surgical pathologic features - in contrast, specificity (89.1%-100% vs. 93.9%-98.6%) was adequate. mpMRI accuracy for extracapsular extension, seminal vesicle invasion, and lymph node involvement was significantly (p < 0.001) associated with AUA RS. There was no association between mpMRI accuracy and MRI-I, MRI-S, and MRI-T.

CONCLUSION

Despite enthusiasm for its use, in a real-world setting, mpMRI appears to be a poor staging study for localized CaP and is unreliable as the sole means of staging patients prior to prostatectomy. mpMRI should be used cautiously as a staging tool for CaP, and should be interpreted considering individual patient risk strata.

Nomogram for prediction of peritoneal metastasis risk in colorectal cancer

OBJECTIVE

Peritoneal metastasis is difficult to diagnose using traditional imaging techniques. The main aim of the current study was to develop and validate a nomogram for effectively predicting the risk of peritoneal metastasis in colorectal cancer (PMCC).

METHODS

A retrospective case-control study was conducted using clinical data from 1284 patients with colorectal cancer who underwent surgery at the First Affiliated Hospital of Guangxi Medical University from January 2010 to December 2015. Least absolute shrinkage and selection operator (LASSO) regression was applied to optimize feature selection of the PMCC risk prediction model and multivariate logistic regression analysis conducted to determine independent risk factors. Using the combined features selected in the LASSO regression model, we constructed a nomogram model and evaluated its predictive value via receiver operating characteristic (ROC) curve analysis. The bootstrap method was employed for repeated sampling for internal verification and the discrimination ability of the prediction models evaluated based on the C-index. The consistency between the predicted and actual results was assessed with the aid of calibration curves.

RESULTS

Overall, 96 cases of PMCC were confirmed via postoperative pathological diagnosis. Logistic regression analysis showed that age, tumor location, perimeter ratio, tumor size, pathological type, tumor invasion depth, CEA level, and gross tumor type were independent risk factors for PMCC. A nomogram composed of these eight factors was subsequently constructed. The calibration curve revealed good consistency between the predicted and actual probability, with a C-index of 0.882. The area under the curve (AUC) of the nomogram prediction model was 0.882 and its 95% confidence interval (CI) was 0.845-0.919. Internal validation yielded a C-index of 0.868.

CONCLUSION

We have successfully constructed a highly sensitive nomogram that should facilitate early diagnosis of PMCC, providing a robust platform for further optimization of clinical management strategies.

Prognostic nomogram that predicts progression-free survival and overall survival of patients with ovarian clear cell carcinoma

Objectives

We aims to develop nomograms to predict progression-free survival (PFS) and overall survival (OS) in patients with ovarian clear cell carcinoma (OCCC) after primary treatment and compare the predictive accuracy with the currently used International Federation of Gynecology and Obstetrics (FIGO) system.

Methods

We collected data from 358 Chinese patients diagnosed with OCCC and who underwent standard treatment at our hospital. Patients diagnosed from 1982-9 to 2011-12 were classified as the training group and patients diagnosed from 2012-1 to 2016-11 were classified as the validation group. Nomograms were developed based on the training group and was validated in the validation group. The predictive performance was determined by concordance index and calibration curve.

Results

The most predictive nomogram for PFS was constructed using variables: thrombosis, the FIGO staging, residual of the tumor and distant metastasis, with a concordance index of 0.738. While the nomogram for OS consisted of thrombosis, lymph node metastasis, residual of the tumor, malignant ascites/washing, and platinum resistance, with a concordance index of 0.835. The nomograms were internally validated by concordance indexes of 0.775 and 0.807 for predicting PFS and OS, respectively. In comparison, the concordance statistics for OS based on the FIGO staging was significantly lower (P&lt;0.05).

Conclusion

We have established two prognostic nomograms for recurrence and long-term survival in patients with OCCC after primary treatment in a large Chinese center and validated them in patients from the same center. This tool used variables specifically related to OCCC and was more accurate than the FIGO system. It is relatively easy to use in clinic for patient counseling, postoperative management, and follow-up for individual patients.

Prognostic Nomogram of Osteocarcinoma after Surgical Treatment

Purpose

This study aimed to establish a valid prognostic nomogram for osteocarcinoma after surgical management.

Methods

Based on the SEER database, we retrieved the clinical variables of patients confirmed to have osteocarcinoma between 1975 and 2016. Then, we performed univariate and multivariate analyses and constructed a nomogram of overall survival.

Results

Multivariate analysis of the primary cohort revealed that the independent factors for survival were age, grade, pathologic stage, T stage, and surgery performed. All these factors were showed by the nomogram. The correction curve of survival probability showed that the prediction results of nomogram well agreed with the actual observation results. The C index of the nomogram used to predict survival was 0.82; the AUC of 1-year, 3-year, and 5-year survival rates in the training cohort were 0.9, 0.819, and 0.80631, respectively, indicating that the model was accurate and reliable; whether the operation was performed or not; T stage; grade; and age were the main factors affecting the survival of patients. The AUC of the validation cohort for 1 year, 3 years, and 5 years were 0.8, 0.831, and 0.80023, respectively.

Conclusion

The proposed nomogram can more accurately predict the prognosis of patients with osteocarcinoma after surgical management. This could be a potential method that services clinical work.

Clinical Prediction Nomograms to Assess Overall Survival and Disease-Specific Survival of Patients with Salivary Gland Adenoid Cystic Carcinoma

Aim

Salivary gland adenoid cystic carcinoma (SACC) is the second highest incidence of malignant salivary gland tumor. The purpose of this study was to establish nomograms combined with SACC patients based on the Surveillance, Epidemiology, and End Results (SEER) database.

Methods

Patients with SACC were included in the SEER∗Stat Database from 2004 to 2016. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to filter potential prognostic clinical variables. Multivariate analysis from the Cox proportional hazards model was performed to determine the independent prognostic factors on overall survival (OS) and disease-specific survival (DSS), applied to develop nomograms. The Schönfeld residual test verified the proportional hazard assumption. The discrimination and consistency of nomograms was assessed and validated according to concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration curves using an internal 1,000 times bootstrap resampling. The nomogram's net clinical benefit was assessed through decision curve analysis (DCA).

Results

A total of 658 patients with SACC were included. Age, T stage, N stage, M stage, histologic grade, and surgery were independent prognostic factors for OS and DSS. Based on these independent prognostic factors, nomograms were developed to predict 3-, 5-, and 10-year OS and DSS. In the validation of 1,000 times bootstrap resampling, the C-index and ROC curves had good discriminatory ability. The calibration curves indicated excellent consistency between the predicted and actual survival results in the nomograms. The DCA curves demonstrated that the nomograms had good clinical benefit and were superior to the TNM stage and other variables.

Conclusions

Two nomograms developed in this study precisely predicted the 3-, 5-, and 10-year OS and DSS rates of patients with SACC in accordance with independent prognostic factors, and their clinical value is better than TNM staging, providing a prognostic reference for other SACC patients.

Prognostic Nomograms Based on the Cirrhotic Severity Scoring for Preoperative Prediction of Long-Term Outcomes in Patients with HBV-Related Hepatocellular Carcinoma and Child-Pugh Grade A Liver Function

Background

Cirrhotic severity scoring (CSS) is a noninvasive method that can predict histological severity of cirrhosis. This study is aimed at assessing the predictive value of CSS on long-term outcomes after curative hepatectomy for patients with hepatitis B virus- (HBV-) related hepatocellular carcinoma (HCC) and Child-Pugh grade A liver function and further developing novel nomograms to preoperatively predict posthepatectomy recurrence and survival.

Methods

Consecutive patients who underwent curative hepatectomy for HCC between 2008 and 2014 were retrospectively studied. According to the CSS, patients were subclassified into 3 groups: no/mild, moderate, and severe cirrhosis. The impact of CSS on recurrence-free survival (RFS) and overall survival (OS) was assessed. Furthermore, RFS and OS nomograms were developed.

