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Liu YC, Zhang X, Yang HN, Zhang L, Li D, Yang MQ, Wang NH, Wu YZ, Sui JD, Wang Y. Proposals for the delineation of neck clinical target volume for definitive Radiation therapy in patients with oral/ oropharyngeal squamous cell cancer based on lymph node distribution. Radiother Oncol 2024; 195:110225. [PMID: 38490491 DOI: 10.1016/j.radonc.2024.110225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 03/07/2024] [Accepted: 03/11/2024] [Indexed: 03/17/2024]
Abstract
PURPOSE/OBJECTIVE(S) To establish the distribution pattern of cervical lymph node metastasis (LNM) and propose optimized clinical target volume (CTV) boundaries specific to oral/ oropharyngeal squamous cell cancer (OSCC/OPSCC). MATERIALS/METHODS 531 patients with pathologically confirmed OSCC/OPSCC were enrolled from January 2013 to June 2022. Patients were stratified into two groups based on the minimal distance from the lesion's edge to the body's midline: ≤1 cm or > 1 cm. The geometric center of cervical metastatic LN was marked on a template CT. LN distribution probability maps were established. The relationships between the LN distribution and consensus guidelines were analyzed to propose modifications for CTV boundaries specific to OSCC/OPSCC. RESULTS A total of 1962 positive LNs were enrolled. Compared with the > 1 cm group, the ≤ 1 cm group has following feature tendencies: male smokers, younger, median organs, large gross lesion, infiltrative growth pattern, contralateral LNM. The most frequently involved level of LNM was ipsilateral II, but ipsilateral Ib had the highest involvement rate in the > 1 cm OSCC group. In addition, tongue cancer had a higher incidence of LN extranodal extension (ENE), which mainly distributes in ipsilateral level II. The skip metastasis was prone to from level III to Vb (3.5 %) in LN(+)/ENE (-), and level Ib to VIa (3.7 %) in LN(+)/ENE (+). Accordingly, we proposed the following modifications: 1. only including lateral and posterior margin of submandibular gland within 5 mm; 2. retracting posterior boundary of level II to front edge of levator scapula muscle, and descending the upper boundary to transverse process of C2 vertebra only for OSCC; 3. including posterior third of thyroglossal muscle or anterior edge of sternocleidomastoid muscle; 4. sparing level Va in case of only level II involvement; 5. including upper area of the thyroid cartilage plate in case of level Ib LN(+)/ENE (+); 6. sparing level VIIa is considered. CONCLUSION This is the first description of LN topographic spread patterns for OSCC/OPSCC. Modified CTV for prophylactic irradiation was proposed to spare the organs at risk and minimize adverse effects.
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Affiliation(s)
- Yun-Chang Liu
- College of Medicine, Chongqing University, Chongqing, China.
| | - Xin Zhang
- Radiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
| | - Hao-Nan Yang
- College of Medicine, Chongqing University, Chongqing, China
| | - Lu Zhang
- College of Medicine, Chongqing University, Chongqing, China
| | - Dan Li
- Radiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Meng-Qi Yang
- Radiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Nuo-Han Wang
- College of Medicine, Chongqing University, Chongqing, China
| | - Yong-Zhong Wu
- College of Medicine, Chongqing University, Chongqing, China; Radiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Jiang-Dong Sui
- College of Medicine, Chongqing University, Chongqing, China; Radiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
| | - Ying Wang
- College of Medicine, Chongqing University, Chongqing, China; Radiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China.
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Mair M, Singhavi H, Pai A, Khan M, Conboy P, Olaleye O, Salha R, Ameerally P, Vaidhyanath R, Chaturvedi P. A Systematic Review and Meta-Analysis of 29 Studies Predicting Diagnostic Accuracy of CT, MRI, PET, and USG in Detecting Extracapsular Spread in Head and Neck Cancers. Cancers (Basel) 2024; 16:1457. [PMID: 38672539 PMCID: PMC11047869 DOI: 10.3390/cancers16081457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 03/27/2024] [Accepted: 03/27/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Extracapsular spread (ECS) is the extension of cancer cells beyond the lymph node capsule and is a significant prognostic factor in head and neck cancers. This meta-analysis compared the diagnostic accuracy of CT, MRI, PET, and USG in detecting ECS in head and neck cancers. METHODOLOGY The authors conducted a systematic review and meta-analysis of studies that compared the diagnostic accuracy of CT, MRI, PET, and USG in detecting ECS in head and neck cancers. They included studies that were published between 1990 and December 2023 and that used histopathology as the reference standard for ECS. RESULTS The pooled sensitivity and specificity of CT scan were 0.63 (95% CI = 0.53-0.73) and 0.85 (95% CI = 0.74-0.91), respectively. The pooled sensitivity and specificity of MRI were 0.83 (95% CI = 0.71-0.90) and 0.85 (95% CI = 0.73-0.92), respectively. The pooled sensitivity and specificity of PET were 0.80 (95% CI = 0.74-0.85) and 0.93 (95% CI = 0.92-0.94), respectively. The pooled sensitivity and specificity of USG were 0.80 (95% CI = 0.68-0.88) and 0.84 (95% CI = 0.74-0.91), respectively. MRI had significantly higher sensitivity than CT scan (p-0.05). The specificity of CT and MRI was not significantly different (p-0.99). PET scan had the highest specificity among all imaging modalities. CONCLUSION MRI is the most accurate imaging modality for detecting ECS in head and neck cancers. CT scan is a reasonable alternative, but PET scan may be considered when high specificity is required. USG may not add any further benefit in detecting ECS.
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Affiliation(s)
- Manish Mair
- Head and Neck Surgery, University Hospital of Leicester, Leicester LE1 5WW, UK
| | | | - Ameya Pai
- Tata Memorial Hospital, Mumbai 400012, India; (A.P.); (P.C.)
| | - Mariya Khan
- Fortis Hospital, Mumbai 400016, India; (H.S.); (M.K.)
| | - Peter Conboy
- Head and Neck Surgery, University Hospital of Leicester, Leicester LE1 5WW, UK
| | - Oladejo Olaleye
- Head and Neck Surgery, University Hospital of Leicester, Leicester LE1 5WW, UK
| | - Rami Salha
- Head and Neck Surgery, University Hospital of Northampton, Northampton NN1 5BD, UK (P.A.)
| | - Phil Ameerally
- Head and Neck Surgery, University Hospital of Northampton, Northampton NN1 5BD, UK (P.A.)
| | - Ram Vaidhyanath
- Radiology Department, University Hospital of Leicester, Leicester LE1 5WW, UK
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Welch ML, Kim S, Hope AJ, Huang SH, Lu Z, Marsilla J, Kazmierski M, Rey-McIntyre K, Patel T, O'Sullivan B, Waldron J, Bratman S, Haibe-Kains B, Tadic T. RADCURE: An open-source head and neck cancer CT dataset for clinical radiation therapy insights. Med Phys 2024; 51:3101-3109. [PMID: 38362943 DOI: 10.1002/mp.16972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 01/17/2024] [Accepted: 01/17/2024] [Indexed: 02/17/2024] Open
Abstract
PURPOSE This manuscript presents RADCURE, one of the most extensive head and neck cancer (HNC) imaging datasets accessible to the public. Initially collected for clinical radiation therapy (RT) treatment planning, this dataset has been retrospectively reconstructed for use in imaging research. ACQUISITION AND VALIDATION METHODS RADCURE encompasses data from 3346 patients, featuring computed tomography (CT) RT simulation images with corresponding target and organ-at-risk contours. These CT scans were collected using systems from three different manufacturers. Standard clinical imaging protocols were followed, and contours were manually generated and reviewed at weekly RT quality assurance rounds. RADCURE imaging and structure set data was extracted from our institution's radiation treatment planning and oncology information systems using a custom-built data mining and processing system. Furthermore, images were linked to our clinical anthology of outcomes data for each patient and includes demographic, clinical and treatment information based on the 7th edition TNM staging system (Tumor-Node-Metastasis Classification System of Malignant Tumors). The median patient age is 63, with the final dataset including 80% males. Half of the cohort is diagnosed with oropharyngeal cancer, while laryngeal, nasopharyngeal, and hypopharyngeal cancers account for 25%, 12%, and 5% of cases, respectively. The median duration of follow-up is five years, with 60% of the cohort surviving until the last follow-up point. DATA FORMAT AND USAGE NOTES The dataset provides images and contours in DICOM CT and RT-STRUCT formats, respectively. We have standardized the nomenclature for individual contours-such as the gross primary tumor, gross nodal volumes, and 19 organs-at-risk-to enhance the RT-STRUCT files' utility. Accompanying demographic, clinical, and treatment data are supplied in a comma-separated values (CSV) file format. This comprehensive dataset is publicly accessible via The Cancer Imaging Archive. POTENTIAL APPLICATIONS RADCURE's amalgamation of imaging, clinical, demographic, and treatment data renders it an invaluable resource for a broad spectrum of radiomics image analysis research endeavors. Researchers can utilize this dataset to advance routine clinical procedures using machine learning or artificial intelligence, to identify new non-invasive biomarkers, or to forge prognostic models.
