The prevalence and locations of bone metastases using whole-body MRI in treatment-naïve intermediate- and high-risk prostate cancer

Potential biomarkers for the early detection of bone metastases

The clinical manifestations of bone metastases are diversified while many sites remain asymptomatic at early stage. As the early diagnosis method is not perfect and the early symptoms of tumor bone metastasis are not typical, bone metastasis is not easy to be detected. Therefore, the search for bone metastasis-related markers is effective for timely detection of tumor bone metastases and the development of drugs to inhibit bone metastases. As a result, bone metastases can only be diagnosed when symptoms are found, increasing the risk of developing skeletal-related event (SREs), which significantly impairs the patient's quality of life. Therefore, the early diagnosis of bone metastases is of great importance for the treatment and prognosis of cancer patients. Changes of bone metabolism indexes appear earlier in bone metastases, but the traditional biochemical indexes of bone metabolism lack of specificity and could be interfered by many factors, which limits their application in the study of bone metastases. Some new biomarkers of bone metastases have good diagnostic value, such as proteins, ncRNAs, circulating tumor cells (CTCs). Therefore, this study mainly reviewed the initial diagnostic biomarkers of bone metastases which were expected to provide references for the early detection of bone metastases.

Management of bone metastasis in prostate cancer

Progression of bone metastases is the primary cause of death in prostate cancer, and skeletal-related events (SREs), including pathologic fractures, spinal cord compression, radiation, or surgery to bone can impair patients' quality of life. Over the past decade, the development of cytotoxic agents, androgen-receptor-axis-targeted therapies (ARATs), and radioligand therapies has prolonged overall survival of prostate cancer patients with bone metastases and reduced the risk of SREs. The use of bone-modifying agents has also contributed to the reduced risk of SREs. Initial use of a cytotoxic agent, docetaxel, or an ARAT agent with androgen deprivation therapy (ADT) is the current approach to metastatic castration-sensitive prostate cancer. However, there is no consensus on the optimal medication for upfront use in combination with ADT, or on specific patient selection. Recently, next-generation imaging modalities, such as whole-body magnetic resonance imaging and prostate-specific membrane antigen-positron emission tomography have been utilized to detect bone metastases at an early stage. In addition, metastasis-directed therapy, such as stereotactic body radiation therapy, has been attempted. In the future, patients with bone metastatic prostate cancer will be divided into subgroups and their treatment options will be tailored to their specific characteristics.

Analysis of interreader agreement in structured reports of pelvic multiparametric magnetic resonance imaging using the METastasis Reporting and Data System for Prostate Cancer guidelines

PURPOSE

To evaluate interreader agreement on pelvic multiparametric magnetic resonance imaging (mpMRI) interpretation among radiologists using a structured reporting tool based on the METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P) guidelines.

METHODS

A structured report for follow-up pelvic mpMRI for advanced prostate cancer (APC) patients was formulated based on MET-RADS-P guidelines. In total, 163 paired pelvic mpMRI examinations were performed from December 2017 to February 2021 on 105 patients with APC. These were retrospectively reviewed by two senior and two junior radiologists for metastatic lesion detection and were categorized by these readers using primary/secondary response assessment categories (RACs), with and without the structured report. Interreader agreement regarding metastasis detection and RAC scores was evaluated with Cohen's kappa and weighted Cohen's kappa statistics (K), respectively.

RESULTS

The two senior radiologists showed higher agreement with the reference standard for metastasis detection using the structured report (S1: K = 0.83; S2: K = 0.73) compared with the conventional report (S1: K = 0.72; S2: K = 0.61). Junior radiologists showed similar results (J1: 0.66 vs. 0.59; J2: 0.65 vs. 0.57). The overall agreement between the two senior radiologists was excellent for the primary RAC pattern using the structured reports (K = 0.81) and was substantial for secondary RAC categorization (K = 0.75). The interreader agreement of the two junior radiologists was substantial for both primary and secondary RAC values (K = 0.76, 0.68).