Results

The 5-year RFS and OS rates were 36.1% and 62.8% in the no/mild cirrhosis group, compared with 28.4% and 56.2% in the moderate cirrhosis group, and 16.2% and 33.0% in the severe cirrhosis group. Long-term survival outcomes were significantly worse with the increment of cirrhotic severity. CSS, alpha-fetoprotein level, tumor size, tumor number, and macrovascular invasion were identified as independent predictors of both RFS and OS. Besides, albumin-bilirubin grade was an independent risk factor of OS not RFS. RFS- and OS-predictive nomograms based on these preoperative variables were built. For these 2 nomograms, the C-indexes were 0.696 and 0.732, respectively. Calibration curves exhibited good agreement between actual observation and nomogram prediction.

Conclusions

CSS was a predictor for long-term outcomes in HCC patients after curative hepatectomy. The novel nomograms exhibited accurate preoperative prediction of posthepatectomy recurrence and OS.

Concordance between Preoperative mpMRI and Pathological Stage and Its Influence on Nerve-Sparing Surgery in Patients with High-Risk Prostate Cancer

Background: We aimed to determine the concordance between the radiologic stage (rT), using multiparametric magnetic resonance imaging (mpMRI), and pathologic stage (pT) in patients with high-risk prostate cancer and its influence on nerve-sparing surgery compared to the use of the intraoperative frozen section technique (IFST). Methods: The concordance between rT and pT and the rates of nerve-sparing surgery and positive surgical margin were assessed for patients with high-risk prostate cancer who underwent radical prostatectomy. Results: The concordance between the rT and pT stages was shown in 66.4% (n = 77) of patients with clinical high-risk prostate cancer. The detection of patients with extraprostatic disease (≥pT3) by preoperative mpMRI showed a sensitivity, negative predictive value and accuracy of 65.1%, 51.7% and 67.5%. In addition to the suspicion of extraprostatic disease in mpMRI (≥rT3), 84.5% (n = 56) of patients with ≥rT3 underwent primary nerve-sparing surgery with IFST, resulting in 94.7% (n = 54) of men with at least unilateral nerve-sparing surgery after secondary resection with a positive surgical margin rate related to an IFST of 1.8% (n = 1). Conclusion: Patients with rT3 should not be immediately excluded from nerve-sparing surgery, as by using IFST some of these patients can safely undergo nerve-sparing surgery.

A Prognostic Model Based on mRNA Expression Analysis of Esophageal Squamous Cell Carcinoma

Background: The aim of this study was to identify prognostic markers for esophageal squamous cell carcinoma (ESCC) and build an effective prognostic nomogram for ESCC.

Methods: A total of 365 patients with ESCC from three medical centers were divided into four cohorts. In the discovery phase of the study, we analyzed transcriptional data from 179 cancer tissue samples and identified nine marker genes using edgeR and rbsurv packages. In the training phase, penalized Cox regression was used to select the best marker genes and clinical characteristics in the 179 samples. In the verification phase, these marker genes and clinical characteristics were verified by internal validation cohort (n = 58) and two external cohorts (n = 81, n = 105).

Results: We constructed and verified a nomogram model based on multiple clinicopathologic characteristics and gene expression of a patient cohort undergoing esophagectomy and adjuvant radiochemotherapy. The predictive accuracy for 4-year overall survival (OS) indicated by the C-index was 0.75 (95% CI, 0.72–0.78), which was statistically significantly higher than that of the American Joint Committee on Cancer (AJCC) seventh edition (0.65). Furthermore, we found two marker genes (TM9SF1, PDZK1IP) directly related to the OS of esophageal cancer.

Conclusion: The nomogram presented in this study can accurately and impersonally predict the prognosis of ESCC patients after partial resection of the esophagus. More research is required to determine whether it can be applied to other patient populations. Moreover, we found two marker genes directly related to the prognosis of ESCC, which will provide a basis for future research.

A Novel Nomogram for Prediction of Early Postoperative Complications of Total Gastrectomy for Gastric Cancer

Background

Accurate prediction of postoperative complications is especially important for the formulation of treatment plans for patients with total gastrectomy (TG) for gastric cancer (GC). The purpose of this study was to establish a risk assessment model for early postoperative complications.

Methods

This retrospective study involved 363 patients with GC who underwent TG from January 2019 to December 2020. The influencing factors were explored by univariate and multivariable logistic regression; then, a nomogram was established and verified by internal verification.

Results

Linear stapler (OR=2.501, P=0.030), age (OR=1.052, P =0.024), blood transfusion (yes) (OR=2.450, P =0.021), one-time consumables for surgery (or=1.000, P =0.022), number of total lymph nodes (OR=1.060, P =0.011) and number of positive lymph nodes (OR=1.054, P =0.029) were independent risk factors for early postoperative complications in TG, and nomogram model was constructed. The C-index of primary cohort, modeling cohort and validation cohort was 0.787, 0.754 and 0.912. The calibration curves showed good accuracy.

Conclusion

This study used the indicators available before and during surgery to establish a nomogram model for early postoperative complications of total gastrectomy for gastric cancer, which found that linear stapler (LS), blood transfusion, one-time consumables for surgery, number of total lymph nodes and number of positive lymph nodes were factors.

Development and validation of prognostic nomograms for patients with colon neuroendocrine neoplasms

BACKGROUND

Colon neuroendocrine neoplasms (NENs) have one of the poorest median overall survival (OS) rates among all NENs. The American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system-currently the most commonly used prediction model-has limited prediction accuracy because it does not include parameters such as age, sex, and treatment. The aim of this study was to construct nomograms containing various clinically important parameters to predict the prognosis of patients with colon NENs more accurately.

METHODS

Using the Surveillance, Epidemiology, and End Results (SEER) database, we performed a retrospective analysis of colon NENs diagnosed from 1975 to 2016. Data were collected from 1196 patients; almost half were female (617/1196, 51.6%), and the average age was 61.94 ± 13.05 years. Based on the age triple cut-off values, there were 396 (33.1%), 408 (34.1%), and 392 (32.8%) patients in age groups 0-55 years, 55-67 years, and ≥ 68 years, respectively. Patients were randomized into training and validation cohorts (3:1). Independent prognostic factors were used for construction of nomograms to precisely predict OS and cancer-specific survival (CSS) in patients with colon NENs.

RESULTS

Multivariate analysis showed that age ≥ 68 years, sex, tumor size, grade, chemotherapy, N stage, and M stage were independent predictors of OS. In the validation cohort, the Concordance index (C-index) values of the OS and CSS nomograms were 0.8345 (95% confidence interval [CI], 0.8044-0.8646) and 0.8209 (95% CI, 0.7808-0.861), respectively. C-index also indicated superior performance of both nomograms (C-index 0.8347 for OS and 0.8668 for CSS) compared with the AJCC TNM classification (C-index 0.7159 for OS and 0.7366 for CSS).

CONCLUSIONS

We established and validated new nomograms for more precise prediction of OS and CSS in patients with colon NENs to facilitate individualized clinical decisions.

Identification of a nomogram based on an 8-lncRNA signature as a novel diagnostic biomarker for childhood acute lymphoblastic leukemia

Childhood acute lymphoblastic leukemia (cALL) still represents a major cause of disease-related death in children. This study aimed to explore the prognostic value of long non-coding RNAs (lncRNAs) in cALL. We downloaded lncRNA expression profiles from the TARGET and GEO databases. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were applied to identify lncRNA-based signatures. We identified an eight-lncRNA signature (LINC00630, HDAC2-AS2, LINC01278, AL356599.1, AC114490.1, AL132639.3, FUT8.AS1, and TTC28.AS1), which separated the patients into two groups with significantly different overall survival rates. A nomogram based on the signature, BCR ABL1 status and white blood cell count at diagnosis was developed and showed good accuracy for predicting the 3-, 5- and 7-year survival probability of cALL patients. The C-index values of the nomogram in the training and internal validation set reached 0.8 (95% CI, 0.757 to 0.843) and 0.806 (95% CI, 0.728 to 0.884), respectively. The nomogram proposed in this study objectively and accurately predicted the prognosis of cALL. In vitro experiments suggested that LINC01278 promoted the proliferation of leukemic cells and inhibited leukemic cell apoptosis by targeting the inhibition of miR-500b-3p in cALL, and LINC01278 may be a biological target for the treatment of cALL in the future.