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Affiliation(s)
- Mattea L Welch
- Princess Margaret Cancer Centre, Toronto, ON, Canada
- Cancer Digital Intelligence Program, Toronto, ON, Canada
| | - Sejin Kim
- Princess Margaret Cancer Centre, Toronto, ON, Canada
- Cancer Digital Intelligence Program, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Andrew J Hope
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Shao Hui Huang
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Zhibin Lu
- Princess Margaret Cancer Centre, Toronto, ON, Canada
| | - Joseph Marsilla
- Princess Margaret Cancer Centre, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Michal Kazmierski
- Princess Margaret Cancer Centre, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Katrina Rey-McIntyre
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada
| | - Tirth Patel
- Cancer Digital Intelligence Program, Toronto, ON, Canada
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada
- TECHNA Institute, University Health Network, Toronto, ON, Canada
| | - Brian O'Sullivan
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - John Waldron
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Scott Bratman
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Benjamin Haibe-Kains
- Princess Margaret Cancer Centre, Toronto, ON, Canada
- Cancer Digital Intelligence Program, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- TECHNA Institute, University Health Network, Toronto, ON, Canada
| | - Tony Tadic
- Cancer Digital Intelligence Program, Toronto, ON, Canada
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
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Struckmeier AK, Buchbender M, Moest T, Lutz R, Agaimy A, Kesting M. Occult metastasis is no burden factor in oral squamous cell carcinoma patients when adhering to a standardized approach in neck dissection. Clin Oral Investig 2024; 28:113. [PMID: 38267767 PMCID: PMC10808318 DOI: 10.1007/s00784-024-05514-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 01/16/2024] [Indexed: 01/26/2024]
Abstract
OBJECTIVES Management of the neck in patients with oral squamous cell carcinoma (OSCC) is pivotal to oncologic control and survival. However, there is controversy regarding necessity of neck dissection (ND) in patients with clinically node-negative neck. We aimed to assess risk factors for occult metastasis and to explore whether the presence of occult lymph node metastases (LNMs) has an impact on recurrence and survival. MATERIAL AND METHODS A retrospective cohort study was performed including patients with primary OSCC who underwent radical tumor resection and ND in a high-volume center adhering to the prevailing German guideline. The ND was performed according to a standardized approach. RESULTS Four hundred twenty-one patients with primary surgically treated OSCC were included. The incidence of occult metastasis was 14.49%. A pathological T stage > 1 (multivariate analysis, odds ratio (OR) 3.958, p = 0.042) and the presence of extranodal extension in LNMs (multivariate analysis, OR 0.287, p = 0.020) were identified as independent risk factors for occult metastasis. When comparing patients with and without occult metastasis, there were no significant differences in terms of progression-free survival (log-rank, p = 0.297) and overall survival (log-rank, p = 0.320). There were no cases of ipsilateral neck recurrence. One patient developed contralateral neck metastasis; however, he initially presented with a unilateral pT1 pN0 tumor. CONCLUSIONS Overall, our findings suggest that conducting a standardized approach in ND should be applied in terms of management of the neck in order to maintain survival rates and to prevent neck recurrence in OSCC patients. CLINICAL RELEVANCE None of the risk factors for occult metastasis can be reliably assessed preoperatively. Although elective ND does not guarantee the complete prevention of neck recurrence, it increases the likelihood of either timely removal of micrometastases or strengthens the justification for adjuvant therapy. Consequently, this approach leads to improvements in clinical outcomes.
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Affiliation(s)
- Ann-Kristin Struckmeier
- Department of Oral and Cranio-Maxillofacial Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Glückstraße 11, 91054, Erlangen, Germany.
- Comprehensive Cancer Center Erlangen-European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany.
| | - Mayte Buchbender
- Department of Oral and Cranio-Maxillofacial Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Glückstraße 11, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
| | - Tobias Moest
- Department of Oral and Cranio-Maxillofacial Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Glückstraße 11, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
| | - Rainer Lutz
- Department of Oral and Cranio-Maxillofacial Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Glückstraße 11, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
| | - Abbas Agaimy
- Comprehensive Cancer Center Erlangen-European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
- Institute of Pathology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Marco Kesting
- Department of Oral and Cranio-Maxillofacial Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Glückstraße 11, 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
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Hancioglu T, Pekcevik Y, Akdogan AI, Kucuk U, Ekmekci S, Arslan IB, Cukurova I. Imaging Characteristics Predictive of Cervical Extranodal Tumor Extension in Patients With Head and Neck Squamous Cell Carcinoma. J Comput Assist Tomogr 2024; 48:129-136. [PMID: 37478483 DOI: 10.1097/rct.0000000000001512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/23/2023]
Abstract
OBJECTIVES The aims of the study were to determine the predictive imaging findings of extranodal extension (ENE) in metastatic cervical lymph nodes of head and neck squamous cell carcinoma and to investigate the interobserver agreement among radiologists with different experience levels. MATERIALS AND METHODS Patients with cervical lymph node dissection and who had metastatic lymph nodes and preoperative imaging were included. Three radiologists evaluated nodal necrosis, irregular contour, gross invasion, and perinodal fat stranding. They also noted their overall impression regarding the presence of the ENE. Sensitivity, specificity, odds ratios based on logistic regression, and interobserver agreement of ENE status were calculated. RESULTS Of 106 lymph nodes (that met inclusion criteria), 31 had radiologically determined ENE. On pathologic examination, 22 of 31 nodes were positive for ENE. The increasing number of metastatic lymph nodes was associated with the presence of the ENE ( P = 0.010). Irregular contour had the highest sensitivity (78.6%) and gross invasion had the highest specificity (96%) for the determination of the ENE. The radiologists' impression regarding the presence of the pathlogical ENE had 39.3% sensitivity and 82% specificity. Metastatic lymph nodes with a perinodal fat stranding and with the longest diameter of greater than 2 cm were found to be strong predictors of the ENE. The gross invasion demonstrated the highest κ value (0.731) among the evaluated imaging criteria. CONCLUSIONS In the assessment of ENE, the gross invasion had the highest specificity among imaging features and showed the highest interobserver agreement. Perinodal fat stranding and the longest diameter of greater than 2 cm in a metastatic lymph node were the best predictors of the ENE.
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Affiliation(s)
- Tugce Hancioglu
- From the Department of Radiology, Turgutlu State Hospital, Manisa
| | - Yeliz Pekcevik
- Department of Radiology, Izmir Health Sciences University, Tepecik Training and Research Hospital
| | - Aslı Irmak Akdogan
- Department of Radiology, Ataturk Training and Research Hospital, Katip Celebi University
| | | | | | - Ilker Burak Arslan
- Otolaryngology-Head and Neck, Izmir Health Sciences University, Tepecik Training and Research Hospital, Izmir, Turkey
| | - Ibrahim Cukurova
- Otolaryngology-Head and Neck, Izmir Health Sciences University, Tepecik Training and Research Hospital, Izmir, Turkey
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Qu J, Su T, Pan B, Zhang T, Chen X, Zhu X, Chen Y, Zhang Z, Jin Z. Free-Breathing StarVIBE Sequence for the Detection of Extranodal Extension in Head and Neck Cancer: An Image Quality and Diagnostic Performance Study. Cancers (Basel) 2023; 15:4992. [PMID: 37894359 PMCID: PMC10605568 DOI: 10.3390/cancers15204992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/27/2023] [Accepted: 10/02/2023] [Indexed: 10/29/2023] Open
Abstract
(1) Background: This study aims to evaluate the image quality of abnormal cervical lymph nodes in head and neck cancer and the diagnostic performance of detecting extranodal extension (ENE) using free-breathing StarVIBE. (2) Methods: In this retrospective analysis, 80 consecutive head and neck cancer patients underwent StarVIBE before neck dissection at an academic center. Image quality was compared with conventional VIBE available for 28 of these patients. A total of 73 suspicious metastatic lymph nodes from 40 patients were found based on morphology and enhancement pattern on StarVIBE. Sensitivity (SN), specificity (SP), and odds ratios were calculated for each MR feature from StarVIBE to predict pathologic ENE. (3) Results: StarVIBE showed significantly superior image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for enlarged lymph nodes compared to VIBE. The MR findings of "invading adjacent planes" (SN, 0.54; SP, 1.00) and "matted nodes" (SN, 0.72; SP, 0.89) emerged as notable observations. The highest diagnostic performance was attained by combining these two features (SN, 0.93; SP, 0.89). (4) Conclusions: This study confirms that StarVIBE offers superior image quality for abnormal lymph nodes compared to VIBE, and it can accurately diagnose ENE by utilizing a composite MR criterion in head and neck cancer.
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Affiliation(s)
- Jiangming Qu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
| | - Tong Su
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
| | - Boju Pan
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
| | - Tao Zhang
- Department of Stomatology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
| | - Xingming Chen
- Department of Otolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
| | - Xiaoli Zhu
- Department of Otolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
| | - Yu Chen
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
| | - Zhuhua Zhang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China
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Bruening J. Robotic Surgery in the Head and Neck: Presurgical Considerations and Post-treatment Appearance. Semin Roentgenol 2023; 58:374-383. [PMID: 37507177 DOI: 10.1053/j.ro.2023.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 05/24/2023] [Accepted: 05/30/2023] [Indexed: 07/30/2023]
Affiliation(s)
- Jennifer Bruening
- Department of Otolaryngology and Communication Sciences, Head and Neck Surgical Oncology and Reconstructive Surgery, Medical College of Wisconsin, Milwaukee, WI.
