Lymph Node Assessment in Prostate Cancer

Lennartz, Simon; Täger, Philipp; Zopfs, David; Iuga, Andra-Iza; Reimer, Robert Peter; Zäske, Charlotte; Hokamp, Nils Große; Maintz, David; Heidenreich, Axel; Drzezga, Alexander; Kobe, Carsten; Persigehl, Thorsten

doi:10.1097/rlu.0000000000003496

Cited by 11 publications

(6 citation statements)

References 25 publications

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“…It has been shown that the average iodine density of larger tumors is significantly lower than that of the smaller ones [ 25 ], which is inconsistent with the results of our study. There were no significant correlations between derived parameters of IC and WC with tumor diameter except NWCD 3 .…”

Section: Discussioncontrasting

confidence: 99%

Effect of spectral CT on tumor microvascular angiogenesis in renal cell carcinoma

Zhang

Qiu

et al. 2021

BMC Cancer

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Background To examine the value of energetic-spectrum computed tomography (spectral CT) quantitative parameters in renal cell carcinoma (RCC) microvascular angiogenesis. Methods The authors evaluated 32 patients with pathologically confirmed RCC who underwent triple-phase contrast-enhanced CT with spectral CT imaging mode from January 2017 to December 2019. Quantitative parameters include parameters derived from iodine concentration (IC) and water concentration (WC) of 120 keV monochromatic images. All specimens were evaluated including the microvascular density (MVD), microvascular area (MVA) and so on. The correlation between IC and WC (including average values and random values) with microvascular parameters were analyzed with Pearson or Spearman rank correlation coefficients. Results The MVD of all tumors was 26.00 (15.00–43.75) vessels per field at × 400 magnification. The MVD of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical phase, WCD1, WCD2, NWCD2 and ICD1 (Spearman rank correlation coefficients, r range, 0.362–0.533; all p < 0.05). The MVA of all tumors was (16.16 ± 8.98) % per field at × 400 magnification. The MVA of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical, mean WC and mean NWC in renal parenchymal phase, WCD1, WCD2, WCD3, NWCD2, and NWCD3 (Pearson or Spearman rank correlation coefficients, r range, 0.357–0.576; all p < 0.05). Microvascular grading correlated positively with the mean NWC, mean NIC and random NIC in renal cortical phase, mean NWC in renal parenchymal phase, NWCD2, WCD3, NWCD3, NICD2 and NICD3 (Spearman rank correlation coefficients, r range, 0.367–0.520; all p < 0.05). As for tumor diameter (55.19 ± 19.15), μm, only NWCD3 was associated with it (Spearman rank correlation coefficients, r = 0.388; p < 0.05). Conclusions ICD and WCD of spectral CT have a potential for evaluating RCC microvascular angiogenesis. MVD, MVA and microvascular grade showed moderate positive correlation with ICD and WCD. ICD displayed more relevant than that of WCD. The parameters of renal cortical phase were the best in three phases. NICD and NWCD manifested stronger correlation with microvascular parameters than that of ICD and WCD.

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Section: Discussioncontrasting

confidence: 99%

Effect of spectral CT on tumor microvascular angiogenesis in renal cell carcinoma

Zhang

Qiu

et al. 2021

BMC Cancer

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“…Over recent years, DECT post-processing techniques and radiomics have become rapidly evolving research fields in cancer research, leading to improved non-invasive lesion characterization [ 16 , 32 , 33 ]. The ability of DECT to provide information about lymph node characterization beyond subjective evaluation and simple attenuation measurements has been validated in prior studies [ 13 – 15 ]. In a study from 2018, the authors investigated the potential of DECT iodine quantification to differentiate lymphoma, lymph node metastases and benign lymph nodes [ 13 ].…”

Section: Discussionmentioning

confidence: 99%

“…Thus, iodine quantification provides information about the local content of iodine contrast agent and can serve as a surrogate for tumor vascularity [ 11 , 12 ]. The potential of DECT-based iodine quantification to differentiate benign and malignant lymph nodes has been assessed in recent studies [ 13 – 15 ].…”

