Usefulness of the inchworm sign on DWI for predicting pT1 bladder cancer progression

Enhancing recurrence risk prediction for bladder cancer using multi-sequence MRI radiomics

OBJECTIVE

We aimed to develop a radiomics-clinical nomogram using multi-sequence MRI to predict recurrence-free survival (RFS) in bladder cancer (BCa) patients and assess its superiority over clinical models.

METHODS

A retrospective cohort of 229 BCa patients with preoperative multi-sequence MRI was divided into a training set (n = 160) and a validation set (n = 69). Radiomics features were extracted from T2-weighted images, diffusion-weighted imaging, apparent diffusion coefficient, and dynamic contrast-enhanced images. Effective features were identified using the least absolute shrinkage and selection operator (LASSO) method. Clinical risk factors were determined via univariate and multivariate Cox analysis, leading to the creation of a radiomics-clinical nomogram. Kaplan-Meier analysis and log-rank tests assessed the relationship between radiomics features and RFS. We calculated the net reclassification improvement (NRI) to evaluate the added value of the radiomics signature and used decision curve analysis (DCA) to assess the nomogram's clinical validity.

RESULTS

Radiomics features significantly correlated with RFS (log-rank p < 0.001) and were independent of clinical factors (p < 0.001). The combined model, incorporating radiomics features and clinical data, demonstrated the best prognostic value, with C-index values of 0.853 in the training set and 0.832 in the validation set. Compared to the clinical model, the radiomics-clinical nomogram exhibited superior calibration and classification (NRI: 0.6768, 95% CI: 0.5549-0.7987, p < 0.001).

CONCLUSION

The radiomics-clinical nomogram, based on multi-sequence MRI, effectively assesses the BCa recurrence risk. It outperforms both the radiomics model and the clinical model in predicting BCa recurrence risk.

CRITICAL RELEVANCE STATEMENT

The radiomics-clinical nomogram, utilizing multi-sequence MRI, holds promise for predicting bladder cancer recurrence, enhancing individualized clinical treatment, and performing tumor surveillance.

KEY POINTS

• Radiomics plays a vital role in predicting bladder cancer recurrence. • Precise prediction of tumor recurrence risk is crucial for clinical management. • MRI-based radiomics models excel in predicting bladder cancer recurrence.

Progress of Multiparameter Magnetic Resonance Imaging in Bladder Cancer: A Comprehensive Literature Review

Magnetic resonance imaging (MRI) has been proven to be an indispensable imaging method in bladder cancer, and it can accurately identify muscular invasion of bladder cancer. Multiparameter MRI is a promising tool widely used for preoperative staging evaluation of bladder cancer. Vesical Imaging-Reporting and Data System (VI-RADS) scoring has proven to be a reliable tool for local staging of bladder cancer with high accuracy in preoperative staging, but VI-RADS still faces challenges and needs further improvement. Artificial intelligence (AI) holds great promise in improving the accuracy of diagnosis and predicting the prognosis of bladder cancer. Automated machine learning techniques based on radiomics features derived from MRI have been utilized in bladder cancer diagnosis and have demonstrated promising potential for practical implementation. Future work should focus on conducting more prospective, multicenter studies to validate the additional value of quantitative studies and optimize prediction models by combining other biomarkers, such as urine and serum biomarkers. This review assesses the value of multiparameter MRI in the accurate evaluation of muscular invasion of bladder cancer, as well as the current status and progress of its application in the evaluation of efficacy and prognosis.

Vesical imaging reporting and data system (VI-RADS) could predict the survival of bladder-cancer patients who received radical cystectomy