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Kim S, Park H, Yeou SH, Roh J, Shin YS, Kim CH, Ha EJ, Jang JY. Assessment of Radiologic Extranodal Extension Using Combinatorial Analysis of Nodal Margin Breakdown and Metastatic Burden in Oropharyngeal Cancer. Cancers (Basel) 2023; 15:3276. [PMID: 37444387 DOI: 10.3390/cancers15133276] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 06/17/2023] [Accepted: 06/19/2023] [Indexed: 07/15/2023] Open
Abstract
The importance of risk stratification in the management of oropharyngeal squamous cell carcinoma (OPSCC) is becoming increasingly obvious with the growing evidence of its variable prognosis. We identified and evaluated imaging characteristics predictive of extranodal extension (ENE) in OPSCC. Preoperative computed tomography and histopathologic results of 108 OPSCC patients who underwent neck dissection as primary treatment were analyzed. Imaging characteristics were reassessed for factors associated with nodal margin breakdown and metastatic burden. Moreover, the predictability of pathological ENE (pENE) was analyzed. Univariate and multivariate binomial logistic regression analyses were performed to examine the predictive power of ENE-related radiologic features. Imaging-based characteristics showed variable degrees of association with pENE. Factors associated with nodal margin breakdown (indistinct capsular contour, irregular margin, and perinodal fat stranding) and factors associated with nodal burden (nodal matting, lower neck metastasis, and presence of >4 lymph node metastases) were significantly predictive of ENE (odds ratio (OR) = 11.170 and 12.121, respectively). The combined utilization of the nodal margin and burden factors further increased the predictive ability (OR = 14.710). Factors associated with nodal margin breakdown and nodal burden were associated with pENE, demonstrating the use of combinatorial analysis for more accurate ENE prediction.
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Affiliation(s)
- Sungryeal Kim
- Department of Otolaryngology, College of Medicine, Ajou University, Incheon 22332, Republic of Korea
| | - Hannah Park
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon 16502, Republic of Korea
| | - Se Hyun Yeou
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon 16502, Republic of Korea
| | - Jin Roh
- Department of Pathology, School of Medicine, Ajou University, Suwon 16502, Republic of Korea
| | - Yoo Seob Shin
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon 16502, Republic of Korea
| | - Chul-Ho Kim
- Department of Otolaryngology, College of Medicine, Ajou University, Incheon 22332, Republic of Korea
- Department of Molecular Science and Technology, Graduate School of Medicine, Ajou University, Suwon 16502, Republic of Korea
| | - Eun Ju Ha
- Department of Radiology, School of Medicine, Ajou University, Suwon 16502, Republic of Korea
| | - Jeon Yeob Jang
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon 16502, Republic of Korea
- Department of Biomedical Sciences, Graduate School of Medicine, Ajou University, Suwon 16502, Republic of Korea
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9
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Kann BH, Likitlersuang J, Bontempi D, Ye Z, Aneja S, Bakst R, Kelly HR, Juliano AF, Payabvash S, Guenette JP, Uppaluri R, Margalit DN, Schoenfeld JD, Tishler RB, Haddad R, Aerts HJWL, Garcia JJ, Flamand Y, Subramaniam RM, Burtness BA, Ferris RL. Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial. Lancet Digit Health 2023; 5:e360-e369. [PMID: 37087370 PMCID: PMC10245380 DOI: 10.1016/s2589-7500(23)00046-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 01/18/2023] [Accepted: 02/21/2023] [Indexed: 04/24/2023]
Abstract
BACKGROUND Pretreatment identification of pathological extranodal extension (ENE) would guide therapy de-escalation strategies for in human papillomavirus (HPV)-associated oropharyngeal carcinoma but is diagnostically challenging. ECOG-ACRIN Cancer Research Group E3311 was a multicentre trial wherein patients with HPV-associated oropharyngeal carcinoma were treated surgically and assigned to a pathological risk-based adjuvant strategy of observation, radiation, or concurrent chemoradiation. Despite protocol exclusion of patients with overt radiographic ENE, more than 30% had pathological ENE and required postoperative chemoradiation. We aimed to evaluate a CT-based deep learning algorithm for prediction of ENE in E3311, a diagnostically challenging cohort wherein algorithm use would be impactful in guiding decision-making. METHODS For this retrospective evaluation of deep learning algorithm performance, we obtained pretreatment CTs and corresponding surgical pathology reports from the multicentre, randomised de-escalation trial E3311. All enrolled patients on E3311 required pretreatment and diagnostic head and neck imaging; patients with radiographically overt ENE were excluded per study protocol. The lymph node with largest short-axis diameter and up to two additional nodes were segmented on each scan and annotated for ENE per pathology reports. Deep learning algorithm performance for ENE prediction was compared with four board-certified head and neck radiologists. The primary endpoint was the area under the curve (AUC) of the receiver operating characteristic. FINDINGS From 178 collected scans, 313 nodes were annotated: 71 (23%) with ENE in general, 39 (13%) with ENE larger than 1 mm ENE. The deep learning algorithm AUC for ENE classification was 0·86 (95% CI 0·82-0·90), outperforming all readers (p<0·0001 for each). Among radiologists, there was high variability in specificity (43-86%) and sensitivity (45-96%) with poor inter-reader agreement (κ 0·32). Matching the algorithm specificity to that of the reader with highest AUC (R2, false positive rate 22%) yielded improved sensitivity to 75% (+ 13%). Setting the algorithm false positive rate to 30% yielded 90% sensitivity. The algorithm showed improved performance compared with radiologists for ENE larger than 1 mm (p<0·0001) and in nodes with short-axis diameter 1 cm or larger. INTERPRETATION The deep learning algorithm outperformed experts in predicting pathological ENE on a challenging cohort of patients with HPV-associated oropharyngeal carcinoma from a randomised clinical trial. Deep learning algorithms should be evaluated prospectively as a treatment selection tool. FUNDING ECOG-ACRIN Cancer Research Group and the National Cancer Institute of the US National Institutes of Health.
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Affiliation(s)
- Benjamin H Kann
- Department of Radiation Oncology, Harvard Medical School, Boston, MA, USA; Mass General Brigham Artificial Intelligence in Medicine Program, Boston, MA, USA.
| | - Jirapat Likitlersuang
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Mass General Brigham Artificial Intelligence in Medicine Program, Boston, MA, USA
| | - Dennis Bontempi
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Mass General Brigham Artificial Intelligence in Medicine Program, Boston, MA, USA
| | - Zezhong Ye
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Mass General Brigham Artificial Intelligence in Medicine Program, Boston, MA, USA
| | - Sanjay Aneja
- Department of Therapeutic Radiology, New Haven, CT, USA
| | - Richard Bakst
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Amy F Juliano
- Mass Eye and Ear, Mass General Hospital, Boston, MA, USA
| | | | - Jeffrey P Guenette
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ravindra Uppaluri
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Danielle N Margalit
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jonathan D Schoenfeld
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Roy B Tishler
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Robert Haddad
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Hugo J W L Aerts
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Mass General Brigham Artificial Intelligence in Medicine Program, Boston, MA, USA; Department of Radiology, Maastricht University, Maastricht, Netherlands
| | | | - Yael Flamand
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, ECOG-ACRIN Biostatistics Center, Boston, MA, USA
| | - Rathan M Subramaniam
- Department of Radiology and Nuclear Medicine, University of Notre Dame Australia, Sydney, NSW, Australia; Department of Radiology, Duke University, Durham, NC, USA
| | | | - Robert L Ferris
- Department of Otolaryngology, University of Pittsburgh Cancer Institute, Pittsburgh, PA, USA
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10
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Tran NA, Palotai M, Hanna GJ, Schoenfeld JD, Bay CP, Rettig EM, Bunch PM, Juliano AF, Kelly HR, Suh CH, Zander DA, Morales Pinzon A, Kann BH, Huang RY, Haddad RI, Guttmann CRG, Guenette JP. Diagnostic performance of computed tomography features in detecting oropharyngeal squamous cell carcinoma extranodal extension. Eur Radiol 2023; 33:3693-3703. [PMID: 36719493 DOI: 10.1007/s00330-023-09407-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 12/06/2022] [Accepted: 12/27/2022] [Indexed: 02/01/2023]
Abstract
OBJECTIVES Accurate pre-treatment imaging determination of extranodal extension (ENE) could facilitate the selection of appropriate initial therapy for HPV-positive oropharyngeal squamous cell carcinoma (HPV + OPSCC). Small studies have associated 7 CT features with ENE with varied results and agreement. This article seeks to determine the replicable diagnostic performance of these CT features for ENE. METHODS Five expert academic head/neck neuroradiologists from 5 institutions evaluate a single academic cancer center cohort of 75 consecutive HPV + OPSCC patients. In a web-based virtual laboratory for imaging research and education, the experts performed training on 7 published CT features associated with ENE and then independently identified the "single most (if any) suspicious" lymph node and presence/absence of each of the features. Inter-rater agreement was assessed using percentage agreement, Gwet's AC1, and Fleiss' kappa. Sensitivity, specificity, and positive and negative predictive values were calculated for each CT feature based on histologic ENE. RESULTS All 5 raters identified the same node in 52 cases (69%). In 15 cases (20%), at least one rater selected a node and at least one rater did not. In 8 cases (11%), all raters selected a node, but at least one rater selected a different node. Percentage agreement and Gwet's AC1 coefficients were > 0.80 for lesion identification, matted/conglomerated nodes, and central necrosis. Fleiss' kappa was always < 0.6. CT sensitivity for histologically confirmed ENE ranged 0.18-0.94, specificity 0.41-0.88, PPV 0.26-0.36, and NPV 0.78-0.96. CONCLUSIONS Previously described CT features appear to have poor reproducibility among expert head/neck neuroradiologists and poor predictive value for histologic ENE. KEY POINTS • Previously described CT imaging features appear to have poor reproducibility among expert head and neck subspecialized neuroradiologists as well as poor predictive value for histologic ENE. • Although it may still be appropriate to comment on the presence or absence of these CT features in imaging reports, the evidence indicates that caution is warranted when incorporating these features into clinical decision-making regarding the likelihood of ENE.
