Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Protocol, Support, and Funding
2.2. Quantitative Diffusion Phantom for In Vitro Study
2.3. Subjects for In Vivo Study
2.4. MR Imaging
2.4.1. MR Imaging for In Vitro Study
2.4.2. MR Imaging for In Vivo Study
2.5. Image Analysis
2.5.1. Image Analysis for In Vitro Study
2.5.2. Image Analysis for In Vivo Study
2.6. Statistical Analysis
2.6.1. In Vitro Study
2.6.2. In Vivo Study
3. Results
3.1. In Vitro Study
3.2. In Vivo Study
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
SCC | squamous cell carcinoma |
MRI | Magnetic resonance imaging |
DWI | Diffusion-weighted imaging |
EPI | Echo planar imaging |
ADC | apparent diffusion coefficient |
FASE | fast advanced spin-echo |
DLR | Deep learning reconstruction |
QIBA | Quantitative imaging biomarker alliance |
PVP | Polyvinylpyrrolidone |
FSE | Fast spin-echo |
TR | Repetition time |
TE | Echo time |
FOV | Field of view |
FA | Flip angle |
NEX | number of excitations |
SNR | Signal-to-noise ratio |
DR | Deformation ratio |
ROC | receiver operating characteristic |
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Gender | Male | 30 | |
Female | 28 | ||
Age | Male | Mean: 62.8, range: 12 to 89 years old | |
Female | Mean: 58.2, range: 17 to 93 years old | ||
Histology | Malignant tumors | Nasopharyngeal cancer | 1 |
Oropharyngeal cancer | 3 | ||
Hypopharyngeal cancer | 4 | ||
Oral cancer | 7 | ||
Laryngeal cancer | 5 | ||
Maxillary sinus cancer | 4 | ||
Thyroid cancer | 1 | ||
Follicular cell lymphoma | 1 | ||
Benign lesions | Venous malformation | 2 | |
Nasopharyngeal adenoid hypertrophy | 1 | ||
Pleomorphic adenoma of parotid gland | 7 | ||
Warthin tumor of parotid gland | 4 | ||
Parotid gland | 1 | ||
Sjogren syndrome | 2 | ||
Sarcoidosis | 1 | ||
Ranula | 1 | ||
Thyroglossal duct cyst | 1 | ||
Second brachial cleft cyst | 1 | ||
Benign follicular tumor thyroid | 2 | ||
Benign neurogenic tumor | 4 | ||
Calcifying epithelial odontogenic tumor | 1 | ||
Odontogenic keratocyst | 2 | ||
Benign lymphadenopathy | 1 | ||
Unknown benign mandibular lesion | 1 |
Protocol | T2WI | DWI by EPI | DWI by FASE |
---|---|---|---|
Sequence | Multi-slice FSE | Single-shot EPI | Single-shot FASE |
Fat suppression | N/A | STIR | STIR |
Repetition time (TR: ms) | 4500–5300 | 6800–7964 | 26,628–30,000 |
Echo time (TE: ms) | 93.5 | 78 | 78 |
Inversion Time (TI: ms) | N/A | 240 | 240 |
Echo train length (ETL) | 19 | - | - |
Echo spacing (ETS: ms) | 8.5 | 0.52 | 0.8 |
Acquisition matrix | 352 × 352 | 136 × 80 | 136 × 80 |
Reconstruction matrix | 704 × 704 | 272 × 260 | 272 × 260 |
Reconstruction matrix size (mm) | 0.3 × 0.3 | 0.9 × 0.9 | 0.9 × 0.9 |