Section: Introductionmentioning

confidence: 99%

“…Radiomics features capture tissue characteristics such as heterogeneity and shape and may be used for the prediction of tumor subtypes, treatment response and clinical outcome [ 16 , 17 ]. The potential of DECT material decomposition and radiomics features for the characterization of benign and malignant lymph nodes including lymphoma has been assessed in recent studies [ 14 , 15 , 18 , 19 ]. However, the combined application of both DECT and radiomics features for stratification of lymphoma has not been evaluated.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of radiomics models and dual-energy material decomposition to decipher abdominal lymphoma in contrast-enhanced CT

et al. 2023

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Purpose The radiologists’ workload is increasing, and computational imaging techniques may have the potential to identify visually unequivocal lesions, so that the radiologist can focus on equivocal and critical cases. The purpose of this study was to assess radiomics versus dual-energy CT (DECT) material decomposition to objectively distinguish visually unequivocal abdominal lymphoma and benign lymph nodes. Methods Retrospectively, 72 patients [m, 47; age, 63.5 (27–87) years] with nodal lymphoma (n = 27) or benign abdominal lymph nodes (n = 45) who had contrast-enhanced abdominal DECT between 06/2015 and 07/2019 were included. Three lymph nodes per patient were manually segmented to extract radiomics features and DECT material decomposition values. We used intra-class correlation analysis, Pearson correlation and LASSO to stratify a robust and non-redundant feature subset. Independent train and test data were applied on a pool of four machine learning models. Performance and permutation-based feature importance was assessed to increase the interpretability and allow for comparison of the models. Top performing models were compared by the DeLong test. Results About 38% (19/50) and 36% (8/22) of the train and test set patients had abdominal lymphoma. Clearer entity clusters were seen in t-SNE plots using a combination of DECT and radiomics features compared to DECT features only. Top model performances of AUC = 0.763 (CI = 0.435–0.923) were achieved for the DECT cohort and AUC = 1.000 (CI = 1.000–1.000) for the radiomics feature cohort to stratify visually unequivocal lymphomatous lymph nodes. The performance of the radiomics model was significantly (p = 0.011, DeLong) superior to the DECT model. Conclusions Radiomics may have the potential to objectively stratify visually unequivocal nodal lymphoma versus benign lymph nodes. Radiomics seems superior to spectral DECT material decomposition in this use case. Therefore, artificial intelligence methodologies may not be restricted to centers with DECT equipment.

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“…This can facilitate material separation and quantitative analysis, to provide information on the different physical properties of all the tissues. Signi cant information on tissues and lesions can be derived by processing and analyzing these data [6,7] . For instance, spectral CT showed clear and sharp blood vessels and could also display more numbers of collateral vessels and arterioles at the distal end of the feeding arteries [8] .…”

Section: Introductionmentioning

confidence: 99%

Application of spectral CT in D3 lymphadenectomy under a laparoscope for treating right-sided colorectal cancer

Zhang,

Shi,

Qiao

et al. 2023

Preprint

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Objective: The positive aspects of using spectral CT in D3 lymphadenectomy under a laparoscope for the treatment of right-sided colorectal cancer (CRC) are discussed. Methods: We enrolled right-sided CRC patients (n=40) and preoperative examinations by spectral CT revealed no distant metastasis. The pattern and orientation of the colon, tumor location, the positional correlation of lymph nodes and vessels, and the anatomy and alterations of key blood vessels were probed. Further, the relative spatial positions of different vessels were investigated using the 3D reconstruction technology of spectral CT. Finally, the results were compared with those observed during surgery. Results: Examination using spectral CT, 3D reconstruction, and data analysis were performed for all 40 cases with successful completion of all the surgeries. Overall, the pattern and orientation of the colon, tumor location, the relation of lymph nodes and blood vessels, and the anatomy and variation of key blood vessels observed during surgery were identical to the 3D reconstructed images obtained by spectral CT before the surgery. This suggests that the accuracy of 3D reconstruction reached 100%. Conclusion: The application of the 3D reconstruction technology of spectral CT before D3 lymphadenectomy under a laparoscope can help to visualize and determine the correlation between the location of a lesion and the anatomical location, hence assisting the surgery.

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Lymph Node Assessment in Prostate Cancer

Cited by 11 publications

References 25 publications

Effect of spectral CT on tumor microvascular angiogenesis in renal cell carcinoma

Effect of spectral CT on tumor microvascular angiogenesis in renal cell carcinoma

Comparison of radiomics models and dual-energy material decomposition to decipher abdominal lymphoma in contrast-enhanced CT

Application of spectral CT in D3 lymphadenectomy under a laparoscope for treating right-sided colorectal cancer

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