Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 20 de 3.515
Filter
1.
BMC Urol ; 24(1): 129, 2024 Jun 17.
Article in English | MEDLINE | ID: mdl-38886684

ABSTRACT

BACKGROUND: Non-clear cell renal cell carcinoma (nccRCC) represents a rare form of renal cell carcinoma (RCC) in the clinic. It is now understood that contrast-enhanced ultrasound (CEUS) exhibits diverse manifestations and can be prone to misdiagnosis. Therefore, summarizing the distinctive features of contrast-enhanced ultrasonography is essential for differentiation from ccRCC. OBJECTIVE: This study aims to evaluate the diagnostic efficacy of qualitative and quantitative CEUS in diagnosing nccRCC to enhance our understanding of this condition. METHODS: We conducted a retrospective analysis of 21 patients with confirmed nccRCC following surgery and assessed the characteristic conventional ultrasound and CEUS imaging features. The paired Wilcoxon signed-rank sum test was employed to compare differences in CEUS time-intensity curve (TIC) parameters between the lesions and the normal renal cortex. RESULTS: Routine ultrasound revealed the following primary characteristics in the 21 nccRCC cases: hypoechoic appearance (10/21, 47.6%), absence of liquefaction (18/21, 66.7%), regular shape (19/21, 90.5%), clear boundaries (21/21, 100%), and absence of calcification (17/21, 81%). Color Doppler flow imaging (CDFI) indicated a low blood flow signal (only 1 case of grade III). Qualitative CEUS analysis demonstrated that nccRCC predominantly exhibited slow progression (76.1%), fast washout (57%), uniformity (61.9%), low enhancement (71.5%), and ring enhancement (61.9%). Quantitative CEUS analysis revealed that parameters such as PE, WiAUC, mTTI, WiR, WiPI, WoAUC, WiWoAUC, and WOR in the lesions were significantly lower than those in the normal renal cortex (Z=-3.980, -3.563, -2.427, -3.389, -3.980, -3.493, -3.528, -2.763, P < 0.001, < 0.001, = 0.015, = 0.001, < 0.001, < 0.001, < 0.001, = 0.006). However, there were no significant differences in RT, TTP, FT, or QOF (all P > 0.05). CONCLUSION: nccRCC exhibits distinctive CEUS characteristics, including slow progression, fast washout, low homogeneity enhancement, and ring enhancement, which can aid in distinguishing nccRCC from ccRCC.


Subject(s)
Carcinoma, Renal Cell , Contrast Media , Kidney Neoplasms , Ultrasonography , Humans , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Kidney Neoplasms/diagnostic imaging , Male , Female , Middle Aged , Retrospective Studies , Aged , Ultrasonography/methods , Adult
3.
BMC Med Imaging ; 24(1): 135, 2024 Jun 06.
Article in English | MEDLINE | ID: mdl-38844837

ABSTRACT

BACKGROUND: This study aims to explore machine learning(ML) methods for non-invasive assessment of WHO/ISUP nuclear grading in clear cell renal cell carcinoma(ccRCC) using contrast-enhanced ultrasound(CEUS) radiomics. METHODS: This retrospective study included 122 patients diagnosed as ccRCC after surgical resection. They were divided into a training set (n = 86) and a testing set(n = 36). CEUS radiographic features were extracted from CEUS images, and XGBoost ML models (US, CP, and MP model) with independent features at different phases were established. Multivariate regression analysis was performed on the characteristics of different radiomics phases to determine the indicators used for developing the prediction model of the combined CEUS model and establishing the XGBoost model. The training set was used to train the above four kinds of radiomics models, which were then tested in the testing set. Radiologists evaluated tumor characteristics, established a CEUS reading model, and compared the diagnostic efficacy of CEUS reading model with independent characteristics and combined CEUS model prediction models. RESULTS: The combined CEUS radiomics model demonstrated the best performance in the training set, with an area under the curve (AUC) of 0.84, accuracy of 0.779, sensitivity of 0.717, specificity of 0.879, positive predictive value (PPV) of 0.905, and negative predictive value (NPV) of0.659. In the testing set, the AUC was 0.811, with an accuracy of 0.784, sensitivity of 0.783, specificity of 0.786, PPV of 0.857, and NPV of 0.688. CONCLUSIONS: The radiomics model based on CEUS exhibits high accuracy in non-invasive prediction of ccRCC. This model can be utilized for non-invasive detection of WHO/ISUP nuclear grading of ccRCC and can serve as an effective tool to assist clinical decision-making processes.