CONCLUSION

Good interreader agreement was found for the follow-up assessment of APC patients between radiologists, where the pelvic mpMRI was reported using MET-RADS-P guidelines. This improvement applied to both metastatic lesion detection and qualitative RAC assessment.

Establishment and validation of a predictive model for bone metastasis in prostate cancer patients based on multiple immune inflammatory parameters

OBJECTIVE

This study aims to establish and validate a predictive model for bone metastasis in prostate cancer patients based on multiple immune inflammatory parameters.

METHODS

In this retrospective study, 162 prostate cancer patients who met the inclusion criteria were selected by Urology Surgery, Shaanxi Provincial People's Hospital. Based on the medical record number of patients and the random number table method, 40 patients were randomly included in a validation group, and the rest were in a modeling group. The patients in the modeling group were divided into a metastatic group (n=67) and a non-metastatic group (n=55) according to the whole-body bone imaging results.

RESULTS

The predictive model was established based on the results of Logistics regression analysis: Logit (P) = -5.341 + 0.930*total Gleason score + 1.426*total prostate specific antigen + 0.836*neutrophil-lymphocyte ratio + 0.896*platelet lymphocyte ratio + 0.641*lymphocyte/monocyte ratio + 0.750*albumin/globulin ratio. ROC analysis showed that the areas under the curve of the predictive model for bone metastasis in the modeling and validation groups were 0.896 and 0.870, respectively. Hosmer-Lemeshow test showed that P=0.253, indicating a high degree of the fitting. External verification results showed that the C-index for predicting prostate cancer bone metastasis in the predictive model established in this study was 0.760 (95% CI: 0.670-0.851).

CONCLUSION

The bone metastasis predictive model based on the multiple immune inflammatory parameters (neutrophil-lymphocyte ratio, platelet lymphocyte ratio, lymphocyte/monocyte ratio and albumin/globulin ratio) in prostate cancer patients can reasonably predict the occurrence of bone metastasis and is well worth clinical application.

Validating the screening criteria for bone metastases in treatment-naïve unfavorable intermediate and high-risk prostate cancer - the prevalence and location of bone- and lymph node metastases

OBJECTIVE

The European Association of Urology (EAU) recommends a bone scan for newly diagnosed unfavorable intermediate- and high-risk prostate cancer. We aimed to validate the screening criteria for bone metastases in patients with treatment-naïve prostate cancer.

METHODS

This single-center retrospective study included all patients with treatment-naïve unfavorable intermediate- or high-risk prostate cancer. All underwent MRI of the lumbar column (T2Dixon) and pelvis (3DT2w, DWI, and T2 Dixon). The presence and location of lymph node and bone metastases were registered according to risk groups and radiological (rad) T-stage. The risk of lymph node metastases was assessed by odds ratio (OR).

RESULTS

We included 390 patients, of which 68% were high-risk and 32% were unfavorable intermediate-risk. In the high-risk group, the rate of regional- and non-regional lymph node metastases was 11% and 6%, respectively, and the rate of bone metastases was 10%. In the unfavorable intermediate-risk group, the rate of regional- and non-regional lymph node metastases was 4% and 0.8%, respectively, and the rate of bone metastases was 0.8%. Metastases occurred exclusively in the lumbar column in 0.5% of all patients, in the pelvis in 4%, and the pelvis and lumbar column in 3%. All patients with bone metastases had radT3-4, and patients with radT3-4 showed a four-fold increased risk of lymph node metastases (OR 4.48, 95% CI: 2.1-9.5).

CONCLUSION

Bone metastases were found in 10% with high-risk prostate cancer and 0.8% with unfavorable intermediate-risk. Therefore, we question the recommendation to screen the unfavorable intermediate-risk group for bone metastases.

KEY POINTS

• The rate of bone metastases was 10% in high-risk patients and 0.8% in the unfavorable intermediate-risk group. • The rate of lymph-node metastases was 17% in high-risk patients and 5% in the unfavorable intermediate-risk group. • No bone metastases were seen in radiologically localized disease.

