Radiomics Analyses to Predict Histopathology in Patients with Metastatic Testicular Germ Cell Tumors before Post-Chemotherapy Retroperitoneal Lymph Node Dissection
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
- (a)
- Residual nodal size exceeding 1 cm, as determined through transverse axial dimension on CT imaging, following frontline cisplatin-based chemotherapy for metastatic non-seminomatous TGCT.
- (b)
- Residual nodal size exceeds 3 cm in cases of seminoma.
- (c)
- Residual nodal size measuring less than 1 cm in patients exhibiting intermediate or poor prognosis or pure teratoma in the primary orchiectomy specimen.
- (a)
- Lack of contrast-enhanced CT imaging data post-chemotherapy.
- (b)
- Inadequate image quality is attributable to motion artifacts.
- (c)
- CT scans were conducted at external institutions.
- (d)
- Images displaying a tumor size exceeding 15 cm.
- (e)
- Patients without comprehensive clinical data, pre-operative and intraoperative records, or patients who underwent primary RPLND.
2.2. Segmentation
2.3. Radiomics Feature Extraction
- diagnostics_Configuration_Settings.additionalInfo (True)
- Configuration_Settings.binWidth (25.0)
- Configuration_Settings.distancesforce2Ddimension (0)
- Configuration_Settings.interpolator (sitkBSpline).label (1.0)
- minimumROIDimensions (2)
- minimumROISize (null)
- normalize (false)
- diagnostics_Configuration_Settings.normalizeScale (1)
- diagnostics_Configuration_Settings.padDistance (5)
- diagnostics_Configuration_Settings.preCrop (false)
- diagnostics_Configuration_Settings.removeOutliers (null)
- diagnostics_Configuration_Settings.resampledPixelSpacing (null)
- diagnostics_Configuration_Settings.resegmentRange (null)
- diagnostics_Configuration_Settings.symmetricalGLCM (true)
2.4. Machine Learning Pipeline
2.4.1. Minority Classes Oversampling
2.4.2. Feature Reduction and Selection
- In the event that none of the features meet the first threshold (p < 0.005), we elevated the p-value threshold to the second level;
- If the second threshold remains unmet, we escalate the p-value to the third threshold;
- If none of the features satisfied the third threshold, all the features were given as input to the LASSO. The optimal lambda value was determined through a rigorous 10-fold cross-validation process.
2.4.3. Classification
2.4.4. Statistical Analyses
- Accuracy ((TP + TN)/(TP + TN + FP + FN))
- True Positive Rate (TPR) or sensitivity (TP/(TP + FN))
- True Negative Rate (TNR) or specificity (TN/(TN + FP))
- Positive Predicted Value (PPV) or precision (TP/(TP + FP))
- The area under the receiver operating characteristic curve (AUC)
- F-score
3. Results
3.1. Clinical Data
3.2. Feature Reduction and Selection
3.3. Classification
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Fibrosis/Necrosis | Teratoma | Viable Tumor | |
---|---|---|---|
Patient age at diagnosis (years) | 26.03 ± 6.46 | 23.94 ± 5.95 | 28.81 ± 11.66 |
Clinical stage (initial) | |||
I | 2/57 (3.51%) | 7/48 (14.6%) | 9/17 (52.9%) |
II | 20/57 (35.1%) | 16/48 (33.3%) | 6/17 (35.3%) |
III | 35/57 (61.4%) | 25/48 (52.1%) | 2/17 (11.7%) |
IGCCCG (initial) | |||
Good | 14/57 (24.6%) | 15/48 (31.2%) | 5/17 (29.4%) |
Intermediate | 26/57 (45.6%) | 19/48 (39.6%) | 7/17 (41.2%) |
Poor | 13/57 (22.8%) | 12/48 (25.0%) | 5/17 (29.4%) |
Missing information | 4/57 (7.0%) | 2/48 (4.2%) | 0/17 (0%) |
Serum Marker initial | |||
AFP | 2278 ± 7246 | 3639 ± 8481 | 5401 ± 9912 |
hCG | 3596 ± 12,899 | 13,436 ± 40,984 | 925 ± 1331 |
LDH | 1334 ± 2202 | 475 ± 384 | 546 ± 431 |
Primary histopathology | |||
Seminoma | 13/57 (22.8%) | 1/48 (0.021%) | 1/17 (0.059%) |
Non-seminoma | 44/57 (77.2%) | 47/48 (97.9%) | 16/17 (94.12%) |
Containing teratoma | 1/57 (0.017%) | 2/48 (0.042%) | 6/17 (35.3%) |
Without teratoma | 56/57 (98.2%) | 46/48 (95.8%) | 11/17 (64.7%) |
Type of pcRPLND | |||
Primary | 2/57 (3.5%) | 0/48 (0%) | 2/17 (11.8%) |
Standard | 8/57 (14.0%) | 10/48 (20.8%) | 0/17 (0%) |
Salvation | 41/57 (71.9%) | 28/48 (58.3%) | 6/17 (35.3%) |
Desperation | 5/57 (8.8%) | 9/48 (18.8%) | 5/17 (29.4%) |
Redo | 1/57 (1.8%) | 1/48 (2.1%) | 4/17 (23.5%) |
Serum marker prior pcRPLN | |||