Subject(s)
Carcinoma, Renal Cell , Contrast Media , Kidney Neoplasms , Machine Learning , Neoplasm Grading , Ultrasonography , Humans , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/pathology , Female , Retrospective Studies , Male , Middle Aged , Ultrasonography/methods , Aged , Adult , Radiomics
4.
Clin Genitourin Cancer ; 22(4): 102124, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38852436

ABSTRACT

OBJECTIVE: Eosinophilic solid and cystic renal cell carcinoma (ESC-RCC) is rare and difficult to diagnose. Therefore, we aim to investigate the imaging and pathologic features of ESC-RCC. METHODS: Fifteen cases of ESC-RCC with pathologically confirmed diagnoses were retrospectively collected: CT was performed in 15 cases and MRI in 9 cases. RESULTS: In these patients (6 males and 9 females) (age: mean, 53.3 ± 14.7 years; range, 27-72 years), all tumors were unilateral, renal, and solitary with no clinical symptoms and were classified into-type 1: cystic-solid component, with equal cystic and solid components, was the most common (8/15, 53.3%); type 2: predominantly cystic with a small solid component (4/15, 26.7%); and type 3: predominantly solid (3/15, 20%). The solid component showed equal/slightly higher density on the CT-plain-scan, equal/slightly high signal on the T1-weighted image (T1WI), and low signal on the T2-weighted image (T2WI). Ten cases showed progressive enhancement, while 5 showed a fast-wash-in and fast-wash-out enhancement. One patient experienced hemorrhage, while the others showed no signs of hemorrhage, necrosis, fat, or calcification. Pathologically, the tumor showed cystic solidity, with eosinophilic cytoplasm and granular basophilic-colored spots with focal or diffuse expression of CK20. Ten patients had componential nephrectomy and 5 had radical nephrectomy. No recurrence or metastasis was noted in any case at the follow-up (8-49 months). CONCLUSION: This study describes the imaging and pathologic features of a rare type of renal cancer and proposes 3 imaging types to enhance physicians' diagnosis of this disease and guide clinical diagnosis and treatment.


Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Magnetic Resonance Imaging , Tomography, X-Ray Computed , Humans , Male , Middle Aged , Female , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Carcinoma, Renal Cell/surgery , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/pathology , Kidney Neoplasms/surgery , Aged , Adult , Retrospective Studies , Eosinophilia/diagnostic imaging , Eosinophilia/pathology , Eosinophilia/surgery
5.
World J Surg Oncol ; 22(1): 145, 2024 Jun 01.
Article in English | MEDLINE | ID: mdl-38822338

ABSTRACT

BACKGROUND: The detection of renal cell carcinoma (RCC) has been rising due to the enhanced utilization of cross-sectional imaging and incidentally discovered lesions with adverse pathology demonstrate potential for metastasis. The purpose of our study was to determine the clinical and multiparametric dynamic contrast-enhanced magnetic resonance imaging (CEMRI) associated independent predictors of adverse pathology for cT1/2 RCC and develop the predictive model. METHODS: We recruited 105 cT1/2 RCC patients between 2018 and 2022, all of whom underwent preoperative CEMRI and had complete clinicopathological data. Adverse pathology was defined as RCC patients with nuclear grade III-IV; pT3a upstage; type II papillary RCC, collecting duct or renal medullary carcinoma, unclassified RCC; sarcomatoid/rhabdoid features. The qualitative and quantitative CEMRI parameters were independently reviewed by two radiologists. Univariate and multivariate binary logistic regression analyses were utilized to determine the independent predictors of adverse pathology for cT1/2 RCC and construct the predictive model. The receiver operating characteristic (ROC) curve, confusion matrix, calibration plot, and decision curve analysis (DCA) were conducted to compare the diagnostic performance of different predictive models. The individual risk scores and linear predicted probabilities were calculated for risk stratification, and the Kaplan-Meier curve and log-rank tests were used for survival analysis. RESULTS: Overall, 45 patients were pathologically confirmed as RCC with adverse pathology. Clinical characteristics, including gender, and CEMRI parameters, including RENAL score, tumor margin irregularity, necrosis, and tumor apparent diffusion coefficient (ADC) value were identified as independent predictors of adverse pathology for cT1/2 RCC. The clinical-CEMRI predictive model yielded an area under the curve (AUC) of the ROC curve of 0.907, which outperformed the clinical model or CEMRI signature model alone. Good calibration, better clinical usefulness, excellent risk stratification ability of adverse pathology and prognosis were also achieved for the clinical-CEMRI predictive model. CONCLUSIONS: The proposed clinical-CEMRI predictive model offers the potential for preoperative prediction of adverse pathology for cT1/2 RCC. With the ability to forecast adverse pathology, the predictive model could significantly benefit patients and clinicians alike by providing enhanced guidance for treatment planning and decision-making.