A Nomogram Predicting Progression Free Survival in Patients with Gastrointestinal Stromal Tumor Receiving Sunitinib: Incorporating Pre-Treatment and Post-Treatment Parameters

Simple Summary

Sunitinib has been approved as the second-line targeted treatment for gastrointestinal stromal tumor (GIST) after imatinib failure. It is thus necessary to effectively assess prognosis after sunitinib use. However, the current assessment remains insufficient for the contemporary period. We examined prognostic factors influencing progression-free survival. Furthermore, we constructed a prognostic nomogram model using these significant pre-treatment and post-treatment variables.

Abstract

The present study aimed to construct a prognostic nomogram incorporating pre-treatment and post-treatment factors to predict progression-free survival (PFS) after use of sunitinib in patients with metastatic gastrointestinal stromal tumors (GISTs) following imatinib intolerance or failure. From 2007 to 2018, 109 metastatic GIST patients receiving sunitinib at Chang Gung Memorial Hospital, Taiwan, were enrolled. A prognostic nomogram to predict PFS was developed. Sixty-three male and forty-six female metastatic GIST patients, with a median age of 61 years (range: 15–91 years), received sunitinib. The median PFS for 109 patients is 9.93 months. For pre-treatment factors, male gender, body mass index more than 18.5 kg/m², no sarcopenia status, higher lymphocyte count, lower platelet/lymphocyte ratio, good performance status, higher sunitinib dose, and non-liver metastasis were significantly associated with favorable PFS. For post-treatment factors, adverse events with hypertension, hand–foot skin reaction, and diarrhea were significantly associated with favorable PFS. However, only eight clinicopathological independent factors for PFS prediction were selected for prognostic nomogram establishment. The calibration curve for probability of PFS revealed good agreement between the nomogram prediction and actual observation. High risk patients will experience the lowest PFS. A prognostic nomogram integrating eight clinicopathological factors was constructed to assist prognostic prediction for individual patients with advanced GIST after sunitinib use.

Application-specific nuclear medicalin vivoimaging devices

Nuclear medical imaging devices, such as those enabling photon emission imaging (gamma camera, single photon emission computed tomography, or positron emission imaging), that are typically used in today's clinics are optimized for assessing large portions of the human body, and are classified as whole-body imaging systems. These systems have known limitations for organ imaging, therefore application-specific devices have been designed, constructed and evaluated. These devices, given their compact nature and superior technical characteristics, such as their higher detection sensitivity and spatial resolution for organ imaging compared to whole-body imaging systems, have shown promise for niche applications. Several of these devices have further been integrated with complementary anatomical imaging devices. The objectives of this review article are to (1) provide an overview of such application-specific nuclear imaging devices that were developed over the past two decades (in the twenty-first century), with emphasis on brain, cardiac, breast, and prostate imaging; and (2) discuss the rationale, advantages and challenges associated with the translation of these devices for routine clinical imaging. Finally, a perspective on the future prospects for application-specific devices is provided, which is that sustained effort is required both to overcome design limitations which impact their utility (where these exist) and to collect the data required to define their clinical value.

Prognostic Nomogram for Sorafenib Benefit in Hepatitis B Virus-Related Hepatocellular Carcinoma After Partial Hepatectomy

Background

Predicting the long-term prognosis of individuals who experienced sorafenib treatment following partial hepatectomy due to hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) is difficult. This work aims to create an effective prognostic nomogram for HBV related HCC patients who are receiving sorafenib treatment as adjuvant therapy after surgery.

Methods

A total of 233 HBV-related HCC patients treated with or without sorafenib following partial hepatectomy at the Eastern Hepatobiliary Surgery Hospital from 2008 to 2013 were matched with propensity score matching analysis. The optimal cut-off point of the overall survival (OS) factor level was determined by x-tile. The selection of indicators was based on clinical findings. The Cox regression model with an interaction term was employed for evaluating the predictive value. Using a multivariate Cox proportional hazards model, a nomogram was subsequently formulated to analyze 111 patients treated with sorafenib. The nomogram's discriminative ability and predictive accuracy were determined using the concordance index (C-index), calibration, and ROC curve.

Results

The matched sorafenib cohort of 111 patients and control cohort of 118 patients were analyzed. Subgroup analysis revealed that low GPC3, pERK, pAKT, serum AFP levels, without MVI, under 50 years old, male, TNM stage I/II and BCLC stage 0/A were significantly associated with a better OS in patients subjected to sorafenib treatment compared to those without sorafenib treatment after surgery. Multivariate analysis of the sorafenib cohort revealed GPC3, pERK, pAKT, serum AST, and BCLC stage as independent factors for OS, and all were included in the nomogram. The survival probability based on the calibration curve showed that the prediction of the nomogram was in good agreement with the actual observation. The C-index of the nomogram for predicting survival was 0.73(95% CI, 0.67-0.78). The area under the ROC curve (AUC) for the nomogram to predict the survival for 1, 3, and 5-year was 0.726, 0.816, and 0.823, respectively.

Conclusion

This proposed nomogram shows the potential to make a precise prediction regarding the prognosis of HBV-related HCC patients and may help to stratify patients for personalized therapy following partial hepatectomy.

Nomogram Predicting the Risk of Locoregional Recurrence After Mastectomy for Invasive Micropapillary Carcinoma of the Breast

BACKGROUND

The risk of locoregional recurrence (LRR) after mastectomy for breast invasive micropapillary carcinoma (IMPC) remains poorly defined. We aimed to construct an effective prognostic nomogram to estimate the individualized risk of LRR for providing accurate information for long-term follow-up.

PATIENTS AND METHODS

A total of 388 patients with breast IMPC were included in the current study. Based on the Cox regression and clinical significance, a nomogram with an online prediction version was created. This model was evaluated and internally validated by concordance index and calibration plot. Receiver operating characteristic curve and decision curve analysis were used to assess the discrimination and clinical utility, and Kaplan-Meier curves estimated the probability of LRR.

RESULTS

The variables (age, lymph node metastasis, hormone receptor status, lymphovascular invasion, histologic grade, and adjuvant radiotherapy) were included in the nomogram. This model was well-calibrated to predict the possibility of LRR and displayed favorable clinical utility; the concordance index was 0.86 (95% confidence interval, 0.81-0.91), which was higher than any single predictor. The area under the curve of the nomogram was 0.89, whereas that of the conventional staging system was 0.72. An online prognostic nomogram was built for convenient use. Kaplan-Meier curves showed that the nomogram had a better risk stratification than the conventional staging system.

CONCLUSIONS

The nomogram could accurately predict the individualized risk of LRR after mastectomy for breast IMPC. By identifying the risk stratification, this model is expected to assist clinicians and patients in improving long-term follow-up strategies.

Nomograms for Predicting Non-remission in Patients Who Underwent Bariatric Surgery: A Multicenter Retrospective Study in China

BACKGROUND

As a reflection of the increasing global incidence of obesity, there is a corresponding increase in the proportion of obese patients undergoing bariatric surgery. This study reviewed the factors and outcomes of patients who underwent bariatric surgical procedures and determined the relationships and developed a nomogram to calculate individualized patient risk.

METHODS

The nomogram was based on a retrospective study on 259 patients who underwent bariatric surgery at the Chengdu Third People's Hospital from June 2017 to June 2019. The predictive accuracy and discriminative ability of the nomogram were determined by the ROC curve and C-index, respectively. The results were validated using bootstrap resampling and a retrospective study on 121 patients operated on from May 2015 to May 2019 at the Tenth People's Hospital of Shanghai.

RESULTS

The predictors contained in the prediction nomogram included age, sex, surgical approach, hyperlipidemia, blood pressure (BP), hyperuricemia, body mass index (BMI), and waist circumference (WC). The 6-month model displayed good discrimination with a C-index of 0.765 (95% CI: 0.756 to 0.774) and good calibration. The 1-year model reached a C-index of 0.768 (95% CI, 0.759 to 0.777) in the training cohort.

CONCLUSIONS

The proposed nomogram resulted in more accurate non-remission prediction for patients with obesity after bariatric surgery and may provide a reference for the preoperative choice of surgical methods.

Nomogram for predicting the risk of bone metastasis in breast cancer: a SEER population-based study

Background

Bone is the most common metastasis site of breast cancer. The prognosis of bone metastasis is better than other distant metastases, but patients with skeletal related events (SREs) have a poor quality of life, high healthcare costs and low survival rates. This study aimed to establish an effective nomogram for predicting risk of bone metastasis of breast cancer.