Vesical Imaging Reporting and Data System (VI-RADS) shows good potential in determining muscle-invasive bladder cancer (MIBC) patients. However, whether VI-RADS could predict the prognosis of radical cystectomy (RC) patients has not been reported. Our purpose is to determine whether VI-RADS contributed to predict oncologic outcomes. In this retrospective study, we analysed the information of bladder cancer patients who admitted to our centre from June 2012 to June 2022. All patients who underwent multiparametric magnetic resonance imaging (mpMRI) and underwent RC were included. VI-RADS scoring was performed by two radiologists blinded to the clinical data. Patients' clinical features, pathology data, and imaging information were recorded. Kaplan-Meier method was used to estimate patients' overall survival (OS) and progression-free survival (PFS). Log-rank test was used to assess statistical differences. COX regression analysis was used to estimate risk factors. Ultimately, we included 219 patients, with 188 males and 31 females. The median age was 66 (IQR = 61-74.5) years. The VI-RADS scores were as follows: VI-RADS 1, 4 (1.8%); VI-RADS 2, 68 (31.1%); VI-RADS 3, 40 (18.3%); VI-RADS 4, 69 (31.5%); and VI-RADS 5, 38 (17.4%). Patients with VI-RADS ≥ 3 had poorer OS and PFS than those with VI-RADS < 3. The AUC of VI-RADS predicting 3-year OS was 0.804, with sensitivity of 0.824 and negative predictive value of 0.942. Multivariate COX analysis showed that VI-RADS ≥ 3 was risk factors for OS (HR = 3.517, P = 0.003) and PFS (HR = 4.175, P < 0.001). In the MIBC subgroup, patients with VI-RADS ≥ 4 had poorer OS and PFS. In the non-muscle invasive bladder cancer (NMIBC) subgroup, the prognosis of patients with VI-RADS ≥ 3 remained poorer. VI-RADS scores could effectively predict the survival of patients after RC.

Unclear tumor border in magnetic resonance imaging as a prognostic factor of squamous cell cervical cancer

Magnetic resonance imaging (MRI) is used for pretreatment staging in cervical cancer. In the present study, we used pretreatment images to categorize operative cases into two groups and evaluated their prognosis. A total of 53 cervical cancer patients with squamous cell carcinoma who underwent radical hysterectomy were included in this study. Based on MRI, the patients were classified into two groups, namely clear and unclear tumor border. For each patient, the following characteristics were evaluated: overall survival; recurrence-free survival; lymph node metastasis; lymphovascular space invasion; and pathological findings, including immunohistochemical analysis of vimentin. The clear and unclear tumor border groups included 40 and 13 patients, respectively. Compared with the clear tumor border group, the unclear tumor border group was associated with higher incidence rates of recurrence (3/40 vs. 3/13, respectively), lymphovascular space invasion (24/40 vs. 13/13, respectively), lymph node metastasis (6/40 vs. 10/13, respectively), and positivity for vimentin (18/40 vs. 10/13, respectively). Despite the absence of significant difference in recurrence-free survival (p = 0.0847), the unclear tumor border group had a significantly poorer overall survival versus the clear tumor border group (p = 0.0062). According to MRI findings, an unclear tumor border in patients with squamous cell cervical cancer is linked to poorer prognosis, lymph node metastasis, and distant recurrence of metastasis.

Evaluation of Whole-Tumor Texture Analysis Based on MRI Diffusion Kurtosis and Biparametric VI-RADS Model for Staging and Grading Bladder Cancer

BACKGROUND

to evaluate the feasibility of texture analysis (TA) based on diffusion kurtosis imaging (DKI) in staging and grading bladder cancer (BC) and to compare it with apparent diffusion coefficient (ADC) and biparametric vesical imaging reporting and data system (VI-RADS).

MATERIALS AND METHODS

In this retrospective study, 101 patients with pathologically confirmed BC underwent MRI with multiple-b values ranging from 0 to 2000 s/mm². ADC- and DKI-derived parameters, including mean kurtosis (MK) and mean diffusivity (MD), were obtained. First-order texture histogram parameters of MK and MD, including the mean; 5th, 25th, 50th, 75th, and 90th percentiles; inhomogeneity; skewness: kurtosis; and entropy; were extracted. The VI-RADS score was evaluated based on the T2WI and DWI. The Mann-Whitney U-test was used to compare the texture parameters and ADC values between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), as well as between low and high grades. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of each significant parameter and their combinations.

RESULTS

The NMIBC and low-grade group had higher MDmean, MD5th, MD25th, MD50th, MD75th, MD90th, and ADC values than those of the MIBC and the high-grade group. The NMIBC and low-grade group yielded lower MKmean, MK25th, MK50th, MK75th, and MK90th than the MIBC and high-grade group. Among all histogram parameters, MD75th and MD90th yielded the highest AUC in differentiating MIBC from NMIBC (both AUCs were 0.87), while the AUC for ADC was 0.86. The MK75th and MK90th had the highest AUC (both 0.79) in differentiating low- from high-grade BC, while ADC had an AUC of 0.68. The AUC (0.92) of the combination of DKI histogram parameters (MD75th, MD90th, and MK90th) with biparametric VI-RADS in staging BC was higher than that of the biparametric VI-RADS (0.89).