Subject(s)
Carcinoma, Renal Cell , Contrast Media , Kidney Neoplasms , Humans , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Carcinoma, Renal Cell/surgery , Female , Male , Kidney Neoplasms/pathology , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/surgery , Middle Aged , Contrast Media/administration & dosage , Aged , Retrospective Studies , Prognosis , Multiparametric Magnetic Resonance Imaging/methods , Follow-Up Studies , Neoplasm Staging , ROC Curve , Adult , Magnetic Resonance Imaging/methods
6.
Clin Nucl Med ; 49(7): 693-694, 2024 Jul 01.
Article in English | MEDLINE | ID: mdl-38775942

ABSTRACT

ABSTRACT: A 23-year-old woman presenting with gross hematuria was found to have a left renal mass suspicious for renal cell carcinoma on abdominal contrast-enhanced CT. An 18 F-PSMA-1007 PET/CT scan was performed for evaluating the renal mass. 18 F-PSMA-1007 PET/CT showed focal activity of the renal mass, which was a transcription factor E3-rearranged renal cell carcinoma proved after nephrectomy. Surprisingly, diffuse heterogeneous intense activity of the bilateral breasts and moderate activity of the right accessory breast was observed. There was no morphological abnormality of the bilateral breasts and right accessory breast on CT images, indicating physiological PSMA uptake.


Subject(s)
Basic Helix-Loop-Helix Leucine Zipper Transcription Factors , Breast , Carcinoma, Renal Cell , Kidney Neoplasms , Positron Emission Tomography Computed Tomography , Humans , Female , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/metabolism , Breast/diagnostic imaging , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/genetics , Carcinoma, Renal Cell/metabolism , Young Adult , Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/metabolism , Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics , Oligopeptides , Gene Rearrangement , Heterocyclic Compounds, 1-Ring , Niacinamide/analogs & derivatives
7.
J Med Case Rep ; 18(1): 250, 2024 May 18.
Article in English | MEDLINE | ID: mdl-38760853

ABSTRACT

INTRODUCTION: Renal cell carcinoma (RCC) is the dominant primary renal malignant neoplasm, encompassing a significant portion of renal tumors. The presence of synchronous yet histologically distinct ipsilateral RCCs, however, is an exceptionally uncommon phenomenon that is rather under-described in the literature regarding etiology, diagnosis, management, and later outcomes during follow-up. CASE PRESENTATION: We aim to present the 9th case of a combination chromophobe RCC (ChRCC) and clear cell RCC (ccRCC) in literature, according to our knowledge, for a 69-year-old North African, Caucasian female patient who, after complaining of loin pain and hematuria, was found to have two right renal masses with preoperative computed tomography (CT) and underwent right radical nephrectomy. Pathological examination later revealed the two renal masses to be of different histologic subtypes. CONCLUSION: The coexistence of dissimilar RCC subtypes can contribute to diverse prognostic implications. Further research should focus on enhancing the complex, yet highly crucial, preoperative detection and pathological examination to differentiate multiple renal lesions. Planning optimal operative techniques (radical or partial nephrectomy), selecting suitable adjuvant regimens, and reporting long-term follow-up outcomes of patients in whom synchronous yet different RCC subtypes were detected are of utmost importance.


Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Neoplasms, Multiple Primary , Nephrectomy , Tomography, X-Ray Computed , Humans , Carcinoma, Renal Cell/pathology , Carcinoma, Renal Cell/surgery , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/diagnosis , Female , Kidney Neoplasms/pathology , Kidney Neoplasms/surgery , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/diagnosis , Aged , Neoplasms, Multiple Primary/pathology , Neoplasms, Multiple Primary/surgery , Neoplasms, Multiple Primary/diagnosis , Neoplasms, Multiple Primary/diagnostic imaging
8.
Sci Rep ; 14(1): 12043, 2024 05 27.
Article in English | MEDLINE | ID: mdl-38802547