Methods

The nomogram was built on 4,895 adult/female/primary invasive breast cancer patients with complete clinicopathologic information, captured by the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Five biological factors (age, grade, histologic type, surgery of breast lesions and subtypes) were assessed with logistic regression to predict the risk of bone metastases. The predictive accuracy and discriminative ability of the nomogram were determined by the Receiver Operating Characteristic (ROC) curves and the calibration plot. Results were validated on a separate 2,093 cohort using bootstrap resampling from 2010 to 2015 as an internal group and a retrospective study on 120 patients in the First Affiliated Hospital of China Medical University from 2010 to 2014 at the same situation as an external group.

Results

On multivariate logistic regression of the primary cohort, independent factors for bone metastases were age, grade, histologic type, surgery of breast lesions and subtypes, which were all selected into the nomogram. The calibration plot for probability of incidence showed good agreement between prediction by nomogram and two observations. The ROC curves presented a good statistical model for risk of bone metastasis, and the corresponding AUC value of the development group, internal validation group and external validation group were 0.678, 0.689 and 0.704 respectively.

Conclusions

The proposed nomogram resulted in more-accurate prognostic prediction for breast cancer patients with bone metastases.

Identification of a nomogram based on an 8-lncRNA signature as a novel diagnostic biomarker for head and neck squamous cell carcinoma

Long noncoding RNAs (lncRNAs) have been proposed as diagnostic or prognostic biomarkers of head and neck squamous carcinoma (HNSCC). The current study aimed to develop a lncRNA-based prognostic nomogram for HNSCC. LncRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. After the reannotation of lncRNAs, the differential analysis identified 253 significantly differentially expressed lncRNAs in training set TCGA-HNSC (n = 300). The prognostic value of each lncRNA was first estimated in univariate Cox analysis, and 41 lncRNAs with P < 0.05 were selected as seed lncRNAs for Cox LASSO regression, which identified 11 lncRNAs. Multivariate Cox analysis was used to establish an 8-lncRNA signature with prognostic value. Patients in the high-signature score group exhibited a significantly worse overall survival (OS) than those in the low-signature score group, and the area under the receiver operating characteristic (ROC) curve for 3-year survival was 0.74. Multivariable Cox regression analysis among the clinical characteristics and signature scores suggested that the signature is an independent prognostic factor. The internal validation cohort, external validation cohort, and 102 HNSCC specimens quantified by qRT-PCR successfully validate the robustness of our nomogram.

Inflammation Score System using Preoperative Inflammatory Markers to Predict Prognosis for Hepatocellular Carcinoma after Hepatectomy: A Cohort Study

Background: This study developed a novel inflammation score system to predict survival outcomes using preoperational inflammatory markers in hepatocellular carcinoma (HCC) after surgery.

Materials and Methods: An inflammation score system was developed using five preoperative inflammatory markers based on the clinical data of 455 HCC patients (training cohort) receiving radical resection in the Eastern Hepatobiliary Surgery Hospital. The system was validated using a cohort from a different hospital (external validation). Kaplan-Meier curves and log-rank test were used to compare the survival of patients with different inflammation scores. A nomogram including inflammation scores for survival prediction was created to exhibit the risk factors of overall survival (OS).

Results: The patients in the low-score group showed better OS and recurrence-free survival (RFS) in the training and external validation cohorts than those from the high-score group. Subgroup analysis showed that compared with patients in the training cohort from the high-score group, stage I (eighth TNM stage) patients in the low-score group exhibited better prognosis results, whereas the findings for Stage II and III patients were different. Multivariate Cox analysis revealed that high inflammation score is an independent risk factor of OS and RFS. The nomogram established using the inflammation score with the C-index value of 0.661 (95% confidence interval=0.624-0.698) revealed a good three- and five-year calibration curves.

Conclusions: The inflammation score system based on five preoperative inflammatory markers well predicted the survival of HCC patients after surgery, especially in those at the early stage (Stage I).

A Nomogram and a Risk Classification System Predicting the Cancer-Specific Survival of Patients With Initially-Diagnosed Osseous Spinal and Pelvic Tumors

STUDY DESIGN

Retrospective analysis.

OBJECTIVE

Our goal was to provide a predictive model and a risk classification system that predicts cancer-specific survival (CSS) from spinal and pelvic tumors.

SUMMARY OF BACKGROUND DATA

Primary bone tumors of the spinal and pelvic are rare, thus limiting the understanding of the manifestations and survival from these tumors. Nomograms are the graphical representation of mathematical relationships or laws that accurately predict individual survival.

METHODS

A total of 1033 patients with spinal and pelvic bone tumors between 2004 and 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate Cox analysis was used on the training set to select significant predictors to build a nomogram that predicted 3- and 5-year CSS. We validate the precision of the nomogram by discrimination and calibration, and the clinical value of nomogram was assessed by making use of a decision curve analyses (DCA).

RESULTS

Data from 1033 patients with initially-diagnosed spinal and pelvic tumors were extracted from the SEER database. Multivariate analysis of the training cohort, predictors included in the nomogram were age, pathological type, tumor stage, and surgery. The value of C-index was 0.711 and 0.743 for the internal and external validation sets, respectively, indicating good agreement with actual CSS. The internal and external calibration curves revealed good correlation of CSS between the actual observation and the nomogram. Then, the DCA showed greater net benefits than that of treat-all or treat-none at all time points. A novel risk grouping system was established for CSS that can readily divide all patients into three distinct risk groups.

CONCLUSION

The proposed nomogram obtained more precision prognostic prediction for patients with initially-diagnosed primary spinal and pelvic tumors.

LEVEL OF EVIDENCE

3.

Development and validation of a prognostic nomogram to predict overall survival and cancer-specific survival for patients with anaplastic thyroid carcinoma

Background

Anaplastic thyroid carcinoma (ATC) is a rare malignant tumor with a poor prognosis. However, there is no useful clinical prognostic predictive tool for ATC so far. Our study identified risk factors for survival of ATC and created a reliable nomogram to predict overall survival (OS) and cancer-specific survival (CSS) of patients with ATC.

Methods

A total of 1,404 cases of ATC diagnosed between 1983 and 2013 were extracted from on the Surveillance, Epidemiology and End Results database based on our inclusion criteria. OS and CSS were compared among patients between each variable by Kaplan-Meier methods. The Cox proportional hazards model was used to evaluate multiple prognostic factors and obtain independent predictors. All independent risk factors were included to build nomograms, whose accuracy and practicability were tested by concordance index (C-index), calibration curves, ROC curves, DCA, net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

Results

Historic stage, tumor size, surgery and radiotherapy were independent risk factors associated with ATC according to multivariate Cox regression analysis of OS. However, gender was also an important prognostic predictor in CSS besides the factors mentioned above. These characteristics were included in the nomograms predicting OS and CSS of patients with ATC. The nomograms predicting OS and CSS performed well with a C-index of 0.765 and 0.773. ROC curves, DCA, NRI and IDI suggested that the nomogram was superior to TNM staging and age.

Conclusion

The proposed nomogram is a reliable tool based on the prediction of OS and CSS for patients with ATC. Such a predictive tool can help to predict the survival of the patients.

Assessing Extraprostatic Extension with Multiparametric MRI of the Prostate: Mehralivand Extraprostatic Extension Grade or Extraprostatic Extension Likert Scale?

Purpose

To validate the MRI grading system proposed by Mehralivand et al in 2019 (the "extraprostatic extension [EPE] grade") in an independent cohort and to compare the Mehralivand EPE grading system with EPE interpretation on the basis of a five-point Likert score ("EPE Likert").

Materials and Methods

A total of 310 consecutive patients underwent multiparametric MRI according to a standardized institutional protocol before radical prostatectomy was performed by using the same 1.5-T MRI unit at a single institution between 2010 and 2012. Two radiologists blinded to clinical information assessed EPE according to standardized criteria. On the basis of the readings performed until 2017, the diagnostic performance of EPE Likert and Mehralivand EPE score were compared using receiver operating characteristics (ROC) and decision curve methodology against histologic EPE as standard of reference. Prediction of biochemical recurrence-free survival (BRFS) was assessed by Kaplan-Meier analysis and log rank test.