CONCLUSIONS

Texture-analysis-derived DKI is useful in evaluating both the staging and grading of bladder cancer; in addition, the histogram parameters of the DKI (MD75th, MD90th, and MK90th) can provide additional value to VI-RADS.

Does Bladder Cancer with Inchworm Sign Indicate Better Prognosis after TURBT?

Background: Inchworm sign is considered to be a characteristic finding in non-muscle invasive bladder cancer (NMIBC). Nevertheless, pathologically diagnosed muscle invasive bladder cancers (MIBCs) are occasionally diagnosed from tissue obtained by transurethral resection of bladder tumor (TURBT) in patients with inchworm sign. Methods: We retrospectively investigated the factors related to muscle invasive status in bladder cancer associated with inchworm sign and the role of inchworm sign in tumor outcomes following TURBT. Results: Of the 109 patients with inchworm sign, 94 (86.2%) and 15 (13.8%) were NMIBC and MIBC, respectively. Non-papillary tumors (hazard ratio (HR): 9.55, 95% confidence interval (CI): 2.07−44.10; p < 0.01) and tumors located in the bladder neck (HR: 7.73, 95% CI: 1.83−32.76; p < 0.01) were significant predictors of MIBC in bladder cancer with inchworm sign. Furthermore, recurrence-free survival (RFS) and progression-free survival were compared between patients with NMIBC with and without inchworm sign; however, no significant differences were found. In patients with NMIBC with inchworm sign, positive urine cytology was a prognostic factor for RFS (HR: 1.90, 95% CI: 1.04−3.48; p = 0.04). Conclusions: In bladder cancer with inchworm sign, 86.2% were NMIBC. Even in the case of inchworm sign, the presence of a non-papillary tumor or a bladder neck tumor before TURBT should be noted because of the possibility of MIBC. In this study, the inchworm sign was not a prognostic factor in patients with NMIBC.

Combining volumetric apparent diffusion coefficient histogram analysis with vesical imaging reporting and data system to predict the muscle invasion of bladder cancer

OBJECTIVE

The objective of this study was to explore whether volumetric apparent diffusion coefficient (ADC) histogram analysis can provide additional value to Vesical Imaging Reporting and Data System (VI-RADS) in differentiating muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC).

MATERIALS AND METHODS

80 patients were retrospectively reviewed with pathologically proven NMIBC (n = 53) or MIBC (n = 27). All patients underwent MRI including diffusion-weighted imaging (DWI) (b = 0, 800 s/mm²), and the VI-RADS score was evaluated based on DWI. Volumetric ADC histogram parameters were calculated from the volumetric of interest (VOI) on DWI, including the min ADC, mean ADC, median ADC, max ADC, 10th, 25th, 75th, 90th percentiles ADC, skewness, kurtosis, and entropy. The Mann-Whitney U-test was used to compare histogram parameters between NMIBC and MIBC. Receiver operating characteristic analysis was used to evaluate the diagnostic value of each significant parameter.

RESULTS

Among all parameters, the VI-RADS yield the highest Area Under the Curve (AUC, 0.88; sensitivity, 88.89%; specificity, 83.61%). MIBC had significantly lower min ADC, mean ADC, median ADC, 10th, 25th, 75th, and 90th percentiles ADC than NMIBC (p = 0.002, p < 0.001, p < 0.001, p = 0.003, p = 0.004, p < 0.001, p < 0.001). Skewness and kurtosis of MIBC were significantly higher than those of NMIBC (p < 0.001, p < 0.001). The combination of VI-RADS and skewness showed significantly higher AUC (AUC 0.923; 95% CI 0.847-0.969) than only with VI-RADS (AUC 0.880; 95% CI 0.793-0.940).

CONCLUSION

Volumetric ADC histogram analysis and VI-RADS are both useful methods in differentiating MIBC from NMIBC, and the volumetric ADC histogram analysis can provide additional value to VI-RADS.

