Optimization of Preoperative Lymph Node Staging in Patients with Muscle-Invasive Bladder Cancer Using Radiomics on Computed Tomography

Starmans, Martijn P.A.; Ho, Li Shen; Smits, F. Jasmijn; Beije, Nick; Kruijff, Inge de; Jong, Joep J. de; Somford, Diederik M.; Boevé, Egbert R.; Slaa, E. te; Cauberg, Evelyne C. C.; Klaver, Sjoerd; Heijden, Antoine G. van der; Wijburg, Carl; Luijtgaarden, Addy C.M. van de; Melick, Harm H.E. van; Cauffman, Ella; Vries, Peter de; Jacobs, Rebecca; Niessen, Wiro J.; Visser, Jacob J.; Klein, Stefan; Boormans, Joost L.; Veldt, Astrid A.M. van der

doi:10.3390/jpm12050726

Cited by 2 publications

(2 citation statements)

References 63 publications

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“…In fact, to characterize preoperatively the N status with more precision would help not only CC patients but also several other oncologic districts. For instance, an interesting study conducted on bladder cancer by Starmans M P A et al [26] showed how radiomics showed no improvement in the discrimination between N0 and N+. Among the possible explanations found by the authors, there is a bias in the N+ feature characteristics that also includes benign lymph nodes due to the lack of direct labelling on the pathology, and then there is the possibility of missing pathologic lymph nodes measuring less than 3 mm due to the intrinsic limits of the CT slice thickness.…”

Section: Discussionmentioning

confidence: 99%

Is CT Radiomics Superior to Morphological Evaluation for pN0 Characterization? A Pilot Study in Colon Cancer

Zerunian,

Nacci,

Caruso

et al. 2024

Cancers

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The aim of this study was to compare CT radiomics and morphological features when assessing benign lymph nodes (LNs) in colon cancer (CC). This retrospective study included 100 CC patients (test cohort) who underwent a preoperative CT examination and were diagnosed as pN0 after surgery. Regional LNs were scored with a morphological Likert scale (NODE-SCORE) and divided into two groups: low likelihood (LLM: 0–2 points) and high likelihood (HLM: 3–7 points) of malignancy. The T-test and the Mann–Whitney test were used to compare 107 radiomic features extracted from the two groups. Radiomic features were also extracted from primary lesions (PLs), and the receiver operating characteristic (ROC) was used to test a LN/PL ratio when assessing the LN’s status identified with radiomics and with the NODE-SCORE. An amount of 337 LNs were divided into 167 with LLM and 170 with HLM. Radiomics showed 15/107 features, with a significant difference (p < 0.02) between the two groups. The comparison of selected features between 81 PLs and the corresponding LNs showed all significant differences (p < 0.0001). According to the LN/PL ratio, the selected features recognized a higher number of LNs than the NODE-SCORE (p < 0.001). On validation of the cohort of 20 patients (10 pN0, 10 pN2), significant ROC curves were obtained for LN/PL busyness (AUC = 0.91; 0.69–0.99; 95% C.I.; and p < 0.001) and for LN/PL dependence entropy (AUC = 0.76; 0.52–0.92; 95% C.I.; and p = 0.03). The radiomics ratio between CC and LNs is more accurate for noninvasively discriminating benign LNs compared to CT morphological features.

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Section: Discussionmentioning

confidence: 99%

Is CT Radiomics Superior to Morphological Evaluation for pN0 Characterization? A Pilot Study in Colon Cancer

Zerunian,

Nacci,

Caruso

et al. 2024

Cancers

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“…Starmans et al extracted 564 radiomics features after manual segmentation of lymph nodes in 209 patients with clinically T2-T4aN0-N1M0 muscle-invasive bladder cancer, of whom preoperative CT scans and pathology reports were available [ 7 ]. Among the included patients, 50 patients were pathologically proven node-negative at radical cystectomy.…”

Section: Discussionmentioning

confidence: 99%

Radiomics vs radiologist in bladder and renal cancer. Results from a systematic review

2023

Cent european J Urol

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Introduction Radiomics in uro-oncology is a rapidly evolving science proving to be a novel approach for optimizing the analysis of massive data from medical images to provide auxiliary guidance in clinical issues. This scoping review aimed to identify key aspects wherein radiomics can potentially improve the accuracy of diagnosis, staging, and grading of renal and bladder cancer. Material and methods A literature search was performed in June 2022 using PubMed, Embase, and Cochrane Central Controlled Register of Trials. Studies were included if radiomics were compared with radiological reports only. Results Twenty-two papers were included, 4 were pertinent to bladder cancer, and 18 to renal cancer. Radiomics outperforms the visual assessment by radiologists in contrast-enhanced computed tomography (CECT) to predict muscle invasion but are equivalent to CT reporting by radiologists in predicting lymph node metastasis. Magnetic resonance imaging (MRI) radiomics outperforms radiological reporting for lymph node metastasis. Radiomics perform better than radiologists reporting the probability of renal cell carcinoma, improving interreader concordance and performance. Radiomics also helps to determine differences in types of renal pathology and between malignant lesions from their benign counterparts. Radiomics can be helpful to establish a model for differentiating low-grade from high-grade clear cell renal cancer with high accuracy just from contrast-enhanced CT scans. Conclusions Our review shows that radiomic models outperform individual reports by radiologists by their ability to incorporate many more complex radiological features.

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Optimization of Preoperative Lymph Node Staging in Patients with Muscle-Invasive Bladder Cancer Using Radiomics on Computed Tomography

Cited by 2 publications

References 63 publications

Is CT Radiomics Superior to Morphological Evaluation for pN0 Characterization? A Pilot Study in Colon Cancer

Is CT Radiomics Superior to Morphological Evaluation for pN0 Characterization? A Pilot Study in Colon Cancer

Radiomics vs radiologist in bladder and renal cancer. Results from a systematic review

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