Results

Of the 310 patients, 80 patients (26%) had EPE, including 33 with radial distance 1.1 mm or greater. Interrater reliability was fair (weighted κ 0.47 and 0.45) for both EPE grade and EPE Likert. Sensitivity for identifying EPE using EPE grade versus EPE Likert was 0.83 versus 0.86 and 0.86 versus 0.91 for radiologist 1 and 2, respectively. Specificity was 0.48 versus 0.58 and 0.39 versus 0.70 (P < .05 for radiologist 2). There were no significant differences in the ROC area under the curve or on decision curve analysis. Both EPE grade and EPE Likert were significant predictors of BRFS.

Conclusion

Mehralivand EPE grade and EPE Likert have equivalent diagnostic performance for predicting EPE and BRFS with a similar degree of observer dependence.© RSNA, 2020Keywords: MR-Imaging, Neoplasms-Primary, Observer Performance, Outcomes Analysis, Prostate, StagingSupplemental material is available for this article.See also the commentary by Choyke in this issue.

The Role of Magnetic Resonance Spectroscopy in Evaluating the Rate of Brain Metabolic Variations in Chemical Veterans with Respiratory Problem In Comparison To Control Group

BACKGROUND

During the eight years of the imposed war, Iraq used various chemical agents such as sulfur mustard and nerve agents (mainly tabun and sometimes soman) on Iran's soldiers. Using information obtained from specialist sequences and analysing information obtained from magnetic resonance imaging (MRI) in a susceptibility weighted imaging (SWI) sequence and magnetic resonance spectroscopy (MRS) provides valuable information on continuation of treatment and identifying functional disorders.

AIM

The objective of this research was to evaluate the rate of metabolic variations in chemically injured veterans based on chemical neuromarkers using the chemical sequence MRS, which would help patients and physicians in terms of time, economics, and selection of appropriate therapeutic methods, so if the can physician can get complete information about the metabolic properties of the brain through paraclinical (especially MRI) tools before treatment, he might change his treatment program to reduce the complications caused by it.

METHODOLOGY

In this research, 40 chemically injured veterans with brain dysfunction admitted to the screening centre for MRI with specialized MRS sequence participated. Accordingly, we examined the rate of brain metabolic variations about the level of neuromarkers and evaluated the relationship between the level of neuromarkers and brain damages.

RESULTS

The results of this research revealed that while the demographic characteristics such as age of the two groups of chemically injured veterans and control was similar, only the median of the NAA/Cr (N-acetylaspartate to creatine ratio) ratio in PONS of chemically injured patients was significantly lower than that of the control group, and this ratio was similar in other parts of the brain in two groups. The results also showed that the ratio of NAA to total choline and Cr was similar in all parts of the brain in two groups.

CONCLUSION

Based on the research results, using the MR (Magnetic Resonance) spectroscopy device and determination of the value and ratio of markers such as creatinine and N-acetylaspartate and choline, the brain injuries of chemically injured veterans can be examined. By conducting further studies and larger sample size, the brain damages in veterans can be diagnosed early, which would be a great contribution in their treatment.

Targets missed: predictors of MRI-targeted biopsy failing to accurately localize prostate cancer found on systematic biopsy

BACKGROUND

Magnetic resonance imaging (MRI)/ultrasound (US) fusion-guided biopsy has improved the ability to localize and detect prostate cancer (PCa) with efficiency surpassing systematic biopsy. Nevertheless, some patients have PCa missed using the MRI-targeted biopsy sampling alone. We aim to identify clinical and imaging parameters associated with cases where targeted biopsy did not detect PCa compared to systematic biopsy.

METHODS

We conducted a retrospective review of patients who underwent MRI/US fusion-guided biopsy in addition to concurrent systematic, extended-sextant biopsy between 2014 and 2017. For patients with PCa detected on systematic biopsy not properly localized by MRI/US fusion-guided biopsy, the sextant distance from MRI-targeted lesion to the cancer-positive sextant was calculated and parameters potentially predicting this targeting miss were evaluated.

RESULTS

In all, 35/127 (27.6%) patients with single-session MRI/US fusion-guided biopsy plus standard biopsy finding PCa had lesions incorrectly localized. Of these, 15/35 (42.9%) were identified as possible fusion-software misregistrations. The remainder, 12/35 (34.3%), represented targeted biopsies one sextant away from the cancer focus and 8/35 (22.9%) targeted biopsies two sextants away from the cancer focus. Only 7/35 (20.0%) patients were determined to have clinically significant PCa, which represents 7/127 (5.5%) of the overall population. Lower MRI lesion volumes (p = 0.022), lesion density (p < 0.001), and PI-RADS scores (p < 0.001) were significantly associated with targeted biopsy missing PCa detected on systematic biopsy.

CONCLUSION

Clinically significant PCa is rarely missed utilizing MRI/US fusion-guided biopsy. With the majority of missed tumors representing targeting misregistrations or cases of low-grade cancer in sextants immediately adjacent to MRI suspicious lesions. Lower MRI lesion volumes, lesion density, and PI-RADS are predictors of cases with targeted biopsies missing cancer, for which systematic sampling of the sextants containing MRI targets and adjacent sextants would most optimize PCa detection.

Added Value of Multiparametric Magnetic Resonance Imaging to Clinical Nomograms for Predicting Adverse Pathology in Prostate Cancer

PURPOSE

We examined the additional value of preoperative prostate multiparametric magnetic resonance imaging and transrectal ultrasound/multiparametric magnetic resonance imaging fusion guided targeted biopsy when performed in combination with clinical nomograms to predict adverse pathology at radical prostatectomy.

MATERIALS AND METHODS

We identified all patients who underwent 3 Tesla multiparametric magnetic resonance imaging prior to fusion biopsy and radical prostatectomy. The Partin and the MSKCC (Memorial Sloan Kettering Cancer Center) preradical prostatectomy nomograms were applied to estimate the probability of organ confined disease, extraprostatic extension, seminal vesicle invasion and lymph node involvement using transrectal ultrasound guided systematic biopsy and transrectal ultrasound/multiparametric magnetic resonance imaging fusion guided targeted biopsy Gleason scores. With radical prostatectomy pathology as the gold standard we developed multivariable logistic regression models based on these nomograms before and after adding multiparametric magnetic resonance imaging to assess any additional predictive ability.

RESULTS

A total of 532 patients were included in study. When multiparametric magnetic resonance imaging findings were added to the systematic biopsy based MSKCC nomogram, the AUC increased by 0.10 for organ confined disease (p <0.001), 0.10 for extraprostatic extension (p = 0.003), 0.09 for seminal vesicle invasion (p = 0.011) and 0.06 for lymph node involvement (p = 0.120). Using Gleason scores derived from targeted biopsy compared to systematic biopsy provided an additional predictive value of organ confined disease (Δ AUC 0.07, p = 0.003) and extraprostatic extension (Δ AUC 0.07, p = 0.048) at radical prostatectomy with the MSKCC nomogram. Similar results were obtained using the Partin nomogram.

CONCLUSIONS

Magnetic resonance imaging alone or in addition to standard clinical nomograms provides significant additional predictive ability of adverse pathology at the time of radical prostatectomy. This information can be greatly beneficial to urologists for preoperative planning and for counseling patients regarding the risks of future therapy.