Accuracy of Inchworm Sign on Diffusion-Weighted MRI in Differentiating Muscle-Invasive Bladder Cancer

BACKGROUND: Inchworm sign is a finding on diffusion-weighted magnetic resonance imaging (DWI-MRI) and is used to better stratify T-staging in muscle invasive (MIBC) and non-muscle-invasive bladder cancer (NMIBC). An uninterrupted low submucosal signal on DWI, defined as inchworm sign (IS), indicates NMIBC. OBJECTIVE: We aimed to define the diagnostic accuracy of IS in primary bladder cancer, as well as find agreement between the urologists and the radiologist. METHODS: Between December 2018 and December 2020, we retrospectively analyzed 95 primary bladder cancer patients who had undergone multiparametric-MRI before transurethral resection. Patients with former bladder cancer history, tumors smaller than 10 mm, and MRI without proper protocol, as well as patients who did not attend follow-up, were excluded. In total, 71 patients’ images were evaluated by a genitourinary specialist radiologist and two urologists. Sensitivity, specificity, positive and negative predictive values of IS and VI-RADS in differentiating MIBC and NMIBC, and interreader agreement between the radiologist and urologists were analyzed. RESULTS: During follow-up, 38 patients (53.5%) were IS-positive, while 33 patients (46.5%) were negative. Among the 33 patients with negative IS, 14 patients (42.4%) had MIBC. Meanwhile, two out of the 38 IS-positive patients (5.3%) had MIBC (p = 0.00). Sensitivity, specificity, and positive and negative predictive values of IS in predicting MIBC were 87.5%, 63.6%, 41.2%and 94.6%, respectively. The interobserver agreement between the urologists and radiologist was almost perfect ( K  = 0.802 and K  = 0.745) CONCLUSION: The absence of IS on DWI is useful in differentiating MIBC from NMIBC. It is a simple finding that can be interpreted by urologists.

Study Progress of Noninvasive Imaging and Radiomics for Decoding the Phenotypes and Recurrence Risk of Bladder Cancer

Urinary bladder cancer (BCa) is a highly prevalent disease among aged males. Precise diagnosis of tumor phenotypes and recurrence risk is of vital importance in the clinical management of BCa. Although imaging modalities such as CT and multiparametric MRI have played an essential role in the noninvasive diagnosis and prognosis of BCa, radiomics has also shown great potential in the precise diagnosis of BCa and preoperative prediction of the recurrence risk. Radiomics-empowered image interpretation can amplify the differences in tumor heterogeneity between different phenotypes, i.e., high-grade vs. low-grade, early-stage vs. advanced-stage, and nonmuscle-invasive vs. muscle-invasive. With a multimodal radiomics strategy, the recurrence risk of BCa can be preoperatively predicted, providing critical information for the clinical decision making. We thus reviewed the rapid progress in the field of medical imaging empowered by the radiomics for decoding the phenotype and recurrence risk of BCa during the past 20 years, summarizing the entire pipeline of the radiomics strategy for the definition of BCa phenotype and recurrence risk including region of interest definition, radiomics feature extraction, tumor phenotype prediction and recurrence risk stratification. We particularly focus on current pitfalls, challenges and opportunities to promote massive clinical applications of radiomics pipeline in the near future.

[French ccAFU guidelines - update 2020-2022: bladder cancer]

OBJECTIVE

- To update French guidelines for the management of bladder cancer specifically non-muscle invasive (NMIBC) and muscle-invasive bladder cancers (MIBC).

METHODS

- A Medline search was achieved between 2018 and 2020, notably regarding diagnosis, options of treatment and follow-up of bladder cancer, to evaluate different references with levels of evidence.

RESULTS

- Diagnosis of NMIBC (Ta, T1, CIS) is based on a complete deep resection of the tumor. The use of fluorescence and a second-look indication are essential to improve initial diagnosis. Risks of both recurrence and progression can be estimated using the EORTC score. A stratification of patients into low, intermediate and high risk groups is pivotal for recommending adjuvant treatment: instillation of chemotherapy (immediate post-operative, standard schedule) or intravesical BCG (standard schedule and maintenance). Cystectomy is recommended in BCG-refractory patients. Extension evaluation of MIBC is based on contrast-enhanced pelvic-abdominal and thoracic CT-scan. Multiparametric MRI can be an alternative. Cystectomy associated with extended lymph nodes dissection is considered the gold standard for non-metastatic MIBC. It should be preceded by cisplatin-based neoadjuvant chemotherapy in eligible patients. An orthotopic bladder substitution should be proposed to both male and female patients with no contraindication and in cases of negative frozen urethral samples; otherwise transileal ureterostomy is recommended as urinary diversion. All patients should be included in an Early Recovery After Surgery (ERAS) protocol. For metastatic MIBC, first-line chemotherapy using platin is recommended (GC or MVAC), when performans status (PS <1) and renal function (creatinine clearance >60 mL/min) allow it (only in 50% of cases). In second line treatment, immunotherapy with pembrolizumab demonstrated a significant improvement in overall survival.