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Affiliation(s)
- Ngoc-Anh Tran
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Miklos Palotai
- Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Glenn J Hanna
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Jonathan D Schoenfeld
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Camden P Bay
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleni M Rettig
- Division of Otolaryngology-Head and Neck Surgery, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Paul M Bunch
- Division of Neuroradiology, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Amy F Juliano
- Department of Radiology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Hillary R Kelly
- Department of Radiology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
- Division of Neuroradiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - David A Zander
- Division of Neuroradiology, University of Colorado, Aurora, CO, USA
| | - Alfredo Morales Pinzon
- Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Benjamin H Kann
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, 75 Francis Street Boston, Boston, MA, 02115, USA
| | - Robert I Haddad
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Charles R G Guttmann
- Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jeffrey P Guenette
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, 75 Francis Street Boston, Boston, MA, 02115, USA.
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11
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Gowrishankar SV, Bidaye R, Das T, Majcher V, Fish B, Casey R, Masterson L. Intrathyroidal parathyroid adenomas: Scoping review on clinical presentation, preoperative localization, and surgical treatment. Head Neck 2023; 45:706-720. [PMID: 36563301 PMCID: PMC10108101 DOI: 10.1002/hed.27287] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/26/2022] [Accepted: 12/09/2022] [Indexed: 12/24/2022] Open
Abstract
Intrathyroidal parathyroid adenomas (IPAs) are a rare cause of primary hyperparathyroidism. They are often difficult to localize preoperatively and intraoperatively, making diagnosis and treatment challenging. Current data on IPAs are sparse and fragmented in the literature. This makes it difficult to compare the effectiveness of different imaging and surgical techniques. To address this issue, this scoping review maps the literature on IPAs, focusing on four domains: clinical presentation, current localization methods, different surgical techniques, and histopathological features. A search of MEDLINE, Embase, and the Cochrane Library was conducted, with 19 studies meeting the inclusion criteria. The characteristics of IPAs on ultrasound, fine-needle aspiration, CT, MRI, sestamibi-based techniques, and selective venous sampling are summarized. Emerging imaging modalities, including autofluorescence, are introduced. Surgical methods and intraoperative factors that correlate with high success rates for removal are highlighted. This review also identifies gaps in knowledge to guide further research into this area.
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Affiliation(s)
| | - Rohan Bidaye
- Department of Otolaryngology-Head & Neck Surgery, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Tilak Das
- Department of Neuroradiology and Head & Neck Imaging, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Veronika Majcher
- Department of Neuroradiology and Head & Neck Imaging, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Brian Fish
- Department of Otolaryngology-Head & Neck Surgery, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Ruth Casey
- Department of Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Liam Masterson
- Department of Otolaryngology-Head & Neck Surgery, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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12
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Rettig EM, Wang AA, Tran NA, Carey E, Dey T, Schoenfeld JD, Sehgal K, Guenette JP, Margalit DN, Sethi R, Uppaluri R, Tishler RB, Annino DJ, Goguen LA, Jo VY, Haddad RI, Hanna GJ. Association of Pretreatment Circulating Tumor Tissue-Modified Viral HPV DNA With Clinicopathologic Factors in HPV-Positive Oropharyngeal Cancer. JAMA Otolaryngol Head Neck Surg 2022; 148:1120-1130. [PMID: 36301568 PMCID: PMC9614675 DOI: 10.1001/jamaoto.2022.3282] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/31/2022] [Indexed: 01/10/2023]
Abstract
Importance Circulating tumor tissue-modified viral (TTMV) human papillomavirus (HPV) DNA is a dynamic, clinically relevant biomarker for HPV-positive oropharyngeal squamous cell carcinoma. Reasons for its wide pretreatment interpatient variability are not well understood. Objective To characterize clinicopathologic factors associated with TTMV HPV DNA. Design, Setting, and Participants This cross-sectional study included patients evaluated for HPV-positive oropharyngeal squamous cell carcinoma at Dana-Farber Cancer Institute in Boston, Massachusetts, between December 2019 and January 2022 and who were undergoing curative-intent treatment. Exposures Clinicopathologic characteristics including demographic variables, tumor and nodal staging, HPV genotype, and imaging findings. Main Outcomes and Measures Pretreatment circulating TTMV HPV DNA from 5 genotypes (16, 18, 31, 33, and 35) assessed using a commercially available digital droplet polymerase chain reaction-based assay, considered as either detectable/undetectable or a continuous score (fragments/mL). Results Among 110 included patients, 96 were men (87%) and 104 were White (95%), with a mean (SD) age of 62.2 (9.4) years. Circulating TTMV HPV DNA was detected in 98 patients (89%), with a median (IQR) score of 315 (47-2686) fragments/mL (range, 0-60 061 fragments/mL). Most detectable TTMV HPV DNA was genotype 16 (n = 86 [88%]), while 12 patients (12%) harbored other genotypes. Circulating TTMV HPV DNA detection was most strongly associated with clinical N stage. Although few patients had clinical stage N0 disease, only 4 of these 11 patients (36%) had detectable DNA compared with 94 of 99 patients (95%) with clinical stage N1 to N3 disease (proportion difference, 59%; 95% CI, 30%-87%). Among patients with undetectable TTMV HPV DNA, more than half (7 of 12 [58%]) had clinical stage N0 disease. The TTMV HPV DNA prevalence and score increased with progressively higher clinical nodal stage, diameter of largest lymph node, and higher nodal maximum standardized uptake value on positron emission tomography/computed tomography. In multivariable analysis, clinical nodal stage and nodal maximum standardized uptake value were each strongly associated with TTMV HPV DNA score. Among 27 surgically treated patients, more patients with than without lymphovascular invasion had detectable TTMV HPV DNA (12 of 12 [100%] vs 9 of 15 [60%]). Conclusions and Relevance In this cross-sectional study, circulating TTMV HPV DNA was statistically significantly associated with nodal disease at HPV-positive OPSCC diagnosis. The few patients with undetectable levels had predominantly clinical stage N0 disease, suggesting assay sensitivity for diagnostic purposes may be lower among patients without cervical lymphadenopathy. Mechanisms underlying this association, and the use of this biomarker for surveillance of patients with undetectable baseline values, warrant further investigation.
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Affiliation(s)
- Eleni M. Rettig
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, Massachusetts
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Center for Surgery and Public Health, Brigham and Women’s Hospital, Boston, Massachusetts
| | | | - Ngoc-Anh Tran
- Harvard Medical School, Boston, Massachusetts
- Division of Neuroradiology, Department of Radiology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Evan Carey
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Tanujit Dey
- Harvard Medical School, Boston, Massachusetts
- Center for Surgery and Public Health, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Jonathan D. Schoenfeld
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Radiation Oncology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Kartik Sehgal
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jeffrey P. Guenette
- Harvard Medical School, Boston, Massachusetts
- Division of Neuroradiology, Department of Radiology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Danielle N. Margalit
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Radiation Oncology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Rosh Sethi
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, Massachusetts
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Center for Surgery and Public Health, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Ravindra Uppaluri
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, Massachusetts
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Roy B. Tishler
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Radiation Oncology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Donald J. Annino
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, Massachusetts
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Laura A. Goguen
- Division of Otolaryngology–Head and Neck Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, Massachusetts
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Vickie Y. Jo
- Harvard Medical School, Boston, Massachusetts
- Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Robert I. Haddad
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Glenn J. Hanna
- Center for Head and Neck Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
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13
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Mahajan A, Chand A, Agarwal U, Patil V, Vaish R, Noronha V, Joshi A, Kapoor A, Sable N, Ahuja A, Shukla S, Menon N, Agarwal JP, Laskar SG, D' Cruz A, Chaturvedi P, Chaukar D, Pai PS, Pantvaidya G, Thiagarajan S, Rane S, Prabhash K. Prognostic Value of Radiological Extranodal Extension Detected by Computed Tomography for Predicting Outcomes in Patients With Locally Advanced Head and Neck Squamous Cell Cancer Treated With Radical Concurrent Chemoradiotherapy. Front Oncol 2022; 12:814895. [PMID: 35719994 PMCID: PMC9202501 DOI: 10.3389/fonc.2022.814895] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 04/13/2022] [Indexed: 11/14/2022] Open
Abstract
Objective Extra Nodal Extension (ENE) assessment in locally advanced head and neck cancers (LAHNCC) treated with concurrent chemo radiotherapy (CCRT) is challenging and hence the American Joint Committee on Cancer (AJCC) N staging. We hypothesized that radiology-based ENE (rENE) may directly impact outcomes in LAHNSCC treated with radical CCRT. Materials and Methods Open-label, investigator-initiated, randomized controlled trial (RCT) (2012–2018), which included LAHNSCC planned for CCRT. Patients were randomized 1:1 to radical radiotherapy (66–70 grays) with concurrent weekly cisplatin (30 mg/m2) [cisplatin radiation arm (CRT)] or same schedule of CRT with weekly nimotuzumab (200 mg) [nimotuzumab plus CRT (NCRT)]. A total of 536 patients were accrued and 182 were excluded due to the non-availability of Digital Imaging and Communications in Medicine (DICOM) computed tomography (CT) data. A total of 354 patients were analyzed for rENE. Metastatic nodes were evaluated based on five criteria and further classified as rENE as positive/negative based on three-criteria capsule irregularity with fat stranding, fat invasion, and muscle/vessel invasion. We evaluated the association of rENE and disease-free survival (DFS), loco-regional recurrence-free survival (LRRFS), and overall survival (OS). Results A total of 244 (68.9%) patients had radiologically metastatic nodes (rN), out of which 140 (57.3%) had rENE. Distribution of rENE was balanced in the two study groups CRT or NCRT (p-value 0.412). The median follow-up period was 39 months (ranging from 35.5 to 42.8 months). Complete response (CR) was seen in 204 (57.6%); incomplete response (IR), i.e., partial response plus stable disease (PR + SD), in 126 (35.6%); and progressive disease (PD) in 24 (6.8%). rENE-positive group had poor survival compared to rENE-negative group 3-year OS (46.7% vs. 63.6%), poor DFS (48.8% vs. 87%), and LRRFS (39.9% vs. 60.4%). rENE positive had 1.71 times increased risk of IR than rENE negative. Overall stage, site, clinical metastatic node (cN), response, and rENE were the significant factors for predicting OS, DFS, and LRRFS on univariate analysis. After making adjustment on multivariate analysis, rENE was an independent prognostic factor for DFS and trending to be significant for OS. Conclusion Pre-treatment rENE is an independent prognostic marker for survival in patients with LAHNSCC treated radically with CCRT that can be used as a potential predictive marker for response to treatment and hence stratify patients into responders vs. non-responders. We propose the mahajan rENE grading system applicable on CT, magnetic resonance imaging, positron emission tomography–contrast-enhanced CT, and ultrasound.