One-Stop-Shop Whole-Body 68Ga-PSMA-11 PET/MRI Compared with Clinical Nomograms for Preoperative T and N Staging of High-Risk Prostate Cancer

Our aim was to assess the diagnostic potential of 1-stop-shop prostate-specific membrane antigen ligand (⁶⁸Ga-PSMA-11) PET/MRI compared with preoperative staging nomograms in patients with high-risk prostate cancer. Methods: A total of 102 patients underwent ⁶⁸Ga-PSMA-11 PET/MRI before intended radical prostatectomy with lymph node dissection. Preoperative variables determined the probabilities for lymph node metastases (LNM), extracapsular extension (ECE), and seminal vesical involvement (SVI) using the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram and Partin tables. Receiver-operating-characteristic analyses were performed to determine best discriminatory cutoffs. On a cohort basis, positivity rates of imaging and nomograms were compared with pathologic prevalence. On a patient basis, sensitivity, specificity, and area under the curves were calculated. Finally, the full concordance of each method to postoperative T and N stage was determined. Results: Seventy-three patients were finally analyzed. On a cohort basis, the MSKCC nomogram (39.7%) positivity rate was most concordant with pathologic prevalence for LNM (34.3%) compared with Partin tables (14.1%) and imaging (20.6%). Prevalence of ECE (72.6%) was best predicted by MSKCC nomograms and imaging (83.6% each), compared with Partin tables (38.4%). For prevalence of SVI (45.2%), imaging (47.9%) performed superior to MSKCC (37.6%) and Partin tables (19.3%). On a patient basis, AUCs for LNM, ECE, and SVI did not differ significantly between tests (P > 0.05). Imaging revealed a high specificity (100%) for LNM and a sensitivity (60%) comparable to the MSKCC nomogram (68%) and Partin tables (60%). For ECE, imaging revealed the highest sensitivity (94.3%) compared with the MSKCC nomogram (66%) and Partin tables (71.1%). For SVI, sensitivity and specificity of imaging and the MSKCC nomogram were comparable (81.5% and 80% vs. 87.9% and 75%). The rate of concordance to the final pTN stage was 60.3% for imaging, 52.1% for the MSKCC nomogram, and 39.7% for Partin tables. Conclusion: In our analysis, preoperative 1-stop-shop ⁶⁸Ga-PSMA-11 PET/MRI performs at least equally for T and N stage prediction compared with nomograms in high-risk prostate cancer patients. Despite an improved prediction of the full final stage and the yield of additional anatomic information, the use of ⁶⁸Ga-PSMA-11 PET/MRI warrants further prospective evaluation.

Establishment and validation of a predictive nomogram model for non-small cell lung cancer patients with chronic hepatitis B viral infection

Background

This study aimed to establish an effective predictive nomogram for non-small cell lung cancer (NSCLC) patients with chronic hepatitis B viral (HBV) infection.

Methods

The nomogram was based on a retrospective study of 230 NSCLC patients with chronic HBV infection. The predictive accuracy and discriminative ability of the nomogram were determined by a concordance index (C-index), calibration plot and decision curve analysis and were compared with the current tumor, node, and metastasis (TNM) staging system.

Results

Independent factors derived from Kaplan–Meier analysis of the primary cohort to predict overall survival (OS) were all assembled into a Cox proportional hazards regression model to build the nomogram model. The final model included age, tumor size, TNM stage, treatment, apolipoprotein A-I, apolipoprotein B, glutamyl transpeptidase and lactate dehydrogenase. The calibration curve for the probability of OS showed that the nomogram-based predictions were in good agreement with the actual observations. The C-index of the model for predicting OS had a superior discrimination power compared with the TNM staging system [0.780 (95% CI 0.733–0.827) vs. 0.693 (95% CI 0.640–0.746), P < 0.01], and the decision curve analyses showed that the nomogram model had a higher overall net benefit than did the TNM stage. Based on the total prognostic scores (TPS) of the nomogram, we further subdivided the study cohort into three groups: low risk (TPS ≤ 13.5), intermediate risk (13.5 < TPS ≤ 20.0) and high risk (TPS > 20.0).

Conclusion

The proposed nomogram model resulted in more accurate prognostic prediction for NSCLC patients with chronic HBV infection.

Incidental findings on multiparametric MRI performed for evaluation of prostate cancer

PURPOSE

Multiparametric magnetic resonance imaging (mp-MRI) and MRI/Ultrasound (US) fusion-guided biopsy are relatively new techniques for improved detection, staging, and active surveillance of prostate cancer (PCa). As with all imaging modalities, MRI reveals incidental findings (IFs) which carry the risk of increased cost, patient anxiety, and iatrogenic morbidity due to workup of IFs. Herein, we report the IFs from 684 MRIs for evaluation of PCa and consider their characteristics and clinical significance.

METHODS

Patients underwent mp-MRI prostate protocol incorporating triplanar T2-weighted, diffusion-weighted, and dynamic contrast-enhanced pelvic MRI as well as a post-contrast abdominopelvic MRI with the primary indication of detection or evaluation of PCa. A total of 684 consecutive prostate MRI reports performed in a series of 580 patients were reviewed. All extraprostatic findings reported were logged and then categorized by organ system and potential clinical significance.

RESULTS

There were 349 true IFs found in 233 (40%) of the 580 patients. One hundred nineteen additional extraprostatic findings were unsuspected but directly related to PCa staging, while the 349 IFs were unrelated and thus truly incidental beyond study indication. While the majority of true IFs were non-urologic, only 6.6% of IFs were considered clinically significant, non-urologic findings, and more than a third of MRI reports had urologic IFs not related to PCa.

CONCLUSIONS

Rates of incidental findings on prostate indication MRI are similar to other abdominopelvic imaging studies. However, only 6.6% of the IFs were considered to be clinically significant non-urologic findings. Further investigations are needed to assess downstream workup of these IFs and resulting costs.

Comparison of Endorectal Magnetic Resonance Imaging, Clinical Prognostic Factors and Nomograms in the Local Staging of Prostate Cancer Patients Treated with Radiotherapy

Aims and background

To determine retrospectively the role of endorectal magnetic resonance in the staging of prostate cancer. The aim of the study was to assess whether it is possible to identify a group of patients with prostate cancer, chosen for certain prognostic factors, eligible for radiotherapy that could take advantage of endorectal magnetic resonance in staging and therapy management.

Methods

Between January 2002 and December 2005, 143 patients with biopsy proven prostate cancer underwent endorectal magnetic resonance. All patients were initially evaluated considering the following prognostic factors: serum prostate-specific antigen at diagnosis, Gleason score, histological grade, involvement of the seminal vesicle and extracapsular extension using the Roach III and ECE equations. The findings were then compared to the results of endorectal magnetic resonance.

Results

The relationship between the variable post-endorectal magnetic resonance stage modification and Gleason score was statistically significant (P = 0.02847). In addition, our study showed a statistically significant correlation between the risk of seminal vesicle involvement according to the Roach III formula and post-endorectal magnetic resonance stage modification (P = 0.01305). Conversely, statistical analysis showed no significant correlation between post-endorectal magnetic resonance stage modification and prostate-specific antigen values (P = 0.83440) or between post-endorectal magnetic resonance stage modification and the risk of extracapsular extension according to the extracapsular extension formula (P = 0.42748).

Conclusions

Our data suggest that endorectal magnetic resonance could be used for staging of the subgroup of patients at high risk of seminal vesicle involvement (>15%). Although we found a statistical correlation between Gleason score and post-endorectal magnetic resonance stage modification, statistical analysis showed no correlation between any of the subgroups. Therefore, it is not possible at the moment to identify a subgroup of patients by Gleason score that may benefit from endorectal magnetic resonance. In our opinion, extracapsular extension values were not useful to select patients for endorectal magnetic resonance.

The efficacy and utilisation of preoperative multiparametric magnetic resonance imaging in robot-assisted radical prostatectomy: does it change the surgical dissection plan?

Objective

We investigated the effect of the use of multiparametric prostate magnetic resonance imaging (mp-MRI) on the dissection plan of the neurovascular bundle and the oncological results of our patients who underwent robot-assisted radical prostatectomy.

Material and methods

We prospectively evaluated 60 consecutive patients, including 30 patients who had (Group 1), and 30 patients who had not (Group 2) mp-MRI before robot-assisted radical prostatectomy. Based on the findings of mp-MRI, the dissection plan was changed as intrafascial, interfascial, and extrafascial in the mp-MRI group. Two groups were compared in terms of age, prostate-specific antigen (PSA), Gleason sum scores and surgical margin positivity.

Results

There was no statistically significant difference between the two groups in terms of age, PSA, biopsy Gleason score, final pathological Gleason score and surgical margin positivity. mp-MRI changed the initial surgical plan in 18 of 30 patients (60%) in Group 1. In seventeen of these patients (56%) surgical plan was changed from non-nerve sparing to interfascial nerve sparing plan. In one patient dissection plan was changed to non-nerve sparing technique which had extraprostatic extension on final pathology. Surgical margin positivity was similar in Groups 1, and 2 (16% and 13%, respectively) although, Group 1 had higher number of high- risk patients. mp-MRI confirmed the primary tumour localisation in the final pathology in 27 of of 30 patients (90%).

Conclusion

Preoperative mp-MRI effected the decision to perform a nerve-sparing technique in 56% of the patients in our study; moreover, changing the dissection plan from non-nerve-sparing technique to a nerve sparing technique did not increase the rate of surgical margin positivity.