ABSTRACT

To compare and analyze the diagnostic value of different enhancement stages in distinguishing low and high nuclear grade clear cell renal cell carcinoma (ccRCC) based on enhanced computed tomography (CT) images by building machine learning classifiers. A total of 51 patients (Dateset1, including 41 low-grade and 10 high-grade) and 27 patients (Independent Dateset2, including 16 low-grade and 11 high-grade) with pathologically proven ccRCC were enrolled in this retrospective study. Radiomic features were extracted from the corticomedullary phase (CMP), nephrographic phase (NP), and excretory phase (EP) CT images, and selected using the recursive feature elimination cross-validation (RFECV) algorithm, the group differences were assessed using T-test and Mann-Whitney U test for continuous variables. The support vector machine (SVM), random forest (RF), XGBoost (XGB), VGG11, ResNet18, and GoogLeNet classifiers are established to distinguish low-grade and high-grade ccRCC. The classifiers based on CT images of NP (Dateset1, RF: AUC = 0.82 ± 0.05, ResNet18: AUC = 0.81 ± 0.02; Dateset2, XGB: AUC = 0.95 ± 0.02, ResNet18: AUC = 0.87 ± 0.07) obtained the best performance and robustness in distinguishing low-grade and high-grade ccRCC, while the EP-based classifier performance in poorer results. The CT images of enhanced phase NP had the best performance in diagnosing low and high nuclear grade ccRCC. Firstorder_Kurtosis and firstorder_90Percentile feature play a vital role in the classification task.


Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Neoplasm Grading , Tomography, X-Ray Computed , Humans , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Carcinoma, Renal Cell/diagnosis , Tomography, X-Ray Computed/methods , Female , Male , Middle Aged , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/pathology , Kidney Neoplasms/diagnosis , Kidney Neoplasms/classification , Aged , Retrospective Studies , Support Vector Machine , Adult , Machine Learning , Algorithms
9.
BMC Cancer ; 24(1): 659, 2024 May 30.
Article in English | MEDLINE | ID: mdl-38816725

ABSTRACT

BACKGROUND: To investigate the diagnostic efficacy of high-frame-rate contrast-enhanced ultrasound (H-CEUS) in differentiating between clear cell renal cell carcinoma (CCRCC) and angiomyolipoma (AML). METHODS: A retrospective study was performed on the clinical data of 79 patients diagnosed with CCRCC and 31 patients diagnosed with AML at the First Affiliated Hospital of Nanchang University between October 2022 and December 2023. Conventional ultrasound (US) and H-CEUS examinations were conducted on all patients prior to surgery, dynamic images were recorded from the US, and the qualitative and quantitative parameters of H-CEUS were collected. The t-test, χ² test and non-parametric Mann-Whitney test were employed to assess differences in clinical data, US characteristics, and qualitative and quantitative parameters of H-CEUS between the CCRCC and AML groups. The independent risk factors of CCRCC were identified using binary logistic regression. The receiver operator characteristic (ROC) curve was constructed to evaluate the diagnostic effectiveness of clinical + US and H-CEUS in differentiating between CCRCC and AML. RESULTS: The CCRCC group and the AML group exhibited significant differences in patient gender, operation mode, nodular echo, and nodule blood flow (χ²=11.698, -, -,=10.582; P<0.001, <0.001, <0.001, and = 0.014, respectively). In addition, the H-CEUS qualitative analysis demonstrated significant differences between the AML group and the CCRCC group with respect to enhancement mode, regression mode, peak intensity, enhancement uniformity, no enhancement, and presence or absence of pseudocapsule (χ²=41.614, -, -, = 2.758, = 42.099, -; P<0.001, <0.001, <0.001, 0.097, <0.001, and <0.001, respectively). The Arrival time (AT) in the CCRCC group was significantly shorter than that in the AML group, as determined by quantitative analysis of H-CEUS (Z=-3.266, P = 0.001). Furthermore, the Peak intensity (PI), Ascent slope (AS), and The area under the curve (AUC) exhibited significantly higher values in the CCRCC group compared to the AML group (Z=-2.043,=-2.545,=-3.565; P = 0.041, = 0.011, and <0.001, respectively). Logistic regression analysis indicated that only gender, nodule echo, the pseudocapsule, AS, and AUC of H-CEUS were independent risk factors of CCRCC. The ROC curve revealed that combining gender and nodule echo yielded a sensitivity of 92.4%, specificity of 64.5%, and an AUC of 0.847 in distinguishing between CCRCC and AML. When combining the H-CEUS parameters of pseudocapsule, AS, and AUC, the sensitivity, specificity, and AUC for distinguishing between CCRCC and AML were 84.8%, 96.8%, and 0.918, respectively. No statistically significant difference was observed in the diagnostic effectiveness of the two methods (Z=-1.286, P = 0.198). However, H-CEUS demonstrated better AUC and specificity. CONCLUSIONS: H-CEUS enhances the sensitivity and specificity of differentiating between CCRCC and AML by improving the temporal resolution, offering a more precise diagnostic foundation for identifying the most appropriate therapy for patients.