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Affiliation(s)
- Abhishek Mahajan
- Department of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Ankur Chand
- Department of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Ujjwal Agarwal
- Department of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Vijay Patil
- Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Richa Vaish
- Department of Head and Neck Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Vanita Noronha
- Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Amit Joshi
- Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Akhil Kapoor
- Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Nilesh Sable
- Department of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Ankita Ahuja
- Department of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Shreya Shukla
- Department of Radiodiagnosis and Imaging, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Nandini Menon
- Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Jai Prakash Agarwal
- Department of Radiation Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Sarbani Ghosh Laskar
- Department of Radiation Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Anil D' Cruz
- Department of Head and Neck Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Pankaj Chaturvedi
- Department of Head and Neck Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Devendra Chaukar
- Department of Head and Neck Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - P S Pai
- Department of Head and Neck Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Gouri Pantvaidya
- Department of Head and Neck Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Shivakumar Thiagarajan
- Department of Head and Neck Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Swapnil Rane
- Department of Pathology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Kumar Prabhash
- Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
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14
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HPV-associated oropharyngeal cancer: epidemiology, molecular biology and clinical management. Nat Rev Clin Oncol 2022; 19:306-327. [PMID: 35105976 PMCID: PMC8805140 DOI: 10.1038/s41571-022-00603-7] [Citation(s) in RCA: 282] [Impact Index Per Article: 141.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2022] [Indexed: 12/13/2022]
Abstract
Human papillomavirus (HPV)-positive (HPV+) oropharyngeal squamous cell carcinoma (OPSCC) has one of the most rapidly increasing incidences of any cancer in high-income countries. The most recent (8th) edition of the UICC/AJCC staging system separates HPV+ OPSCC from its HPV-negative (HPV−) counterpart to account for the improved prognosis seen in the former. Indeed, owing to its improved prognosis and greater prevalence in younger individuals, numerous ongoing trials are examining the potential for treatment de-intensification as a means to improve quality of life while maintaining acceptable survival outcomes. In addition, owing to the distinct biology of HPV+ OPSCCs, targeted therapies and immunotherapies have become an area of particular interest. Importantly, OPSCC is often detected at an advanced stage owing to a lack of symptoms in the early stages; therefore, a need exists to identify and validate possible diagnostic biomarkers to aid in earlier detection. In this Review, we provide a summary of the epidemiology, molecular biology and clinical management of HPV+ OPSCC in an effort to highlight important advances in the field. Ultimately, a need exists for improved understanding of the molecular basis and clinical course of this disease to guide efforts towards early detection and precision care, and to improve patient outcomes. The incidence of human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) is increasing rapidly in most developed countries. In this Review, the authors provide an overview of the epidemiology, molecular biology and treatment of HPV-positive OPSCC, including discussions of the role of treatment de-escalation and emerging novel therapies. The incidence of human papillomavirus-associated oropharyngeal cancer (HPV+ OPSCC) is expected to continue to rise over the coming decades until the benefits of gender-neutral prophylactic HPV vaccination begin to become manifest. The incidence of HPV+ OPSCC appears to be highest in high-income countries, although more epidemiological data are needed from low- and middle-income countries, in which HPV vaccination coverage remains low. The substantially better prognosis of patients with HPV+ OPSCC compared to those with HPV– OPSCC has been recognized in the American Joint Committee on Cancer TNM8 staging guidelines, which recommend stratification by HPV status to improve staging. The molecular biology and genomic features of HPV+ OPSCC are similar to those of other HPV-associated malignancies, with HPV oncogenes (E6 and E7) acting as key drivers of pathogenesis. Treatment de-intensification is being pursued in clinical trials, although identifying the ~15% of patients with HPV+ OPSCC who have recurrent disease, and who therefore require more intensive treatment, remains a key challenge.
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15
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Chang CW, Wang C, Lu CJ, Wang CW, Wu CT, Wang CP, Yang TL, Lou PJ, Ko JY, Chang YL, Chen TC. Incidence and prognostic significance of extranodal extension in isolated nodal recurrence of oral squamous cell carcinoma. Radiother Oncol 2021; 167:81-88. [PMID: 34902369 DOI: 10.1016/j.radonc.2021.12.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 10/23/2021] [Accepted: 12/03/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Extranodal extension (ENE) is a crucial prognostic factor of oral squamous cell carcinoma (OSCC). However, the role of ENE in regional recurrence (rENE) remains unclear. The purpose of our study is to assess the salvage outcome according to the presence of rENE in oral cancer patients with isolated nodal recurrence. METHODS Oral cancer patients diagnosed with isolated nodal recurrence at the National Taiwan University Hospital between January 2010 and December 2015 were reviewed. All patients were classified into two groups: with and without rENE. The treatment included salvage neck dissection (ND) ± metronomic chemotherapy, salvage ND and radiation (RT)/concurrent chemoradiation (CCRT), Salvage RT/CCRT alone, metronomic chemotherapy, or supportive care. RESULTS We analyzed 198 patients, 156 with rENE and 42 without rENE. rENE presented more frequently in patients with initial ENE+ (OR = 3.17, p = 0.04), prior RT+ (OR = 2.96, p = 0.02), initial N2/N3 (OR = 2.76, p = 0.01), and recurrent LN size >1.5 cm (OR = 2.33, p = 0.03). The extent of rENE were also significantly different in these patients. The 2-year disease-free survival for patients with and without rENE were 15.7% and 31.7%, respectively (p = 0.002). The 2-year overall survival for patients with and without rENE were 19.6% and 43.9%, respectively (p = 0.004). For patients without rENE, those received salvage ND had better survival outcome (p < 0.001). By contrast, for patients with rENE, those received salvage RT/CCRT had better survival outcome (p < 0.001). CONCLUSION The rENE is frequently present (78.79%) in OSCC patients with isolated nodal recurrence. Individualized treatment modalities based on the presence of rENE should be recommended to achieve better salvage outcomes.
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Affiliation(s)
- Chun-Wei Chang
- Department of Otolaryngology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Chi Wang
- Department of Otolaryngology, National Taiwan University BioMedical Park Hospital, Hsin-Chu, Taiwan
| | - Chi-Ju Lu
- Department of Radiology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Chun-Wei Wang
- Division of Radiation Oncology, Department of Oncology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Chen-Tu Wu
- Department of Pathology, National Taiwan University Hospital, National Taiwan University Cancer Center and National Taiwan University College of Medicine Taipei, Taiwan; Graduate Institute of Pathology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Cheng-Ping Wang
- Department of Otolaryngology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Tsung-Lin Yang
- Department of Otolaryngology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Pei-Jen Lou
- Department of Otolaryngology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Jenq-Yuh Ko
- Department of Otolaryngology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yih-Leong Chang
- Department of Pathology, National Taiwan University Hospital, National Taiwan University Cancer Center and National Taiwan University College of Medicine Taipei, Taiwan; Graduate Institute of Pathology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Tseng-Cheng Chen
- Department of Otolaryngology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
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16
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Kowalchuk RO, Van Abel KM, Yin LX, Garcia J, Harmsen WS, Moore EJ, Price DL, Chintakuntlawar AV, Price KR, Lester SC, Neben Wittich M, Patel SH, Foote RL, Ma DM, Nagelschneider AA, Routman DM. Correlation between radiographic and pathologic lymph node involvement and extranodal extension via CT and PET in HPV-associated oropharyngeal cancer. Oral Oncol 2021; 123:105625. [PMID: 34814068 DOI: 10.1016/j.oraloncology.2021.105625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 10/27/2021] [Accepted: 11/09/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE/OBJECTIVES Extranodal extension (ENE) and more than 4 pathologically involved lymph nodes (pN2) are critical prognostic factors in HPV-associated oropharyngeal cancer (HPV(+) OPSCC). We analyze a patient cohort with HPV(+) OPSCC to determine the sensitivity and specificity of CT and PET/CT in identifying involvement of more than 4 lymph nodes (rN2) compared to pN2 and radiographic ENE (rENE) compared to pathologic ENE (pENE). MATERIALS/METHODS The dataset consisted of 261 patients enrolled in two prospective clinical trials. All imaging studies were independently reviewed by a blinded neuroradiologist, classifying the presence or absence of rENE and rN2. Secondary analyses included correlations of imaging accuracy and pathologic size of the primary tumor. RESULTS CT demonstrated sensitivity of 59%, specificity of 92%, positive predictive value (PPV) of 53%, negative predictive value (NPV) of 94%, and accuracy of 88% for pN2. PET/CT showed similar results. Patients with up to 4 involved lymph nodes (rN0-1) had a 93-94% chance of remaining pN0-1. CT and PET/CT identified an equal number of involved nodes in 81% of patients. CT demonstrated sensitivity of 54%, specificity of 71%, PPV of 72%, NPV of 53%, and accuracy of 62% for pENE. PET/CT showed similar outcomes. Notably, when multiple radiographic criteria were used to identify rENE, PPV increased for both CT (84%) and PET/CT (79%). CONCLUSION Patients with rN0-1 had a 93-94% chance of remaining pN0-1, suggesting rN0-1 could effectively stratify patients for clinical trials and treatment de-escalation. While CT and PET/CT were highly correlated, both showed low sensitivity for identifying pENE.