CONCLUSION

- These updated French guidelines will contribute to increase the level of urological care for the diagnosis and treatment of patients diagnosed with NMIBC and MIBC.

A population-based study on the effect of a routine second-look resection on survival in primary stage T1 bladder cancer

OBJECTIVE

To assess the value of second-look resection (SLR) in stage T1 bladder cancer (BCa) with respect to progression-free survival (PFS), and also the secondary outcomes recurrence-free survival (RFS), bladder-cancer-specific survival (CSS), and cystectomy-free survival (CFS).

PATIENTS AND METHODS

The study included 2456 patients diagnosed with stage T1 BCa 2004-2009 with 5-yr follow-up registration in the nationwide Bladder Cancer Data Base Sweden (BladderBaSe). PFS, RFS, CSS, and CFS were evaluated in stage T1 BCa patients with or without routine SLR, using univariate and multivariable Cox regression with adjustment for multiple confounders (age, gender, tumour grade, intravesical treatment, hospital volume, comorbidity, and educational level).

RESULTS

SLR was performed in 642 (26%) individuals, and more frequently on patients who were aged < 75 yr, had grade 3 tumours, and had less comorbidity. There was no association between SLR and PFS (hazard ratio [HR] 1.1, confidence interval [CI] 0.85-1.3), RFS (HR 1.0, CI 0.90-1.2), CFS (HR 1.2, CI 0.95-1.5) or CSS (HR 1.1, CI 0.89-1.4).

CONCLUSIONS

We found similar survival outcomes in patients with and patients without SLR, but our study is likely affected by selection mechanisms. A randomised study defining the role of SLR in stage T1 BCa would be highly relevant to guide current praxis.

The invasion depth measurement of bladder cancer using T2-weighted magnetic resonance imaging

BACKGROUND

Invasion depth is an important index for staging and clinical treatment strategy of bladder cancer (BCa). The aim of this study was to investigate the feasibility of segmenting the BCa region from bladder wall region on MRI, and quantitatively measuring the invasion depth of the tumor mass in bladder lumen for further clinical decision-making. This retrospective study involved 20 eligible patients with postoperatively pathologically confirmed BCa. It was conducted in the following steps: (1) a total of 1159 features were extracted from each voxel of both the certain cancerous and wall tissues with the T2-weighted (T2W) MRI data; (2) the support vector machine (SVM)-based recursive feature elimination (RFE) method was implemented to first select an optimal feature subset, and then develop the classification model for the precise separation of the cancerous regions; (3) after excluding the cancerous region from the bladder wall, the three-dimensional bladder wall thickness (BWT) was calculated using Laplacian method, and the invasion depth of BCa was eventually defined by the subtraction of the mean BWT excluding the cancerous region and the minimum BWT of the cancerous region.

RESULTS

The segmented results showed a promising accuracy, with the mean Dice similarity coefficient of 0.921. The "soft boundary" defined by the voxels with the probabilities between 0.1 and 0.9 could demonstrate the overlapped region of cancerous and wall tissues. The invasion depth calculated from proposed segmentation method was compared with that from manual segmentation, with a mean difference of 0.277 mm.

CONCLUSION

The proposed strategy could accurately segment the BCa region, and, as the first attempt, realize the quantitative measurement of BCa invasion depth.

Clinical utility of the Vesical Imaging-Reporting and Data System for muscle-invasive bladder cancer between radiologists and urologists based on multiparametric MRI including 3D FSE T2-weighted acquisitions

OBJECTIVES

To investigate the clinical utility of the Vesical Imaging-Reporting and Data System (VI-RADS) by comparing its diagnostic performance for muscle-invasive bladder cancer (MIBC) between radiologists and urologists based on multiparametric MRI, including three-dimensional (3D) fast spin-echo (FSE) T2-weighted acquisitions.