Subject(s)
Angiomyolipoma , Carcinoma, Renal Cell , Contrast Media , Kidney Neoplasms , Ultrasonography , Humans , Angiomyolipoma/diagnostic imaging , Angiomyolipoma/pathology , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Female , Male , Middle Aged , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/pathology , Retrospective Studies , Diagnosis, Differential , Ultrasonography/methods , Adult , Aged , ROC Curve
10.
J Med Case Rep ; 18(1): 262, 2024 May 28.
Article in English | MEDLINE | ID: mdl-38802967

ABSTRACT

BACKGROUND: The duplex kidney is one of the common congenital anomalies of the kidney and urinary tract. We present two cases of renal tumor accompanied with ipsilateral duplex kidney. The image of the tumor, renal artery system and collecting system were rendered by AI software (Fujifilm's Synapse® AI Platform) to support the diagnosis and surgical planning. CASE PRESENTATION: Two Vietnamese patients (a 45-year-old man and a 54-year-old woman) with incidental cT1 renal cell carcinoma (RCC) were confirmed to have ipsilateral duplex kidneys by 3D reconstruction AI technique. One patient had a Renal score 9ah tumor of left kidney while the other had a Renal score 9 × tumor of right kidney in which a preoperative CT scan failed to identify a diagnosis of duplex kidney. Using the Da Vinci platform, we successfully performed robotic partial nephrectomy without any damage to the collecting system in both cases. CONCLUSION: RCC with duplex kidneys is a rare condition. By utilizing a novel AI reconstruction technique with adequate information, two patients with RCC in duplex kidneys were successfully performed robotic partial nephrectomy without complication.


Subject(s)
Carcinoma, Renal Cell , Imaging, Three-Dimensional , Kidney Neoplasms , Kidney , Nephrectomy , Robotic Surgical Procedures , Humans , Carcinoma, Renal Cell/surgery , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Middle Aged , Nephrectomy/methods , Kidney Neoplasms/surgery , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/pathology , Male , Robotic Surgical Procedures/methods , Female , Kidney/abnormalities , Tomography, X-Ray Computed
13.
J Assoc Physicians India ; 72(3): 18-23, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38736111

ABSTRACT

OBJECTIVES: To study the utility of chemical shift imaging (CSI) and diffusion-weighted images (DWI)/apparent diffusion coefficient (ADC) maps for the evaluation of solid renal tumors. METHODS: Magnetic resonance imaging (MRI) has an equivalent application as computerized tomography (CT) in the characterization of renal masses. It offers a radiation-free imaging technique and has a better soft tissue contrast than CT. Also, MRI is favored in patients with chronic kidney disease. MRI is useful when findings on CT are equivocal. The role of DWI in characterizing solid renal lesions as malignant is encouraging, and DWI can be particularly useful when gadolinium is contraindicated. CSI is useful in differentiating angiomyolipoma (AML) from clear cell (cc) renal cell carcinoma (RCC). We did a cross-sectional study on 24 patients with solid renal masses. MRI of the upper abdomen (from the dome of the diaphragm to the iliac crest) will be done on an MRI machine in our department (1.5T, ACHIEVA, Phillips medical system) using the torso coil. RESULT: There was no significant association seen in terms of ADC values and histological subtypes (χ2 = 11.222, p = 0.082). In our study, 50% (one out of two) of AML showed a signal drop, whereas 40% of cases (6 out of 15) of ccRCC and 66% (two out of three) of papillary RCC showed a signal drop. CONCLUSION: In this article, we concluded CSI, although a useful tool to look for microscopic fat, can't be used as a reliable marker to rule in cc-carcinoma as both AML and papillary cell carcinoma have microscopic fat. Further, no histological classification can be done on the basis of DWI/ADC images.