A novel tool for predicting extracapsular extension during graded partial nerve sparing in radical prostatectomy

OBJECTIVES

To create a statistical tool for the estimation of extracapsular extension (ECE) level of prostate cancer and determine the nerve-sparing (NS) approach that can be safely performed during radical prostatectomy (RP).

PATIENTS AND METHODS

A total of 11 794 lobes, from 6 360 patients who underwent robot-assisted RP between 2008 and 2016 were evaluated. Clinicopathological features were included in a statistical algorithm for the prediction of the maximum ECE width. Five multivariable logistic models were estimated for: presence of ECE and ECE width of >1, >2, >3, and >4 mm. A five-zone decision rule based on a lower and upper threshold is proposed. Using a graphical interface, surgeons can view patient's pre-treatment characteristics and a curve showing the estimated probabilities for ECE amount together with the areas identified by the decision rule.

RESULTS

Of the 6 360 patients, 1 803 (28.4%) were affected by non-organ-confined disease. ECE was present in 1 351 lobes (11.4%) and extended beyond the capsule for >1, >2, >3, and >4 mm in 498 (4.2%), 261 (2.2%), 148 (1.3%), 99 (0.8%) cases, respectively. ECE width was up to 15 mm (interquartile range 1.00-2.00). The five logistic models showed good predictive performance, the area under the receiver operating characteristic curve was: 0.81 for ECE, and 0.84, 0.85, 0.88, and 0.90 for ECE width of >1, >2, >3, and >4 mm, respectively.

CONCLUSION

This novel tool predicts with good accuracy the presence and amount of ECE. Furthermore, the graphical interface available at www.prece.it can support surgeons in patient counselling and preoperative planning.

[Imaging of locally advanced prostate cancer : Importance of ultrasound and especially MRI]

Prostate cancer is the most common male malignant tumor in Germany, which thus places growing demands on differentiated imaging and risk-adapted therapeutic approaches. Multiparametric MRI (mpMRI) of the prostate enables reliable detection of clinically significant cancers and is currently the leading imaging modality for the detection, characterization, and local staging of prostate cancer. According to the German S3 guideline, mpMRI of the prostate is currently primarily recommended in patients with previous negative TRUS biopsies and persisting tumor suspicion. The serial use of mpMRI in the pretherapeutic setting can support individual therapy planning of patients with locally advanced prostate cancer in the near future.

Nomograms predicting disease-specific regional recurrence and distant recurrence of papillary thyroid carcinoma following partial or total thyroidectomy

The study aimed to establish effective nomograms for prediction of tumor regional recurrence and distant recurrence of papillary thyroid carcinoma (PTC) patients after partial or total thyroidectomy.These nomograms were based on a retrospective study on 1034 patients who underwent partial or total thyroidectomy for PTC. The predictive accuracy and discriminative ability of the nomograms were evaluated by the concordance index (C-index) and calibration curve. In addition, a validation cohort was included at the same institution.Multivariate analysis demonstrated that family history, maximal tumor diameter, capsular invasion, and lymph node staging were independent risk factors for regional recurrence-free survival; and family history, histological variants, capsular invasion, perineuronal invasion, and vascular invasion were independent risk factors for distant recurrence-free survival. They were selected into the 2 nomograms, respectively, and the C-index for regional recurrence-free survival and distant recurrence-free survival prediction were 0.72 and 0.83, respectively. In the validation cohort, the 2 nomograms displayed a C-index of 0.72 and 0.89, respectively.The nomograms developed in this study demonstrated their discrimination capability for predicting 3 and 5-year regional recurrence and distant recurrence after partial or total thyroidectomy, and can be used to identify high-risk patients.

Integration of MRI to clinical nomogram for predicting pathological stage before radical prostatectomy

BACKGROUND

Debate persists regarding whether MRI should be used routinely for preoperative evaluation of prostate cancer.

OBJECTIVE

The aim is to assess the role of prostatic magnetic resonance imaging (MRI) and other preoperative data in extra-prostatic extension (EPE) evaluation.

PATIENTS AND METHODS

From 2000 to 2013, 1743 patients operated for radical prostatectomy had a preoperative MRI. Age, clinical stage with digital rectal exam (DRE), PSA, prostate weight, biopsy, MRI and pathological findings of the surgical specimen were noticed. A multiparametric score of the variables independently associated with EPE was built with or without MRI on a random sample test population and internally validated.

RESULTS

With mean age of 62.9 years and mean PSA of 9.6 ng/ml, the population was distributed as follows: 1424 DRE T1, 254 T2, 32 T3; on biopsy 990 Gleason score = 6 and 717 ≥ 7; on MRI 1322 iT2, 290 iT3A and 131 iT3B; on prostatectomy 15 pT0, 998 pT2, 548 pT3A, 181 pT3B and 1 pT4A. In multivariate analysis, DRE, PSA, Gleason score, prostate weight and MRI were independently associated with EPE and integrated in a score with an area under curve (AUC) of 0.74 [95% CI 0.71-0.77] (0.72 without MRI, p < 0.01) a positive predictive value of 61% and a negative predictive value of 74%, internally validated. The Hosmer-Lemeshow goodness-of-fit test showed good accuracy (p = 0.77).

CONCLUSIONS

Integration of MRI with clinical data for predicting pathological stage before radical prostatectomy permits to exclude accurately EPE in 74% of cases.

Incremental value of high b value diffusion-weighted magnetic resonance imaging at 3-T for prediction of extracapsular extension in patients with prostate cancer: preliminary experience

PURPOSE

To investigate whether high b value diffusion-weighted imaging (DWI) contributes to the improvement of diagnostic ability of extracapsular extension (ECE) in prostate cancer (PC).

MATERIALS AND METHODS

Forty-three patients with PC underwent multiparametric MRI including DWI (b values: 0, 2000 s/mm²) at 3-T. Two radiologists assessed the presence of ECE and the diagnostic certainty degree using conventional diagnostic method by consensus. Tumor apparent diffusion coefficient (ADC, ×10^-3 mm²/s) was also measured. Independent predictors of ECE were identified among PSA, tumor ADC, Gleason score, and conventional MRI. ECE in patients with low diagnostic certainty by conventional MRI was further reevaluated using ADC cutoff value, and the results were combined with those of patients with high diagnostic certainty by conventional MRI (MRI + ADC method).

RESULTS

Tumor ADC was an independent predictor of ECE, and the ADC cutoff value was 0.72. The sensitivity, specificity, and accuracy of conventional MRI and MRI + ADC method in the diagnosis of ECE were 44, 92, and 72%, and 78, 96, and 88%, respectively. Among MRI findings leading to the judgement of low diagnostic certainty, broad tumor contact was most common (72% of the patients).

CONCLUSIONS

The addition of ADC obtained with high b value DWI at 3-T to conventional MRI improved the diagnostic ability of ECE.

MR Imaging of the Prostate Gland

This article discusses MR imaging of the normal prostate and of disease conditions of the prostate including prostatitis, cystic lesions, amyloidosis, calculi, hematospermia, benign prostatic hyperplasia, and malignancy.

Accuracy of Multiparametric Magnetic Resonance Imaging for Extracapsular Extension of Prostate Cancer in Community Practice

INTRODUCTION

The presence of extracapsular extension (ECE) in prostate cancer (PCa) can influence a surgeon's decision to perform a nerve-sparing approach during radical prostatectomy (RP). Preoperatively, multiparametric MRI (mp-MRI) is often used to stage PCa. More recently, the use of mp-MRI has gained wide acceptance in fusion biopsy of the prostate. In this framework, the reported accuracy of mp-MRI has been highly variable, with data often originating from large referral centers with experienced radiologists. We sought to determine the sensitivity and specificity of mp-MRI for detecting ECE in the community.

MATERIALS AND METHODS

We reviewed a prospectively maintained database of men with PCa who had undergone RP. We recorded the prevalence of ECE at RP and determined the sensitivity, specificity, positive predictive value, and negative predictive value of MRI for detecting ECE. We assessed these values according to the D'Amico risk groups and compared the predictive value of MRI to that of the Partin tables.

RESULTS

The prevalence of ECE was 11.5%, 28.1%, and 47.1% in the low-, intermediate, and high-risk groups, respectively, with an overall prevalence of 24.1%. The overall sensitivity, specificity, positive predictive value, and negative predictive value of MRI was 12.5%, 93.1%, 36.4%, and 77.0%, respectively.