Field of view (FOV: mm) | 200 × 200 | 250 × 240 | 250 × 240 |
Number of phase wraps | 1.8 | N/A | N/A |
Slice thickness (mm) | 3 | 3 | 3 |
Number of Slices | 40–47 | 40–47 | 40–47 |
Number of excitations (NEX) | 1 | 2 | 3 |
Flip angle (degree) | 90/160 | 90/180 | 90/140 |
Phase encoding direction | RL | AP | AP |
Imaging plane | Axial | Axial | Axial |
Acceleration method | Compressed SPEEDER | SPEEDER | SPEEDER |
Reduction factor | 3 | 2.5 | 2.5 |
b-value (s/mm2) | - | 0.800 | 0.800 |
Acquisition time (s) | 109 (108–162) | 206 (204–249) | 420 (408–481) |
EPI without DLR | EPI with DLR | FASE without DLR | FASE with DLR | |||||
---|---|---|---|---|---|---|---|---|
ρ | p | ρ | p | ρ | p | ρ | p | |
EPI without DLR | N/A | N/A | 0.99 | <0.0001 | 0.96 | <0.0001 | 0.92 | <0.0001 |
EPI with DLR | – | – | N/A | N/A | 0.96 | <0.0001 | 0.93 | <0.0001 |
FASE without DLR | – | – | – | – | N/A | N/A | 0.92 | <0.0001 |
FASE with DLR | – | – | – | – | – | – | N/A | N/A |
Concentration of Phantom [%] | Standard Reference [×10−3 mm2/s] | Mean Difference ± SD | |||||
---|---|---|---|---|---|---|---|
EPI without DLR | EPI with DLR | p Value | FASE without DLR | FASE with DLR | p Value | ||
0 | 1.127 | 0.011 ± 0.034 | 0.012 ± 0.034 | 0.7962 | 0.033 ± 0.077 | 0.132 ± 0.056 | <0.0001 |
10 | 0.843 | 0.000 ± 0.045 | 0.000 ± 0.044 | 0.9941 | 0.052 ± 0.098 | 0.163 ± 0.077 | <0.0001 |
20 | 0.607 | 0.015 ± 0.028 | 0.016 ± 0.029 | 0.8303 | 0.042 ± 0.104 | 0.182 ± 0.074 | <0.0001 |
30 | 0.403 | 0.035 ± 0.083 | 0.042 ± 0.084 | 0.6520 | 0.031 ± 0.154 | 0.252 ± 0.103 | <0.0001 |
40 | 0.248 | 0.113 ± 0.084 | 0.105 ± 0.080 | 0.6414 | 0.070 ± 0.137 | 0.057 ± 0.158 | 0.0005 |
50 | 0.128 | 0.031 ± 0.034 | 0.027 ± 0.033 | 0.5493 | 0.013 ± 0.047 | 0.037 ± 0.052 | 0.0002 |
Number of Cases | EPI without DLR | EPI with DLR | FASE without DLR | FASE with DLR | |
---|---|---|---|---|---|
Overall tumors | 58 | 5.1 ± 2.6 | 5.4 ± 2.8 | 4.3 ± 1.6 | 5.6 ± 2.4 * |
Spinal cord | 58 | 8.7 ± 6.2 | 8.7 ± 5.7 | 7.0 ± 3.1 | 9.3 ± 3.8 |
Pharynx and larynx | 15 | 5.6 ± 3.0 | 5.9 ± 3.1 | 5.1 ± 2.3 | 7.0 ± 3.1 |
Oral cavity and mandibular | 12 | 4.8 ± 2.7 | 5.6 ± 3.0 | 3.6 ± 1.2 | 5.0 ± 1.9 |
Salivary glands | 15 | 3.9 ± 1.5 | 4.0 ± 1.7 | 4.0 ± 1.2 | 4.3 ± 1.3 |
Others | 16 | 5.3 ± 2.2 | 6.2 ± 3.0 | 4.4 ± 1.1 | 5.9 ± 2.3 |
Number of Cases | EPI without DLR | EPI with DLR | FASE without DLR | FASE with DLR | |
---|---|---|---|---|---|
Overall tumors | 58 | 0.36 ± 0.34 | 0.37 ± 0.33 | 0.19 ± 0.13 *,** | 0.13 ± 0.17 *,** |
Spinal cord | 58 | 0.31 ± 0.30 | 0.34 ± 0.30 | 0.23 ± 0.14 | 0.13 ± 0.13 *,** |
Pharynx and larynx | 15 | 0.32 ± 0.30 | 0.33 ± 0.92 | 0.14 ± 0.10 | 0.10 ± 0.10 *,** |