Tumor-Specificity Growth Factor Combined with Tumor Markers in Nuclear Medicine Imaging to Identify Prostate Cancer Osteonosus

Objective

This study has explored the application value of malignant tumor SPE growth factor (TSGF) combined with tumor markers (TM) (TSGF + TM) in nuclear medicine imaging to identify prostate cancer osteonosus (PCO).

Methods

A retrospective analysis for 70 patients with prostate cancer and bone disease admitted to our hospital was performed, 30 healthy persons in the same period were selected as the control group, and the advantages and disadvantages of various examinations were analyzed. All patients were diagnosed with PET whole body bone imaging. Suspicious lesions could be examined by MRI or CT. According to the results of imaging examination, patients were divided into 40 cases of malignant prostate cancer and 30 cases of benign prostate cancer. All the patients underwent 18F-FDG-PET imaging, alpha-fetoprotein (AFP), and TSGF + TM determination. The case diagnosis results were compared and analyzed, and the sensitivity (SEN), specificity (SPE), and accuracy (ACC) of various detection methods were calculated. The SEN, SPE, and ACC of positron emission tomography (PET) were 90.9%, 57.8%, and 81.2%, respectively; those of TM were 79.2%, 94.6%, and 69.8%, respectively; and those of TSGF + TM were 95.9%, 100%, and 97.3%, respectively. The accuracy of combined diagnosis of tumors can reach 100%. The AFP and TSGF levels of serum TM were compared and analyzed, and it was found that the benign lesion group and the malignant lesion group showed significant increases compared with the control group, and the difference between the malignant lesion group and the control group was obvious (P < 0.05). SGF combined with TM could obtain a more definite diagnosis in PCO.

Conclusion

TSGF + TM combined with 18F-FDG-PET imaging showed important clinical value to diagnose the PCO. The imaging accuracy of TSGF + TM combined with 18F-FDG-PET is 97.3%, and the specificity of tumor diagnosis is 100%. Therefore, the TSGF + TM applied in medical imaging and identification of PCO was worthy of clinical promotion.

Detection of Bone Metastases on Bone Scans through Image Classification with Contrastive Learning

Patients with bone metastases have poor prognoses. A bone scan is a commonly applied diagnostic tool for this condition. However, its accuracy is limited by the nonspecific character of radiopharmaceutical accumulation, which indicates all-cause bone remodeling. The current study evaluated deep learning techniques to improve the efficacy of bone metastasis detection on bone scans, retrospectively examining 19,041 patients aged 22 to 92 years who underwent bone scans between May 2011 and December 2019. We developed several functional imaging binary classification deep learning algorithms suitable for bone scans. The presence or absence of bone metastases as a reference standard was determined through a review of image reports by nuclear medicine physicians. Classification was conducted with convolutional neural network-based (CNN-based), residual neural network (ResNet), and densely connected convolutional networks (DenseNet) models, with and without contrastive learning. Each set of bone scans contained anterior and posterior images with resolutions of 1024 × 256 pixels. A total of 37,427 image sets were analyzed. The overall performance of all models improved with contrastive learning. The accuracy, precision, recall, F1 score, area under the receiver operating characteristic curve, and negative predictive value (NPV) for the optimal model were 0.961, 0.878, 0.599, 0.712, 0.92 and 0.965, respectively. In particular, the high NPV may help physicians safely exclude bone metastases, decreasing physician workload, and improving patient care.

3D MR fingerprinting (MRF) for simultaneous T1 and T2 quantification of the bone metastasis: Initial validation in prostate cancer patients

PURPOSE

To investigate the feasibility of using 3-dimensional MRF for bone marrow evaluation in the field of view of prostate MRI for T1 and T2 quantification of prostate cancer bone metastases, as well as comparing it to the ADC value.