METHODS

This study included 66 treatment-naïve patients (60 men, 6 women; mean age 74.0 years) with pathologically proven bladder cancer who underwent multiparametric MRI, including 3D FSE T2-weighted imaging, before transurethral bladder tumour resection between January 2010 and November 2018. The MRI scans were categorised according to the five-point VI-RADS score by four independent readers (two board-certified radiologists and board-certified urologists each), blinded to the histopathological findings. The VI-RADS scores were compared with the postoperative histopathological diagnosis. Interobserver agreement was assessed using weighted kappa coefficients. ROC analysis and generalised estimating equations were used to evaluate the diagnostic performance.

RESULTS

Forty-nine (74.2%) and 17 (25.8%) tumours were confirmed to be non-MIBC and MIBC, respectively, based on pathological examination. The interobserver agreement was good-to-excellent between all pairs of readers (range, 0.73-0.91). The urologists' sensitivity/specificity values for DCE-MRI VI-RADS scores were significantly lower than those of radiologists. No significant differences were observed for the overall VI-RADS score. The AUC for the overall VI-RADS score was 0.94, 0.92, 0.89, and 0.87 for radiologists 1 and 2 and urologists 1 and 2, respectively.

CONCLUSIONS

The VI-RADS score, based on multiparametric MRI including 3D FSE T2-weighted acquisitions, can be useful for radiologists and urologists to determine the bladder cancer muscle invasion status preoperatively.

KEY POINTS

• VI-RADS (using multiparametric MRI including 3D FSE T2-weighted acquisitions) achieves good to excellent interobserver agreement and has similar diagnostic performance for detecting muscle invasion by both radiologists and urologists. • The diagnostic performance of the overall VI-RADS score is high for both radiologists and urologists, particularly due to the dominant effect of diffusion-weighted imaging on the overall VI-RADS score. • The sensitivity and specificity values of the T2WI VI-RADS scores for four readers in our study (using 3D FSE T2-weighted acquisitions) were similar (with slightly higher specificity values) to previously published results (using 2D FSE T2-weighted acquisitions).

Detection of Muscle-Invasive Bladder Cancer on Biparametric MRI Using Vesical Imaging-Reporting and Data System and Apparent Diffusion Coefficient Values (VI-RADS/ADC)

BACKGROUND: Vesical Imaging-Reporting And Data System (VI-RADS) was proposed to detect muscle-invasive bladder cancer (MIBC). OBJECTIVE: To evaluate the performance of VI-RADS and additional value of apparent diffusion coefficient (ADC) values measured on diffusion-weighted magnetic resonance imaging (MRI) for detecting MIBC. METHODS: A total of 176 patients undergoing MRI (multiparametric in 97 [55%] and biparametric in 79 [45%]) before transurethral resection of bladder tumor for primary bladder cancer were retrospectively identified. MRI findings were scored according to VI-RADS. The standardized tumor ADC (sT-ADC: tumor ADC/gluteus maximus ADC) was calculated and used to account for the incompatibility among different MRI protocols. The accuracy of VI-RADS, sT-ADC and their combination to detect MIBC was assessed using the AUC of the ROC curve. RESULTS: MIBC was pathologically confirmed in 46 patients (26%). AUC of VI-RADS to detect MIBC was 0.86. When cut-off of VI-RADS was set at≥3 and≥4, sensitivity/specificity were 78% /70% and 63% /96%, respectively. A lower sT-ADC (≤0.894) was significantly associated with muscle invasion (p < 0.01, AUC 0.79) with sensitivity 78% and specificity 79%. Combination of VI-RADS and sT-ADC improved the accuracy (AUC 0.94); sensitivity was 100% when VI-RADS≥3 or sT-ADC≤0.894 was considered positive, and specificity was 99% when VI-RADS≥4 and sT-ADC≤0.894 was considered positive. Incorporation of sT-ADC reduced under-staging of MIBC as VI-RADS < 3 by 100% and over-staging of non-MIBC as VI-RADS≥4 by 80%. CONCLUSIONS: Incorporation of ADC values into VI-RADS improves accuracy to detect MIBC in primary bladder cancer patients.

Elaboration of a multisequence MRI-based radiomics signature for the preoperative prediction of the muscle-invasive status of bladder cancer: a double-center study

OBJECTIVES

To develop a multisequence MRI-based radiomics signature for the preoperative prediction of the muscle-invasive status of bladder cancer (BCa).