Oral cavity and mandibular | 12 | 0.40 ± 0.37 | 0.47 ± 0.31 | 0.22 ± 0.18 | 0.06 ± 0.05 *,** |
Salivary glands | 15 | 0.31 ± 0.45 | 0.35 ± 0.48 | 0.17 ± 0.08 | 0.12 ± 0.12 |
Others | 16 | 0.42 ± 0.28 | 0.36 ± 0.24 | 0.22 ± 0.19 | 0.22 ± 0.26 |
Method | ADC [×10−3 mm2/s] (Mean ± SD) | |
---|---|---|
Benign | Malignant | |
EPI without DLR | 1.63 ± 0.53 | 1.10 ± 0.17 * |
EPI with DLR | 1.69 ± 0.57 | 1.16 ± 0.21 * |
FASE without DLR | 1.82 ± 0.56 | 1.22 ± 0.28 * |
FASE with DLR | 1.82 ± 0.56 | 1.21 ± 0.29 * |
Feasible Threshold Value (×10−3mm2/s) | SE (%) | SP (%) | PPV (%) | NPV (%) | AC (%) | |
---|---|---|---|---|---|---|
EPI with DLR | 1.3 | 84.6 (22/26) | 81.3 (26/32) | 78.6 (22/28) | 86.7 (26/30) | 82.8 (48/58) |
EPI without DLR | 1.2 | 76.9 (20/26) | 84.4 (27/32) | 80.0 (20/25) | 81.8 (27/33) | 81.0 (47/58) |
FASE with DLR | 1.4 | 80.8 (21/26) | 81.3 (26/32) | 77.8 (21/27) | 83.9 (26/31) | 81.0 (47/58) |
FASE without DLR | 1.5 | 88.5 (23/26) | 78.1 (25/32) | 76.7 (23/30) | 89.3 (25/28) | 82.8 (48/58) |
Feasible Threshold Value (×10−3mm2/s) | SE (%) | SP (%) | PPV (%) | NPV (%) | AC (%) | |
---|---|---|---|---|---|---|
EPI with DLR | 1.4 | 92.3 (24/26) | 76.9 (20/26) | 80.0 (24/30) | 90.9 (20/22) | 84.6 (44/52) |
EPI without DLR | 1.3 | 88.5 (23/26) | 84.6 (22/26) | 85.2 (23/27) | 88.0 (22/25) | 86.5 (45/52) |
FASE with DLR | 1.5 | 88.5 (23/26) | 80.8 (21/26) | 82.1 (23/28) | 87.5 (21/24) | 84.6 (44/52) |
FASE without DLR | 1.5 | 88.5 (23/26) | 88.5 (23/26) | 88.5 (23/26) | 88.5 (23/26) | 88.5 (46/52) |
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Ikeda, H.; Ohno, Y.; Yamamoto, K.; Murayama, K.; Ikedo, M.; Yui, M.; Kumazawa, Y.; Shimamura, Y.; Takagi, Y.; Nakagaki, Y.; et al. Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors. Cancers 2024, 16, 1714. https://doi.org/10.3390/cancers16091714
Ikeda H, Ohno Y, Yamamoto K, Murayama K, Ikedo M, Yui M, Kumazawa Y, Shimamura Y, Takagi Y, Nakagaki Y, et al. Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors. Cancers. 2024; 16(9):1714. https://doi.org/10.3390/cancers16091714
Chicago/Turabian StyleIkeda, Hirotaka, Yoshiharu Ohno, Kaori Yamamoto, Kazuhiro Murayama, Masato Ikedo, Masao Yui, Yunosuke Kumazawa, Yurika Shimamura, Yui Takagi, Yuhei Nakagaki, and et al. 2024. "Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors" Cancers 16, no. 9: 1714. https://doi.org/10.3390/cancers16091714
APA StyleIkeda, H., Ohno, Y., Yamamoto, K., Murayama, K., Ikedo, M., Yui, M., Kumazawa, Y., Shimamura, Y., Takagi, Y., Nakagaki, Y., Hanamatsu, S., Obama, Y., Ueda, T., Nagata, H., Ozawa, Y., Iwase, A., & Toyama, H. (2024). Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors. Cancers, 16(9), 1714. https://doi.org/10.3390/cancers16091714