Abstract
Purpose: In the treatment of Head-and-Neck Squamous Cell Carcinoma (HNSCC), the early prediction of residual malignant lymph nodes (LNs) is currently required. Here, we investigated the potential of a multi-modal characterization (combination of CT, T2w-MRI and DW-MRI) at baseline and at mid-treatment, based on texture analysis (TA), for the early prediction of LNs response to chemo-radiotherapy (CRT). Methods: 30 patients with pathologically confirmed HNSCC treated with CRT were considered. All patients underwent a planning CT and two serial MR examinations (including T2w and DW images), one before and one at mid-CRT. For each patient the largest malignant LN was selected and within each LN, morphological and textural features were estimated from T2w-MRI and CT, besides a quantification of the apparent diffusion coefficient (ADC) from DW-MRI. After a median follow-up time of 26.6. months, 19 LNs showed regional control, while 11 LNs showed. regional failure at a median time of 4.6. months. Linear discriminant analysis was used to test the accuracy of the image-based features in predicting the final response. Results: Pre-treatment features showed higher predictive power than mid-CRT features, the ADC having the highest accuracy (80%); CT-based indices were found not predictive. When ADC was combined with TA, the classification performance increased (accuracy = 82.8%). If only T2w-MRI features were considered, the best combination of pre-CRT indices and their variation reached an equivalent accuracy (81.8%). Conclusion: Our results may suggest that TA on T2w-MRI and ADC can be combined together to obtain a more accurate prediction of response to CRT.
| Original language | English |
|---|---|
| Journal | Physica Medica |
| DOIs | |
| Publication status | Accepted/In press - Jun 13 2016 |
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Keywords
- DW-MRI
- Head-and-neck lymph-nodes
- T2w-MRI
- Texture analysis
ASJC Scopus subject areas
- Biophysics
- Radiology Nuclear Medicine and imaging
- Physics and Astronomy(all)
Cite this
Characterization of cervical lymph-nodes using a multi-parametric and multi-modal approach for an early prediction of tumor response to chemo-radiotherapy. / Scalco, Elisa; Marzi, Simona; Sanguineti, Giuseppe; Vidiri, Antonello; Rizzo, Giovanna.
In: Physica Medica, 13.06.2016.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Characterization of cervical lymph-nodes using a multi-parametric and multi-modal approach for an early prediction of tumor response to chemo-radiotherapy
AU - Scalco, Elisa
AU - Marzi, Simona
AU - Sanguineti, Giuseppe
AU - Vidiri, Antonello
AU - Rizzo, Giovanna
PY - 2016/6/13
Y1 - 2016/6/13
N2 - Purpose: In the treatment of Head-and-Neck Squamous Cell Carcinoma (HNSCC), the early prediction of residual malignant lymph nodes (LNs) is currently required. Here, we investigated the potential of a multi-modal characterization (combination of CT, T2w-MRI and DW-MRI) at baseline and at mid-treatment, based on texture analysis (TA), for the early prediction of LNs response to chemo-radiotherapy (CRT). Methods: 30 patients with pathologically confirmed HNSCC treated with CRT were considered. All patients underwent a planning CT and two serial MR examinations (including T2w and DW images), one before and one at mid-CRT. For each patient the largest malignant LN was selected and within each LN, morphological and textural features were estimated from T2w-MRI and CT, besides a quantification of the apparent diffusion coefficient (ADC) from DW-MRI. After a median follow-up time of 26.6. months, 19 LNs showed regional control, while 11 LNs showed. regional failure at a median time of 4.6. months. Linear discriminant analysis was used to test the accuracy of the image-based features in predicting the final response. Results: Pre-treatment features showed higher predictive power than mid-CRT features, the ADC having the highest accuracy (80%); CT-based indices were found not predictive. When ADC was combined with TA, the classification performance increased (accuracy = 82.8%). If only T2w-MRI features were considered, the best combination of pre-CRT indices and their variation reached an equivalent accuracy (81.8%). Conclusion: Our results may suggest that TA on T2w-MRI and ADC can be combined together to obtain a more accurate prediction of response to CRT.
AB - Purpose: In the treatment of Head-and-Neck Squamous Cell Carcinoma (HNSCC), the early prediction of residual malignant lymph nodes (LNs) is currently required. Here, we investigated the potential of a multi-modal characterization (combination of CT, T2w-MRI and DW-MRI) at baseline and at mid-treatment, based on texture analysis (TA), for the early prediction of LNs response to chemo-radiotherapy (CRT). Methods: 30 patients with pathologically confirmed HNSCC treated with CRT were considered. All patients underwent a planning CT and two serial MR examinations (including T2w and DW images), one before and one at mid-CRT. For each patient the largest malignant LN was selected and within each LN, morphological and textural features were estimated from T2w-MRI and CT, besides a quantification of the apparent diffusion coefficient (ADC) from DW-MRI. After a median follow-up time of 26.6. months, 19 LNs showed regional control, while 11 LNs showed. regional failure at a median time of 4.6. months. Linear discriminant analysis was used to test the accuracy of the image-based features in predicting the final response. Results: Pre-treatment features showed higher predictive power than mid-CRT features, the ADC having the highest accuracy (80%); CT-based indices were found not predictive. When ADC was combined with TA, the classification performance increased (accuracy = 82.8%). If only T2w-MRI features were considered, the best combination of pre-CRT indices and their variation reached an equivalent accuracy (81.8%). Conclusion: Our results may suggest that TA on T2w-MRI and ADC can be combined together to obtain a more accurate prediction of response to CRT.
KW - DW-MRI
KW - Head-and-neck lymph-nodes
KW - T2w-MRI
KW - Texture analysis
UR - http://www.scopus.com/inward/record.url?scp=84994852899&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84994852899&partnerID=8YFLogxK
U2 - 10.1016/j.ejmp.2016.09.003
DO - 10.1016/j.ejmp.2016.09.003
M3 - Article
JO - Physica Medica
JF - Physica Medica
SN - 1120-1797
ER -