Subject(s)
Carcinoma, Renal Cell , Diffusion Magnetic Resonance Imaging , Kidney Neoplasms , Humans , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/pathology , Diffusion Magnetic Resonance Imaging/methods , Cross-Sectional Studies , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Female , Angiomyolipoma/diagnostic imaging , Male , Middle Aged , Adult , Aged
14.
Int J Med Inform ; 187: 105467, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38678674

ABSTRACT

OBJECTIVES: Adherent perinephric fat (APF) poses significant challenges to surgical procedures. This study aimed to evaluate the usefulness of machine learning algorithms combined with MRI-based radiomics features for predicting the presence of APF. MATERIALS AND METHODS: Patients with renal cell carcinoma who underwent surgery between April 2019 and February 2022 at Chonnam National University Hwasun Hospital were retrospectively screened, and 119 patients included. Twenty-one and seventeen patients were set aside for the internal and external test sets, respectively. Pre-operative T1-weighted MRI acquired at 60 s following a contrast injection (T1w-60) were collected. For each T1w-60 data, two regions of interest (ROIs) were manually drawn: the perinephric fat tissue and an aorta segment on the same level as the targeted kidney. Preprocessing steps included resizing voxels, N4 Bias Correction filtering, and aorta-based normalization. For each patient, 851 radiomics features were extracted from the ROI of perinephric fat tissue. Gender and BMI were added as clinical factors. Least Absolute Shrinkage and Selection Operator was adopted for feature selection. We trained and evaluated five models using a 4-fold cross validation. The final model was chosen based on the highest mean AUC across four folds. The performance of the final model was evaluated on the internal and external test sets. RESULTS: A total of 15 features were selected in the final set. The final model achieved the accuracy, sensitivity, specificity, and AUC of 81% (95% confidence interval, 61.9-95.2%), 72.7% (42.9-100%), 90% (66.7-100%), and 0.855 (0.615-1.0), respectively on the internal test set, and 88.2% (70.6-100%), 100% (100-100%), 80% (50%-100%), 0.971 (0.871-1.0), respectively on the external test set. CONCLUSIONS: Our study demonstrated the feasibility of machine learning algorithms trained with MRI-based radiomics features for APF prediction. Further studies with a multi-center approach are necessary to validate our findings.


Subject(s)
Adipose Tissue , Carcinoma, Renal Cell , Kidney Neoplasms , Machine Learning , Magnetic Resonance Imaging , Humans , Female , Male , Middle Aged , Kidney Neoplasms/diagnostic imaging , Retrospective Studies , Adipose Tissue/diagnostic imaging , Carcinoma, Renal Cell/diagnostic imaging , Aged , Kidney/diagnostic imaging , Adult , Algorithms , Radiomics
15.
Cardiovasc Intervent Radiol ; 47(5): 573-582, 2024 May.
Article in English | MEDLINE | ID: mdl-38561521

ABSTRACT

PURPOSE: To retrospectively compare long-term oncologic outcomes of percutaneous computed tomography-guided microwave ablation (MWA) and robot-assisted partial nephrectomy (RAPN) for the treatment of stage 1 (T1a and T1b) renal cell carcinoma (RCC) patients. MATERIALS AND METHODS: Institutional database research identified all T1 RCC patients who underwent either MWA or RAPN. Models were adjusted with propensity score matching. Kaplan-Meier log-rank test analyses and Cox proportional hazard regression models were used to compare the oncologic outcomes. Patient and tumor characteristics, technical success as well as oncologic outcomes were evaluated and compared between the 2 groups. RESULTS: After propensity score matching, a total of 71 patients underwent percutaneous MWA (mean age 70 ± 10 years) and 71 underwent RAPN (mean age 60 ± 9 years). At 8-year follow-up, the estimated survival rates for MWA cohort were 98% (95% confidence interval [CI] 95-100%) for overall survival, 97% (95% CI 93-100%) for recurrence-free survival, and 97% (95% CI 93-100%) for metastasis-free survival. The matched cohort that underwent RAPN exhibited survival rates of 100% (95% CI 100-100%) for overall survival, 98% (95% CI 94-100%) for recurrence-free survival, and 98% (95% CI 94-100%) for metastasis-free survival. After performing log-rank testing, these rates were not significantly different (p values of 0.44, 0.67, and 0.67, respectively). CONCLUSION: The results of the present study suggest that both MWA and RAPN are equally effective in terms of oncologic outcome for the treatment of T1 RCC.


Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Microwaves , Nephrectomy , Propensity Score , Robotic Surgical Procedures , Humans , Carcinoma, Renal Cell/surgery , Carcinoma, Renal Cell/pathology , Carcinoma, Renal Cell/diagnostic imaging , Kidney Neoplasms/surgery , Kidney Neoplasms/pathology , Kidney Neoplasms/diagnostic imaging , Male , Female , Nephrectomy/methods , Microwaves/therapeutic use , Aged , Middle Aged , Robotic Surgical Procedures/methods , Retrospective Studies , Follow-Up Studies , Treatment Outcome , Neoplasm Staging , Tomography, X-Ray Computed , Radiography, Interventional/methods , Survival Rate
16.
Radiol Med ; 129(6): 834-844, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38662246