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Affiliation(s)
- Roman O Kowalchuk
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Kathryn M Van Abel
- Mayo Clinic, Department of Otolaryngology, Rochester, MN 55905, United States
| | - Linda X Yin
- Mayo Clinic, Department of Otolaryngology, Rochester, MN 55905, United States
| | - Joaquin Garcia
- Mayo Clinic, Department of Pathology, Rochester, MN 55905, United States
| | - William S Harmsen
- Mayo Clinic, Department of Statistics, Rochester, MN 55905, United States
| | - Eric J Moore
- Mayo Clinic, Department of Otolaryngology, Rochester, MN 55905, United States
| | - Daniel L Price
- Mayo Clinic, Department of Otolaryngology, Rochester, MN 55905, United States
| | | | - Katharine R Price
- Mayo Clinic, Department of Medical Oncology, MN 55905, United States
| | - Scott C Lester
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | | | - Samir H Patel
- Mayo Clinic, Department of Radiation Oncology, Scottsdale, AZ 85259, United States
| | - Robert L Foote
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Daniel M Ma
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | | | - David M Routman
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States.
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17
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Ma DJ, Van Abel KM. Treatment De-intensification for HPV-associated Oropharyngeal Cancer: A Definitive Surgery Paradigm. Semin Radiat Oncol 2021; 31:332-338. [PMID: 34455988 DOI: 10.1016/j.semradonc.2021.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Human papillomavirus-associated oropharyngeal squamous cell carcinoma (HPV+OPSCC) constitutes the majority of head and neck diagnoses within the United States. Patients with HPV+OPSCC have biologically and demographically distinct disease, leading to high cure rates after standard treatments. This long survivorship period coupled with the toxicity of standard treatments makes de-intensification strategies an urgent research question. Surgery has generally been avoided for HPV+OPSCC as historical surgical techniques were invasive and morbid. With the advent of minimally invasive transoral techniques, definitive surgical options are becoming more popular. Minimally invasive surgery offers unique opportunities in a de-intensification paradigm, including more detailed patient selection, radiation volume reduction, and radiation dose de-intensification. Nevertheless, careful patient selection must be exercised as surgical defects may lead to quality of life decrements beyond what is gained through de-intensification. Ongoing phase III efforts will help clarify the patient cohorts best suited for surgically oriented de-intensification.
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Affiliation(s)
- Daniel J Ma
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN.
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18
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He C, Liu J, Hu S, Qing H, Luo H, Chen X, Liu Y, Zhou P. Improvement of image quality of laryngeal squamous cell carcinoma using noise-optimized virtual monoenergetic image and nonlinear blending image algorithms in dual-energy computed tomography. Head Neck 2021; 43:3125-3131. [PMID: 34268830 DOI: 10.1002/hed.26812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 04/20/2021] [Accepted: 07/07/2021] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND Dual-energy computed tomography (DECT) has been used to improve image quality of head and neck squamous cell carcinoma (SCC). This study aimed to assess image quality of laryngeal SCC using linear blending image (LBI), nonlinear blending image (NBI), and noise-optimized virtual monoenergetic image (VMI+) algorithms. METHODS Thirty-four patients with laryngeal SCC were retrospectively enrolled between June 2019 and December 2020. DECT images were reconstructed using LBI (80 kV and M_0.6), NBI, and VMI+ (40 and 55 keV) algorithms. Contrast-to-noise ratio (CNR), tumor delineation, and overall image quality were assessed and compared. RESULTS VMI+ (40 keV) had the highest CNR and provided better tumor delineation than VMI+ (55 keV), LBI, and NBI, while NBI provided better overall image quality than VMI+ and LBI (all corrected p < 0.05). CONCLUSIONS VMI+ (40 keV) and NBI improve image quality of laryngeal SCC and may be preferable in DECT examination.
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Affiliation(s)
- Changjiu He
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jieke Liu
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Shibei Hu
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Haomiao Qing
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongbing Luo
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoli Chen
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Ying Liu
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Peng Zhou
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
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19
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Sun L, Shimunov D, Tan EX, Swisher-Mcclure S, Lin A, Lukens JN, Basu D, Chalian AA, Cannady SB, Newman JG, Rajasekaran K, O'Malley BW, Rassekh CH, Weinstein GS, Loevner LA, Aggarwal C, Singh A, Cohen RB, Bauml JM, Brody RM. Survival and toxicity in patients with human papilloma virus-associated oropharyngeal squamous cell cancer receiving trimodality therapy including transoral robotic surgery. Head Neck 2021; 43:3053-3061. [PMID: 34170052 DOI: 10.1002/hed.26797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 04/26/2021] [Accepted: 06/17/2021] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Patients with oropharyngeal cancer who undergo transoral robotic surgery (TORS) and have high-risk features generally receive adjuvant chemoradiotherapy or trimodality therapy (TMT). The notion that TMT leads to high toxicity is largely based on studies that included human papilloma virus (HPV)-negative cancers and/or nonrobotic surgery; we sought to describe outcomes in HPV-associated oropharyngeal squamous cell cancer (HPV + OPSCC) undergoing TORS-TMT. METHODS In consecutive patients with HPV + OPSCC receiving TMT at an academic center from 2010 to 2017, survival was estimated using Kaplan-Meier methodology, and toxicities were ascertained via chart review. RESULTS In our cohort of 178 patients, 5-year survival was 93.6%. Feeding tube rates were 25.8% at therapy completion and 0.7% at 1 year. Rates of grade ≥ 3 kidney injury, anemia, and neutropenia in cisplatin-treated patients were 2.7%, 3.4%, and 11.0%, respectively. CONCLUSIONS Patients with HPV + OPSCC who underwent TORS-TMT had excellent survival and low rates of toxicity and feeding tube dependence. These outcomes compare favorably to historical cohorts treated with definitive chemoradiotherapy.
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Affiliation(s)
- Lova Sun
- Division of Hematology/Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David Shimunov
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Erik X Tan
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Samuel Swisher-Mcclure
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alexander Lin
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John N Lukens
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Devraj Basu
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ara A Chalian
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Steven B Cannady
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jason G Newman
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Karthik Rajasekaran
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Bert W O'Malley
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christopher H Rassekh
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Gregory S Weinstein
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Laurie A Loevner
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Charu Aggarwal
- Division of Hematology/Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Aditi Singh
- Division of Hematology/Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Roger B Cohen
- Division of Hematology/Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Joshua M Bauml
- Division of Hematology/Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robert M Brody
- Department of Otorhinolaryngology - Head and Neck Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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20
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Multimodality oncologic evaluation of superficial neck and facial lymph nodes. Radiol Med 2021; 126:1074-1084. [PMID: 33993441 DOI: 10.1007/s11547-021-01367-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 04/27/2021] [Indexed: 12/24/2022]
Abstract
Involvement of lymph nodes in patients with head and neck cancers impacts treatment and prognosis. Head and neck lymph nodes are comprised of superficial and deep groups which are interconnected. The deep lymph nodes, predominantly centered along internal jugular veins, are very well-known to radiologists and clinicians. However, superficial lymph nodes that drain lymph from the scalp, face, and neck are much less recognized. Here, we describe the anatomic and imaging features of these superficial lymph nodes on CT, MRI, and PET in oncologic settings.
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21
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Sabiq F, Huang K, Patel A, Banerjee R, Debenham B, Lau H, Skarsgard D, Chen G, Lysack JT, Quon HC. Novel imaging classification system of nodal disease in human papillomavirus-mediated oropharyngeal squamous cell carcinoma prognostic of patient outcomes. Head Neck 2021; 43:1854-1863. [PMID: 33638232 DOI: 10.1002/hed.26657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 01/21/2021] [Accepted: 02/09/2021] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Matted nodes in human papillomavirus (HPV)-mediated oropharyngeal squamous cell carcinoma (OPC) is an independent predictor of distant metastases and decreased overall survival. We aimed to classify imaging patterns of metastatic lymphadenopathy, analyze our classification system for reproducibility, and assess its prognostic value. METHODS The metastatic lymphadenopathy was classified based on radiological characteristics for 216 patients with HPV-mediated OPC. Patient outcomes were compared and inter-rater reliability was calculated. RESULTS The presence of ≥3 abutting lymph nodes with imaging features of surrounding extranodal extension (ENE), one subtype of matted nodes, was associated with worse 5-year overall survival, overall recurrence-free survival, regional recurrence-free survival, and distant recurrence-free survival (p ≤ 0.03). Other patterns were not significantly associated with outcome measures. Overall inter-rater agreement was substantial (κ = 0.73). CONCLUSION One subtype of matted nodes defined by ≥3 abutting lymph nodes with imaging features of surrounding ENE is the radiological marker of worst prognosis.