METHODS

In this retrospective study, 30 prostate MRIs were included: 14 cases with prostate cancer bone metastasis and 16 cases without prostate cancer (control). MRF was obtained twice before (nonenhanced [NE] MRF) and after contrast injection (contrast-enhanced [CE] MRF), and T1 and T2 maps were generated from each MRF. Two radiologists independently drew regions of interest (ROIs) on the MRF maps and the ADC maps. Mann-Whitney U tests and the area under the receiver operating characteristic curve (AUROC) evaluated the two-reader means of T1, T2 and ADC values between bone metastasis and normal bone.

RESULTS

There were 83 ROIs, including 39 bone metastases and 44 normal bone. The two-reader average ADC, NE T2 and CE T2 values were significantly lower and NE T1 and CE T1 values were significantly higher in metastatic bone compared with normal bone (P < 0.001). The AUROC of the ADC was lowest (0.685), which was significantly lower than those of NE T1 (1.0, P = 0.001), NE T2 (0.932, P = 0.004), and CE T2 (0.876, P = 0.031).

CONCLUSION

MRF to assess the pelvic bone during a prostate gland evaluation provides a reliable parametric map for skeletal work-up. With higher diagnostic performance than the ADC value, NE MRF is a potential alternative for quantifying bone marrow metastases in prostate cancer patients.

Abnormal Indexes of Liver and Kidney Injury Markers Predict Severity in COVID-19 Patients

BACKGROUND

SARS-CoV-2 can damage not only the lungs but also the liver and kidney. Most critically ill patients with coronavirus disease 2019 (COVID-19) have liver and kidney dysfunction. We aim to investigate the levels of liver and kidney function indexes in mild and severe COVID-19 patients and their capability to predict the severity of the disease.

METHODS

The characteristics and laboratory indexes were compared between patients with different conditions. We applied binary logistic regression to find the independent risk factors of severe patients. Receiver operating characteristic (ROC) analysis was used to predict the severity of COVID-19 using the liver and kidney function indexes.

RESULTS

This study enrolled 266 COVID-19 patients, including 235 mild patients and 31 severe patients. Compared with mild patients, severe patients had lower albumin (ALB) and higher alanine aminotransferase (ALT), aspartate aminotransferase (AST), and urea nitrogen (BUN) (all p<0.001). Binary logistic regression analysis also identified ALB [OR=0.273 (0.079-0.947), p=0.041] and ALT [OR=2.680 (1.036-6.934), p=0.042] as independent factors of severe COVID-19 patients. Combining ALB, ALT, BUN, and LDH exhibited the area under ROC at 0.914, with a sensitivity of 86.7% and specificity of 83.0%.

CONCLUSION

COVID-19 patients, especially severe patients, have damage to liver and kidney function. ALT, AST, LDH, and BUN could be independent factors for predicting the severity of COVID-19. Combining the ALB, ALT, BUN, and LDH could predict the transition from mild to severe in COVID-19 patients.

[MRI of the axial skeleton for evaluation of prostate cancer extent in french Guyana]

INTRODUCTION

Spread evaluation of Prostate Cancer (PC) in French Guyana is bothered by the lack of bone scintigraphy. The availability of 4 MRI allows to develop alternatives using Axial Skeleton MRI (AS MRI). We report the related results.

MATERIAL

AS MRI was done in patients with diagnosis of high risk PC: PSA>=10ng/ml and/or Gleason Score>=7 (predominant Gleason grade 4) and/or clinical T2b and/or T2b/T3 MRI and/or >50% positive biopsies. AS MRI was including spine, pelvis and skull assessement.The results were systematically compared to the clinical, biological and biopsy features.

RESULTS

Amongst 163 AS MRI performed, 30 were positive and 133 negative. Of these 133 patients, 60 were submited to radical prostatectomy with or without lymphadenectomy. In these 133 patients with negative AS MRI, median PSA was 11ng/ml (1-51) and 27 (20,3%) had PSA>20ng/ml. In patients with positive AS MRI, only 1 had PSA<20ng/ml and predominant Gleason grade 3.

CONCLUSION

Our study shows that AS MRI assessement is especially usefull in patients who are most likely to have bone metastasis that is to say those with PSA>20ng/ml and/or predominant Gleason grade 4.

LEVEL OF EVIDENCE

3.