ABSTRACT

PURPOSE: To study the capability of diffusion-relaxation correlation spectroscopic imaging (DR-CSI) on subtype classification and grade differentiation for small renal cell carcinoma (RCC). Histogram analysis for apparent diffusion coefficient (ADC) was studied for comparison. MATERIALS AND METHODS: A total of 61 patients with small RCC (< 4 cm) were included in the retrospective study. MRI data were reviewed, including a multi-b (0-1500 s/mm2) multi-TE (51-200 ms) diffusion weighted imaging (DWI) sequence. Region of interest (ROI) was delineated manually on DWI to include solid tumor. For each patient, a D-T2 spectrum was fitted and segmented into 5 compartments, and the volume fractions VA, VB, VC, VD, VE were obtained. ADC mapping was calculated, and histogram parameters ADC 90th, 10th, median, standard deviation, skewness and kurtosis were obtained. All MRI metrices were compared between clear cell RCC (ccRCC) and non-ccRCC group, and between high-grade and low-grade group. Receiver operator curve analysis was used to assess the corresponding diagnostic performance. RESULTS: Significantly higher ADC 90th, ADC 10th and ADC median, and significantly lower DR-CSI VB was found for ccRCC compared to non-ccRCC. Significantly lower ADC 90th, ADC median and significantly higher VB was found for high-grade RCC compared to low-grade. For identifying ccRCC from non-ccRCC, VB showed the highest area under curve (AUC, 0.861) and specificity (0.882). For differentiating high- from low-grade, ADC 90th showed the highest AUC (0.726) and specificity (0.786), while VB also displayed a moderate AUC (0.715). CONCLUSION: DR-CSI may offer improved accuracy in subtype identification for small RCC, while do not show better performance for small RCC grading compared to ADC histogram.


Subject(s)
Carcinoma, Renal Cell , Diffusion Magnetic Resonance Imaging , Kidney Neoplasms , Humans , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Kidney Neoplasms/diagnostic imaging , Male , Female , Diffusion Magnetic Resonance Imaging/methods , Retrospective Studies , Middle Aged , Aged , Adult , Neoplasm Grading , Aged, 80 and over , Sensitivity and Specificity
17.
Br J Radiol ; 97(1158): 1146-1152, 2024 May 29.
Article in English | MEDLINE | ID: mdl-38688580

ABSTRACT

OBJECTIVE: Quantitative comparison of the diagnostic efficacy of conventional diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in differentiating between chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO). METHODS: A total of 48 patients with renal tumours who had undergone DWI and IVIM were divided into two groups-ChRCC (n = 28) and RO (n = 20) groups, and the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and their diagnostic efficacy were compared between the two groups. RESULTS: The D* values were higher in the ChRCCs group compared to the RO groups (0.019 ± 0.003 mm2/s vs 0.008 ± 0.002 mm2/s, P < .05). Moreover, the ADC, D and f values were higher in ROs compared to ChRCCs (0.61 ± 0.08 × 10-3 mm2/s vs 0.51 ± 0.06 × 10-3 mm2/s, 1.02 ± 0.15 × 10-3 mm2/s vs 0.86 ± 0.07 × 10-3 mm2/s, 0.41 ± 0.05 vs 0.28 ± 0.02, P < .05). The areas of the ADC, D, D* and f values under the ROC curves in differentiating ChRCCs from ROs were 0.713, 0.839, 0.856 and 0.906, respectively. The cut-off values of ADC, D, D* and f were 0.54, 0.91, 0.013 and 0.31, respectively. The AUC, sensitivity, specificity and accuracy of the f values were 0.906, 89.3%, 80.0% and 89.6%, respectively. For pairwise comparisons of ROC curves and diagnostic efficacy, IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCCs from ROs (P = .013, .016, and .008) with f having the highest diagnostic accuracy. CONCLUSION: IVIM parameters presented better performance than ADC in differentiating ChRCCs from ROs. ADVANCES IN KNOWLEDGE: (1) D* values of ChRCCs were higher, while ADC, D and f values were lower than those of RO tumours. (2) f values had the highest diagnostic efficacy in differentiating ChRCC from RO. (3) IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCC from RO (P=.013, .016, and .008).