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Affiliation(s)
- Farahna Sabiq
- Department of Radiology, Division of Neuroradiology, University of Calgary, Calgary, Alberta, Canada
| | - Kitty Huang
- Department of Radiation Oncology, University of Calgary, Calgary, Alberta, Canada
| | - Adarsh Patel
- Department of Radiology, Division of Neuroradiology, University of Calgary, Calgary, Alberta, Canada
| | - Robyn Banerjee
- Department of Radiation Oncology, University of Calgary, Calgary, Alberta, Canada
| | - Brock Debenham
- Department of Radiation Oncology, University of Alberta, Edmonton, Alberta, Canada
| | - Harold Lau
- Department of Radiation Oncology, University of Calgary, Calgary, Alberta, Canada
| | - David Skarsgard
- Department of Radiation Oncology, University of Calgary, Calgary, Alberta, Canada
| | - Guanmin Chen
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
| | - John T Lysack
- Department of Radiology, Division of Neuroradiology, University of Calgary, Calgary, Alberta, Canada
| | - Harvey C Quon
- Department of Radiation Oncology, University of Calgary, Calgary, Alberta, Canada
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22
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Unambiguous advanced radiologic extranodal extension determined by MRI predicts worse outcomes in nasopharyngeal carcinoma: Potential improvement for future editions of N category systems. Radiother Oncol 2021; 157:114-121. [PMID: 33516790 DOI: 10.1016/j.radonc.2021.01.015] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 11/20/2020] [Accepted: 01/06/2021] [Indexed: 01/19/2023]
Abstract
BACKGROUND AND PURPOSE To explore the prognostic value of different radiologic extranodal extension (rENE) grades and their potential improvement for the 8th edition N category in nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS From 2009 to 2013, a cohort of 1887 patients with NPC was retrospectively enrolled and randomized to the training (n = 955) and validation (n = 932) groups. rENE was categorized as follows: grade 0, nodes without rENE; grade 1, nodes with rENE infiltrating the surrounding fat only; grade 2, matted nodes; grade 3, nodes with rENE infiltrating adjacent structures. RESULTS The percentage of patients with MRI-positive cervical nodes was 66.5% (1254/1887), of whom grade 0, 1, 2 and 3 rENE cases accounted for 33.2% (416/1254), 14.9% (187/1254), 36.5% (458/1254) and 15.4% (193/1254), respectively. The kappa coefficients for the inter-rater and intra-rater assessments were 0.63, 0.51, 0.65 and 0.93, and 0.76, 0.69, 0.72 and 1.0 in grade 0, 1, 2 and 3 rENE, respectively. Grade 3 rENE rather than grades 0-2 rENE was an independent unfavorable predictor of overall survival and disease-free survival (P < 0.001). Recursive partitioning analysis was applied to refine the N category: eN0 (N0), eN1 (N1 without grade 3), eN2 (N2 without grade 3), and eN3 (N1/N2 with grade 3, N3). Compared to the current system, the proposed N category performed better in hazard consistency, hazard discrimination, sample size balance and outcome prediction. CONCLUSION Grade 3 rENE was an independent unfavorable indicator of NPC. Upstaging patients in N1-2 with grade 3 rENE to N3 led to a superior prognostic performance.
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23
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Dohopolski M, Chen L, Sher D, Wang J. Predicting lymph node metastasis in patients with oropharyngeal cancer by using a convolutional neural network with associated epistemic and aleatoric uncertainty. Phys Med Biol 2020; 65:225002. [PMID: 33179605 DOI: 10.1088/1361-6560/abb71c] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
There can be significant uncertainty when identifying cervical lymph node (LN) metastases in patients with oropharyngeal squamous cell carcinoma (OPSCC) despite the use of modern imaging modalities such as positron emission tomography (PET) and computed tomography (CT) scans. Grossly involved LNs are readily identifiable during routine imaging, but smaller and less PET-avid LNs are harder to classify. We trained a convolutional neural network (CNN) to detect malignant LNs in patients with OPSCC and used quantitative measures of uncertainty to identify the most reliable predictions. Our dataset consisted of images of 791 LNs from 129 patients with OPSCC who had preoperative PET/CT imaging and detailed pathological reports after neck dissections. These LNs were segmented on PET/CT imaging and then labeled according to the pathology reports. An AlexNet-like CNN was trained to classify LNs as malignant or benign. We estimated epistemic and aleatoric uncertainty by using dropout variational inference and test-time augmentation, respectively. CNN performance was stratified according to the median epistemic and aleatoric uncertainty values calculated using the validation cohort. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.99 on the testing dataset. Sensitivity and specificity were 0.94 and 0.90, respectively. Epistemic and aleatoric uncertainty values were statistically larger for false negative and false positive predictions than for true negative and true positive predictions (p < 0.001). Model sensitivity and specificity were 1.0 and 0.98, respectively, for cases with epistemic uncertainty lower than the median value of the incorrect predictions in the validation dataset. For cases with higher epistemic uncertainty, sensitivity and specificity were 0.67 and 0.41, respectively. Model sensitivity and specificity were 1.0 and 0.98, respectively, for cases with aleatoric uncertainty lower than the median value of the incorrect predictions in the validation dataset. For cases with higher aleatoric uncertainty, sensitivity and specificity were 0.67 and 0.37, respectively. We used a CNN to predict the malignant status of LNs in patients with OPSCC with high accuracy, and we showed that uncertainty can be used to quantify a prediction's reliability. Assigning measures of uncertainty to predictions could improve the accuracy of LN classification by efficiently identifying instances where expert evaluation is needed to corroborate a model's prediction.
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Affiliation(s)
- Michael Dohopolski
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, United States of America
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24
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The diagnostic performance of CT and MRI for detecting extranodal extension in patients with head and neck squamous cell carcinoma: a systematic review and diagnostic meta-analysis. Eur Radiol 2020; 31:2048-2061. [PMID: 32949282 DOI: 10.1007/s00330-020-07281-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 07/15/2020] [Accepted: 09/10/2020] [Indexed: 02/01/2023]
Abstract
OBJECTIVE To review the diagnostic performance of CT and MRI for detecting extranodal extension (ENE) in head and neck squamous cell carcinoma (HNSCC) patients. METHODS MEDLINE and EMBASE databases were searched up to October 7, 2019. Studies that evaluated the diagnostic performance of CT and/or MRI for detecting ENE in HNSCC patients were included. A 2 × 2 table was reconstructed for each study. Pooled sensitivity and specificity were calculated using the bivariate model and hierarchical summary receiver operating characteristic (HSROC) model. Subgroup analyses were performed according to HPV status and radiological features. Pooled correlation coefficient for interobserver agreement was calculated. RESULTS Twenty-two studies including 2478 patients were included. The pooled sensitivity and specificity for detecting ENE were 73% (95% CI, 62-82%) and 83% (95% CI, 75-89%), respectively, for CT, and 60% (95% CI, 49-70%) and 96% (95% CI, 85-99%), respectively, for MRI. There was substantial heterogeneity for both CT and MRI. A threshold effect was present for MRI. On subgroup analysis, the pooled specificity of CT was significantly lower in patients with HPV+ OPSCC than in patients with HPV‑ oral cavity cancer or all HNSCC (74% vs. 87%; p = 0.01). Central node necrosis showed significantly higher pooled sensitivity (81% vs. 51%; p = 0.02), while infiltration of adjacent planes showed significantly higher pooled specificity (94% vs. 65%; p = 0.03). The pooled correlation coefficient was 0.72 (95% CI, 0.60-0.81). CONCLUSION Both CT and MRI show reasonable diagnostic performance for detecting ENE in HNSCC patients and interobserver agreement was substantial. KEY POINTS • Pooled sensitivity and specificity were 73% and 83% for CT and 60% and 96% for MRI without significant difference. • Pooled specificity was lower for HPV+ OPSCC than for HPV‑ oral cavity cancer or all HNSCC (74% vs. 87%, p = 0.01), likely due to central node necrosis. • Central node necrosis showed higher sensitivity (81% vs. 51%; p = 0.02), while infiltration of adjacent planes showed higher specificity (94% vs. 65%; p = 0.03).