METHODS

This retrospective study involved 106 eligible patients from two independent clinical centers. All patients underwent a preoperative 3.0 T MRI scan with T2-weighted image (T2WI) and multi-b-value diffusion-weighted image (DWI) sequences. In total, 1404 radiomics features were extracted from the largest region of the reported tumor locations on the T2WI, DWI, and corresponding apparent diffusion coefficient map (ADC) of each patient. A radiomics signature, namely the Radscore, was then generated using the recursive feature elimination approach and a logistic regression algorithm in a training cohort (n = 64). Its performance was then validated in an independent validation cohort (n = 42). The primary imaging and clinical factors in conjunction with the Radscore were used to determine whether the performance could be further improved.

RESULTS

The Radscore, generated by 36 selected radiomics features, demonstrated a favorable ability to predict muscle-invasive BCa status in both the training (AUC 0.880) and validation (AUC 0.813) cohorts. Subsequently, integrating the two independent predictors (including the Radscore and MRI-determined tumor stalk) into a nomogram exhibited more favorable discriminatory performance, with the AUC improved to 0.924 and 0.877 in both cohorts, respectively.

CONCLUSIONS

The proposed multisequence MRI-based radiomics signature alone could be an effective tool for quantitative prediction of muscle-invasive status of BCa. Integrating the Radscore with MRI-determined tumor stalk could further improve the discriminatory power, realizing more accurate prediction of nonmuscle-invasive and muscle-invasive BCa.

KEY POINTS

• DWI is superior to T2WI sequence in reflecting the heterogeneous differences between NMIBC and MIBC, and multisequence MRI helps in the preoperative prediction of muscle-invasive status of BCa. • Co-occurrence (CM), run-length matrix (RLM), and gray-level size zone matrix (GLSZM) features were the favorable feature categories for the prediction of muscle-invasive status of BCa. • The Radscore (proposed multisequence MRI-based radiomics signature) helps predict preoperatively muscle invasion. Combination with the MRI-determined tumor stalk further improves prediction.

A predictive nomogram for individualized recurrence stratification of bladder cancer using multiparametric MRI and clinical risk factors

BACKGROUND

Preoperative prediction of bladder cancer (BCa) recurrence risk is critical for individualized clinical management of BCa patients.

PURPOSE

To develop and validate a nomogram based on radiomics and clinical predictors for personalized prediction of the first 2 years (TFTY) recurrence risk.

STUDY TYPE

Retrospective.

POPULATION

Preoperative MRI datasets of 71 BCa patients (34 recurrent) were collected, and divided into training (n = 50) and validation cohorts (n = 21).

FIELD STRENGTH/SEQUENCE

3.0T MRI/T₂ -weighted (T₂ W), multi-b-value diffusion-weighted (DW), and dynamic contrast-enhanced (DCE) sequences.

ASSESSMENT

Radiomics features were extracted from the T₂ W, DW, apparent diffusion coefficient, and DCE images. A Rad_Score model was constructed using the support vector machine-based recursive feature elimination approach and a logistic regression model. Combined with the important clinical factors, including age, gender, grade, and muscle-invasive status (MIS) of the archived lesion, tumor size and number, surgery, and image signs like stalk and submucosal linear enhancement, a radiomics-clinical nomogram was developed, and its performance was evaluated in the training and the validation cohorts. The potential clinical usefulness was analyzed by the decision curve.

STATISTICAL TESTS

Univariate and multivariate analyses were performed to explore the independent predictors for BCa recurrence prediction.

RESULTS

Of the 1872 features, the 32 with the highest area under the curve (AUC) of receiver operating characteristic were selected for the Rad_Score calculation. The nomogram developed by two independent predictors, MIS and Rad_Score, showed good performance in the training (accuracy 88%, AUC 0.915, P << 0.01) and validation cohorts (accuracy 80.95%, AUC 0.838, P = 0.009). The decision curve exhibited when the risk threshold was larger than 0.3, more benefit was observed by using the radiomics-clinical nomogram than using the radiomics or clinical model alone.

DATA CONCLUSION

The proposed radiomics-clinical nomogram has potential in the preoperative prediction of TFTY BCa recurrence.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1893-1904.