CONCLUSION

The reduction in the sensitivity of preoperative mp-MRI to determine ECE in the community setting is significant. Even with stratification using the D'Amico criteria and Partin tables, the performance of mp-MRI was not significantly improved. Because most cases of PCa are diagnosed and treated in the community, it is questionable whether mp-MRI is a suitable staging modality in the community.

Role of Multi-Parametric Magnetic Resonance Image and PIRADS Score in Patients with Prostate Cancer Eligible for Active Surveillance According PRIAS Criteria

OBJECTIVE

To evaluate the prognostic role of multiparametric-MRI (mp-MRI) in patients with clinically localized prostate cancer (PCa) eligible for active surveillance (AS) according to Prostate Cancer Research International: Active Surveillance (PRIAS) criteria.

PATIENTS AND METHODS

We analyzed prospectively 73 patients with PCa and PRIAS criteria for low-risk disease. All patients fitted criteria for AS but optioned surgery treatment. The mp-MRI was performed to define the likelihood of malignancy according to the Prostate Imaging Reporting and Data System (PIRADS) score (1-5). Patients were divided in 2 groups: non-visible cancer lesion on MRI (PIRADS 2-3) and visible cancer (PIRADS 4-5). Preoperative clinical data (age, body mass index, prostate specific antigen (PSA) level, positive core biopsy, PSA density (PSAD)) and definitive pathological findings (staging, upgrading, unfavorable disease) were compared between groups. PIRADS score was correlated with pathological data to evaluate the prognostic role of mp-MRI; and preoperative variables and definitive pathology (upgrading, upstaging and unfavorable disease) were also assessed.

RESULTS

PSAD (p = 0.04) and pathological stage (p = 0.03) were significantly associated with the presence of visible disease. Visible disease was significantly associated with upstaging (p = 0.03). Correlation between PIRADS 5 and unfavorable disease was statistically significant (p = 0.02). The mp-MRI had adequate sensibility in detecting upstaging (92%), intermediate for upgrading (76%) and unfavorable disease (76%). Negative predictive value was higher for upstaging than for upgrading or unfavorable disease (96 vs. 68% and 64%). Multivariate logistic regression revealed that PIRADS 5 was a significant predictor of upstaging (p = 0.05, OR 16.12) and unfavorable disease (p = 0.01, OR 6.53).

CONCLUSION

A visible lesion on mp-MRI strongly predicts significant PCa in patients eligible for AS according to PRIAS criteria, based on upstaging and unfavorable disease. We believe that mp-MRI is an important tool and should be added to clinical selection criteria for AS.

Prostate cancer risk stratification with magnetic resonance imaging

In recent years, multiparametric magnetic resonance imaging (mpMRI) has shown promise for prostate cancer (PCa) risk stratification. mpMRI, often followed by targeted biopsy, can be used to confirm low-grade disease before enrollment in active surveillance. In patients with intermediate or high-risk PCa, mpMRI can be used to inform surgical management. mpMRI has sensitivity of 44% to 87% for detection of clinically significant PCa and negative predictive value of 63% to 98% for exclusion of significant disease. In addition to tumor identification, mpMRI has also been shown to contribute significant incremental value to currently used clinical nomograms for predicting extraprostatic extension. In combination with conventional clinical criteria, accuracy of mpMRI for prediction of extraprostatic extension ranges from 92% to 94%, significantly higher than that achieved with clinical criteria alone. Supplemental sequences, such as diffusion-weighted imaging and dynamic contrast-enhanced imaging, allow quantitative evaluation of cancer-suspicious regions. Apparent diffusion coefficient appears to be an independent predictor of PCa aggressiveness. Addition of apparent diffusion coefficient to Epstein criteria may improve sensitivity for detection of significant PCa by as much as 16%. Limitations of mpMRI include variability in reporting, underestimation of PCa volume and failure to detect clinically significant disease in a small but significant number of cases.

Impact of multiparametric magnetic resonance imaging on risk group assessment of patients with prostate cancer addressed to external beam radiation therapy

PURPOSE

To investigate the impact of multiparametric magnetic resonance imaging (mpMRI) on risk group assessment of patients with prostate cancer (PCa) initially addressed to external beam radiation therapy (EBRT).

MATERIALS AND METHODS

We prospectively performed mpMRI (3.0Tsystem) in 44 patients addressed to EBRT, using a multiparametric protocol (high-resolution multiplanar T2-weighted, diffusion-weighted and dynamic contrast-enhanced imaging). Risk group was assessed in accordance with the National comprehensive cancer network (NCCN) categories, by combining prostate-specific-antigen level, Gleason score and the T-stage as established by digital rectal examination (clinical risk assessment; c-RA) versus mpMRI (mpMRI-risk assessment; mpMRI-RA). The agreement between c-RA and mpMRI-RA was investigated using Cohen's kappa.

RESULTS

Patients were included in very low/low risk, intermediate risk, high risk, very high risk and metastatic NCCN categories in 10 (22.7%), 18 (40.9%), 15 (34.1%), 1 (2.3%) and 0 cases using c-RA vs. 8 (18.2%), 14 (31.8%), 14 (31.8%), 4 (9.1%) and 4 (9.1%) cases using mpMRI-RA, respectively, with only moderate agreement (k=0.43). mpMRI-RA determined risk downgrading in 2/44 patients (4.5%), and risk upgrading in 16/44 patients (36.3%). After mpMRI, EBRT remained indicated in all patients.

CONCLUSION

mpMRI changed clinical risk stratification in about 41% of patients with PCa, with potential impact on EBRT planning.

Nonvisible tumors on multiparametric magnetic resonance imaging does not predict low-risk prostate cancer

Purpose

To determine whether multiparametric MRI could help predict the diagnosis of low-risk prostate cancer (PCA).

Methods

We retrospectively analyzed consecutive 623 patients with PCA who underwent multiparametric MRI before radical prostatectomy(RP). High-resolution T1- and T2-weighted, diffusion-weighted, and dynamic precontrast and postcontrast image sequences were obtained for each patient. Of the 623 patients, 177(28.4%) exhibited non visible tumors on MRI of clinical stage T1c. The imaging results were compared with the pathological findings with respect to both stage and Gleason scores (GS).

Results

Of the 177 prostatectomy patients with non visible tumors on MRI, pathological findings resulted in the upgrading of 49(27.7%) patients to a sum of GS 7 or more. 101(57.1%) patients exhibited tumor volumes greater than 0.5cc. The biochemical recurrence rate was significantly higher in the pathological upgraded group compared with the nonupgraded group after a mean follow-up time of 29 months. In the multiple logistic analysis, non visible tumor on MRI was not a significant predictor of low-risk PCA.

Conclusions

Even though cancer foci were not visualized by postbiopsy MRI, the pathological tumor volumes and extent of GS upgrading were relatively high. Therefore, nonvisible tumors by multiparametric MRI do not appear to be predictive of low-risk PCA.

Nomogram for Predicting Time to Death After Withdrawal of Life-Sustaining Treatment in Patients With Devastating Neurological Injury

Reliable prediction of time of death after withdrawal of life-sustaining treatment in patients with devastating neurological injury is crucial to successful donation after cardiac death. Herein, we conducted a study of 419 neurocritical patients who underwent life support withdrawal at four neurosurgical centers in China. Based on a retrospective cohort, we used multivariate Cox regression analysis to identify prognostic factors for patient death, which were then integrated into a nomogram. The model was calibrated and validated using data from an external retrospective cohort and a prospective cohort. We identified 10 variables that were incorporated into a nomogram. The C-indexes for predicting the 60-min death probability in the training, external validation and prospective validation cohorts were 0.96 (0.93-0.98), 0.94 (0.91-0.97), and 0.99 (0.97-1.00), respectively. The calibration plots after WLST showed an optimal agreement between the prediction of time to death by the nomogram and the actual observation for all cohorts. Then we identified 22, 26 and 37 as cut-points for risk stratification into four groups. Kaplan-Meier curves indicated distinct prognoses between patients in the different risk groups (p < 0.001). In conclusion, we have developed and validated a nomogram to accurately identify potential cardiac death donors in neurocritical patients in a Chinese population.