Subject(s)
Adenoma, Oxyphilic , Carcinoma, Renal Cell , Diffusion Magnetic Resonance Imaging , Kidney Neoplasms , Humans , Kidney Neoplasms/diagnostic imaging , Carcinoma, Renal Cell/diagnostic imaging , Adenoma, Oxyphilic/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Diagnosis, Differential , Female , Middle Aged , Male , Aged , Adult , Sensitivity and Specificity , Retrospective Studies
18.
Br J Radiol ; 97(1158): 1169-1179, 2024 May 29.
Article in English | MEDLINE | ID: mdl-38688660

ABSTRACT

OBJECTIVES: This study aimed to develop a model to predict World Health Organization/International Society of Urological Pathology (WHO/ISUP) low-grade or high-grade clear cell renal cell carcinoma (ccRCC) using 3D multiphase enhanced CT radiomics features (RFs). METHODS: CT data of 138 low-grade and 60 high-grade ccRCC cases were included. RFs were extracted from four CT phases: non-contrast phase (NCP), corticomedullary phase, nephrographic phase, and excretory phase (EP). Models were developed using various combinations of RFs and subjected to cross-validation. RESULTS: There were 107 RFs extracted from each phase of the CT images. The NCP-EP model had the best overall predictive value (AUC = 0.78), but did not significantly differ from that of the NCP model (AUC = 0.76). By considering the predictive ability of the model, the level of radiation exposure, and model simplicity, the overall best model was the Conventional image and clinical features (CICFs)-NCP model (AUC = 0.77; sensitivity 0.75, specificity 0.69, positive predictive value 0.85, negative predictive value 0.54, accuracy 0.73). The second-best model was the NCP model (AUC = 0.76). CONCLUSIONS: Combining clinical features with unenhanced CT images of the kidneys seems to be optimal for prediction of WHO/ISUP grade of ccRCC. This noninvasive method may assist in guiding more accurate treatment decisions for ccRCC. ADVANCES IN KNOWLEDGE: This study innovatively employed stability selection for RFs, enhancing model reliability. The CICFs-NCP model's simplicity and efficacy mark a significant advancement, offering a practical tool for clinical decision-making in ccRCC management.


Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Neoplasm Grading , Tomography, X-Ray Computed , Humans , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/pathology , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/pathology , Tomography, X-Ray Computed/methods , Male , Middle Aged , Female , Aged , World Health Organization , Retrospective Studies , Predictive Value of Tests , Adult , Imaging, Three-Dimensional/methods , Sensitivity and Specificity , Aged, 80 and over , Radiomics
19.
Nucl Med Commun ; 45(7): 601-611, 2024 Jul 01.
Article in English | MEDLINE | ID: mdl-38686492

ABSTRACT

AIM: To evaluate relationship between metabolic PET metabolic parameters and size of the primary tumor, various histopathological subtypes of renal cell carcinoma (RCC) and Fuhrman grade of the tumors. MATERIAL AND METHODS: Retrospective analysis of 93 biopsy-proven RCC patients who underwent pretreatment flourine 18 flourodeoxyglucose PET/computed tomography ( 18 F FDG PET/CT) was performed. Quantitative PET parameters, size of the primary tumor, histopathological subtypes and Fuhrman grades of the tumor were extracted. We tried to assess if there was any significant difference in the metabolic patterns of various histopathological subtypes of RCCs, Fuhrman grade of the tumors and size of the primary tumor. RESULTS: A significant correlation was noted between the size of primary tumor and maximum standardized uptake value (SUV max ), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) ( P  < 0.01, P  < 0.001 and P  < 0.001, respectively). SUV max values correlated significantly with the histopathological subtype ( P  < 0.001). Further sub-analyses was also done by segregating the patients into Low grade (Fuhrman grade 1 and 2) vs. High grade (Fuhrman grade 3 and 4). SUV max , MTV and TLG were significantly different between high grade vs. low grade tumors. ROC analysis yielded cut off values for SUV max , MTV and TLG to differentiate between high grade from low grade tumors. CONCLUSION: FDG PET/CT with the use of metabolic PET parameters can differentiate between different histopathological subtypes of RCC. Incorporation of metabolic parameters into clinical practice can potentially noninvasively identify patients with low-grade vs. high-grade RCC.


Subject(s)
Carcinoma, Renal Cell , Fluorodeoxyglucose F18 , Kidney Neoplasms , Neoplasm Grading , Positron Emission Tomography Computed Tomography , Humans , Carcinoma, Renal Cell/diagnostic imaging , Carcinoma, Renal Cell/metabolism , Carcinoma, Renal Cell/pathology , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/metabolism , Kidney Neoplasms/pathology , Male , Female , Middle Aged , Retrospective Studies , Aged , Adult , Aged, 80 and over , Diagnosis, Differential , Tumor Burden
SELECTION OF CITATIONS
SEARCH DETAIL
...