AFP | 4.0 ± 3.5 | 6.6 ± 11.8 | 56.4 ± 91.2 |
hCG | 3.1 ± 18.5 | 5.3 ± 30.0 | 21.7 ± 83.8 |
LDH | 195 ± 105 | 247.7 ± 170.1 | 631.3 ± 1461.3 |
Side of orchiectomy | |||
Left | 31/57 (54.4%) | 30/48 (62.5%) | 7/17 (41.2%) |
Right | 19/57 (33.3%) | 16/48 (33.3%) | 9/17 (52.9%) |
Bilateral | 2/57 (3.5%) | 1/48 (2.1%) | 1/17 (5.9%) |
Extragonadal | 1/57 (1.8%) | 1/48 (2.1%) | 0/17 (0%) |
Deferred | 4/57 (7%) | 0/48 (0%) | 0/17 (0%) |
Damage to organs | |||
Yes | 4/57 (7%) | 2/48 (4.2%) | 1/17 (5.9%) |
No | 53/57 (93%) | 46/48 (95.8%) | 16/17 (94.1%) |
Vascular damage | |||
Yes | 4/57 (7%) | 7/48 (14.6%) | 2/17 (11.8%) |
No | 53/57 (93%) | 41/48 (85.4%) | 15/17 (88.2%) |
Volume (cm3) | 65.8 ± 132.4 | 505.4 ± 744.6 | 1156.6 ± 1689.3 |
Selected Features | p-Value |
---|---|
original_firstorder_Median | <<0.005 |
wavelet_LLH_glcm_MCC | <<0.005 |
original_firstorder_90Percentile | <<0.005 |
wavelet_LLL_glcm_Idmn | <<0.005 |
wavelet_LLL_firstorder_RootMeanSquared | <<0.005 |
wavelet_HHH_glszm_LargeAreaEmphasis | <<0.005 |
wavelet_HLH_glszm_SmallAreaEmphasis | <<0.005 |
wavelet_HHH_glszm_LargeAreaHighGrayLevelEmphasis | <<0.005 |
wavelet_HHH_firstorder_Median | <<0.005 |
wavelet_HLH_glrlm_RunLengthNonUniformityNormalized | <<0.005 |
wavelet_LHL_glrlm_RunLengthNonUniformityNormalized | <<0.005 |
wavelet_LLH_glcm_InverseVariance | <<0.005 |
wavelet_LLH_gldm_SmallDependenceEmphasis | <<0.005 |
wavelet_LLH_glszm_ZoneVariance | <<0.005 |
wavelet_LLL_firstorder_10Percentile | <<0.005 |
wavelet_HLH_glszm_LargeAreaEmphasis | <<0.005 |
wavelet_HHL_firstorder_Minimum | <<0.005 |
wavelet_LHL_glszm_SmallAreaHighGrayLevelEmphasis | <<0.005 |
wavelet_LHH_firstorder_Range | <<0.005 |
wavelet_LHH_glrlm_LongRunHighGrayLevelEmphasis | 0.0011 |
wavelet_LLH_firstorder_Minimum | 0.0017 |
wavelet_HHL_glszm_SizeZoneNonUniformityNormalized | 0.0018 |
wavelet_HHL_glrlm_RunLengthNonUniformityNormalized | 0.0021 |
wavelet_LLH_firstorder_Kurtosis | 0.0022 |
wavelet_LHH_ngtdm_Complexity | 0.0028 |
wavelet_HLH_glcm_MCC | 0.0040 |
original_glszm_LargeAreaEmphasis | 0.0041 |
wavelet_LHH_gldm_DependenceNonUniformity | 0.0042 |
wavelet_HLL_firstorder_10Percentile | 0.0045 |
wavelet_HHL_gldm_HighGrayLevelEmphasis | 0.0048 |
Image Type | Class | Number of Features |
---|---|---|
Original | Shape | 0 |
Original | First Order | 2 |
Original | Texture | 1 |
Wavelet | Shape | 0 |
Wavelet | First Order | 10 |
Wavelet | Texture | 17 |
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Scavuzzo, A.; Pasini, G.; Crescio, E.; Jimenez-Rios, M.A.; Figueroa-Rodriguez, P.; Comelli, A.; Russo, G.; Vazquez, I.C.; Araiza, S.M.; Ortiz, D.G.; et al. Radiomics Analyses to Predict Histopathology in Patients with Metastatic Testicular Germ Cell Tumors before Post-Chemotherapy Retroperitoneal Lymph Node Dissection. J. Imaging 2023, 9, 213. https://doi.org/10.3390/jimaging9100213
Scavuzzo A, Pasini G, Crescio E, Jimenez-Rios MA, Figueroa-Rodriguez P, Comelli A, Russo G, Vazquez IC, Araiza SM, Ortiz DG, et al. Radiomics Analyses to Predict Histopathology in Patients with Metastatic Testicular Germ Cell Tumors before Post-Chemotherapy Retroperitoneal Lymph Node Dissection. Journal of Imaging. 2023; 9(10):213. https://doi.org/10.3390/jimaging9100213
Chicago/Turabian StyleScavuzzo, Anna, Giovanni Pasini, Elisabetta Crescio, Miguel Angel Jimenez-Rios, Pavel Figueroa-Rodriguez, Albert Comelli, Giorgio Russo, Ivan Calvo Vazquez, Sebastian Muruato Araiza, David Gomez Ortiz, and et al. 2023. "Radiomics Analyses to Predict Histopathology in Patients with Metastatic Testicular Germ Cell Tumors before Post-Chemotherapy Retroperitoneal Lymph Node Dissection" Journal of Imaging 9, no. 10: 213. https://doi.org/10.3390/jimaging9100213
APA StyleScavuzzo, A., Pasini, G., Crescio, E., Jimenez-Rios, M. A., Figueroa-Rodriguez, P., Comelli, A., Russo, G., Vazquez, I. C., Araiza, S. M., Ortiz, D. G., Perez Montiel, D., Lopez Saavedra, A., & Stefano, A. (2023). Radiomics Analyses to Predict Histopathology in Patients with Metastatic Testicular Germ Cell Tumors before Post-Chemotherapy Retroperitoneal Lymph Node Dissection. Journal of Imaging, 9(10), 213. https://doi.org/10.3390/jimaging9100213