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25
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Yeh CH. Editorial for "Prognostic Value of Nodal Matting on MRI in Nasopharyngeal Carcinoma Patients". J Magn Reson Imaging 2020; 53:165-166. [PMID: 32827205 DOI: 10.1002/jmri.27337] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Accepted: 07/13/2020] [Indexed: 01/29/2023] Open
Affiliation(s)
- Chih-Hua Yeh
- Department of Neuroradiology, Chang Gung Memorial Hospital at Linkou and School of Medicine, Chang Gung University, Taoyuan, Taiwan
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26
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Beltz A, Zimmer S, Michaelides I, Evert K, Psychogios G, Bohr C, Künzel J. Significance of Extranodal Extension in Surgically Treated HPV-Positive Oropharyngeal Carcinomas. Front Oncol 2020; 10:1394. [PMID: 32850449 PMCID: PMC7433688 DOI: 10.3389/fonc.2020.01394] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 07/02/2020] [Indexed: 01/25/2023] Open
Abstract
Squamous cell carcinomas of the head and neck are the subject of numerous current studies, especially in view of the increasing incidence of tumors induced by human papillomavirus (HPV) and the latest changes to the TNM classification of oropharyngeal squamous cell carcinoma (OPSCC). In addition to HPV status, the presence of extranodal extension of lymph node metastases represents an important risk and prognostic factor, which has now been integrated into the staging algorithm of the eighth edition of TNM classification for HPV-negative OPSCC. In the past numerous studies had shown a lack of prognostic significance of extranodal extension in HPV-associated tumors. However, extranodal extension–as a possible risk factor even in HPV-positive OPSCC–remains an important subject of current studies, which are now particularly characterized by high numbers of cases. In this paper, diagnostic methods and the prognostic significance of extranodal extension in surgically treated HPV-positive OPSCC are presented and discussed based on relevant literature, and the results of current publications are summarized. Further development of diagnostic criteria and procedures as well as international standardization of clinical diagnostics of extranodal extension should be encouraged. Several studies demonstrate that extranodal extension results in worse survival outcomes even in HPV-positive tumors, in contrast to results of previous studies. Consequently, whether the prognostic significance of extranodal extension is not actually relevant to outcome and the staging algorithm of HPV-positive OPSCC should be questioned and further analyzed.
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Affiliation(s)
- Anna Beltz
- Department of Otorhinolaryngology, University Medical Center Mainz, Mainz, Germany
| | - Stefanie Zimmer
- Institute of Pathology, Tissue Bank, University Medical Center Mainz, Mainz, Germany
| | - Ioannis Michaelides
- Department of Otorhinolaryngology, University Hospital Regensburg, Regensburg, Germany
| | - Katja Evert
- Institute of Pathology, University of Regensburg, Regensburg, Germany
| | - Georgios Psychogios
- Department of Otorhinolaryngology, University Hospital of Ioannina, Ioannina, Greece
| | - Christopher Bohr
- Department of Otorhinolaryngology, University Hospital Regensburg, Regensburg, Germany
| | - Julian Künzel
- Department of Otorhinolaryngology, University Hospital Regensburg, Regensburg, Germany
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27
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Hatten KM, Amin J, Isaiah A. Machine Learning Prediction of Extracapsular Extension in Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma. Otolaryngol Head Neck Surg 2020; 163:992-999. [PMID: 32600154 DOI: 10.1177/0194599820935446] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To determine whether machine learning (ML) can predict the presence of extracapsular extension (ECE) prior to treatment, using common oncologic variables, in patients with human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC). STUDY DESIGN Retrospective database review. SETTING National Cancer Database study. METHODS All patients with HPV-associated OPSCC treated surgically between January 1, 2010, and December 31, 2015, were selected from the National Cancer Database. Patients were excluded if surgical pathology reports did not include information regarding primary tumor stage, number of metastatic regional lymph nodes, size of largest metastatic regional lymph node, and tumor grade. The data were split into a random distribution of 80% for training and 20% for testing with ML methods. RESULTS A total of 3753 adults with surgically treated HPV-associated OPSCC met criteria for inclusion in the study. Approximately 38% of these patients treated with surgical management demonstrated ECE. ML models demonstrated modest accuracy in predicting ECE, with the areas under the receiver operating characteristic curves ranging from 0.58 to 0.68. The conditional inference tree model (0.66) predicted the metastatic lymph node number to be the most important predictor of ECE. CONCLUSION Despite a large cohort and the use of ML algorithms, the power of clinical and oncologic variables to predict ECE in HPV-associated OPSCC remains limited.
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Affiliation(s)
- Kyle M Hatten
- Department of Otorhinolaryngology-Head and Neck Surgery, School of Medicine, University of Maryland, Baltimore, Maryland, USA
| | - Julian Amin
- Department of Otorhinolaryngology-Head and Neck Surgery, School of Medicine, University of Maryland, Baltimore, Maryland, USA
| | - Amal Isaiah
- Department of Otorhinolaryngology-Head and Neck Surgery, School of Medicine, University of Maryland, Baltimore, Maryland, USA
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Yan F, Byun YJ, Nguyen SA, Stalcup ST, Day TA. Predictive value of computed tomography in identifying extranodal extension in human papillomavirus-positive versus human papillomavirus-negative head and neck cancer. Head Neck 2020; 42:2687-2695. [PMID: 32484583 DOI: 10.1002/hed.26281] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 04/02/2020] [Accepted: 05/12/2020] [Indexed: 01/26/2023] Open
Abstract
Pathologic extranodal extension (pENE) impacts treatment planning and is an important prognostic indicator for patients with head and neck squamous cell carcinoma (HNSCC). Computed tomography (CT) is a commonly used modality for assessment of radiographic ENE (rENE). To determine the predictive value of CT-identified rENE in predicting pENE, we performed a systematic review through a search of 4 databases (PubMed, Scopus, Cochrane, and OVID). Meta-analysis of diagnostic performance based on human papillomavirus (HPV) status was conducted. For HPV-negative HNSCC, pooled sensitivity, specificity, and accuracy were 60.6%, 93.3%, and 82.6%, respectively. Overall positive predictive value (PPV) was 82.7%. For HPV-positive HNSCC, pooled sensitivity, specificity, and accuracy were 77.7%, 72.2%, and 63.8%, respectively. Overall PPV was 68.6%. Significant differences were observed in diagnostic performance parameters between the two cohorts. The radiographic characteristics of HPV-positive and HPV-negative nodal metastases in HNSCC differ and radiographic evaluation of ENE in HPV-positive nodes is challenging. Development of refined imaging characteristics of HPV-positive nodes is needed to improve diagnostic performance.
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Affiliation(s)
- Flora Yan
- Head and Neck Tumor Center, Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Young J Byun
- Head and Neck Tumor Center, Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA.,University of Central Florida College of Medicine, Orlando, Florida, USA
| | - Shaun A Nguyen
- Head and Neck Tumor Center, Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Seth T Stalcup
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Terry A Day
- Head and Neck Tumor Center, Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA
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Kann BH, Payabvash S, Aneja S. Reply to A.B. Simon et al. J Clin Oncol 2020; 38:1869-1870. [PMID: 32271673 DOI: 10.1200/jco.20.00402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
- Benjamin H Kann
- Benjamin H. Kann, MD, Department of Radiation Oncology, Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, and Artificial Intelligence in Medicine Program, Brigham and Women's Hospital, Boston, MA; Sam Payabvash, MD, Department of Radiology, Yale School of Medicine, New Haven, CT; and Sanjay Aneja, MD, Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT
| | - Sam Payabvash
- Benjamin H. Kann, MD, Department of Radiation Oncology, Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, and Artificial Intelligence in Medicine Program, Brigham and Women's Hospital, Boston, MA; Sam Payabvash, MD, Department of Radiology, Yale School of Medicine, New Haven, CT; and Sanjay Aneja, MD, Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT
| | - Sanjay Aneja
- Benjamin H. Kann, MD, Department of Radiation Oncology, Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, and Artificial Intelligence in Medicine Program, Brigham and Women's Hospital, Boston, MA; Sam Payabvash, MD, Department of Radiology, Yale School of Medicine, New Haven, CT; and Sanjay Aneja, MD, Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT
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Kann BH, Hicks DF, Payabvash S, Mahajan A, Du J, Gupta V, Park HS, Yu JB, Yarbrough WG, Burtness BA, Husain ZA, Aneja S. Multi-Institutional Validation of Deep Learning for Pretreatment Identification of Extranodal Extension in Head and Neck Squamous Cell Carcinoma. J Clin Oncol 2019; 38:1304-1311. [PMID: 31815574 DOI: 10.1200/jco.19.02031] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
PURPOSE Extranodal extension (ENE) is a well-established poor prognosticator and an indication for adjuvant treatment escalation in patients with head and neck squamous cell carcinoma (HNSCC). Identification of ENE on pretreatment imaging represents a diagnostic challenge that limits its clinical utility. We previously developed a deep learning algorithm that identifies ENE on pretreatment computed tomography (CT) imaging in patients with HNSCC. We sought to validate our algorithm performance for patients from a diverse set of institutions and compare its diagnostic ability to that of expert diagnosticians. METHODS We obtained preoperative, contrast-enhanced CT scans and corresponding pathology results from two external data sets of patients with HNSCC: an external institution and The Cancer Genome Atlas (TCGA) HNSCC imaging data. Lymph nodes were segmented and annotated as ENE-positive or ENE-negative on the basis of pathologic confirmation. Deep learning algorithm performance was evaluated and compared directly to two board-certified neuroradiologists. RESULTS A total of 200 lymph nodes were examined in the external validation data sets. For lymph nodes from the external institution, the algorithm achieved an area under the receiver operating characteristic curve (AUC) of 0.84 (83.1% accuracy), outperforming radiologists' AUCs of 0.70 and 0.71 (P = .02 and P = .01). Similarly, for lymph nodes from the TCGA, the algorithm achieved an AUC of 0.90 (88.6% accuracy), outperforming radiologist AUCs of 0.60 and 0.82 (P < .0001 and P = .16). Radiologist diagnostic accuracy improved when receiving deep learning assistance. CONCLUSION Deep learning successfully identified ENE on pretreatment imaging across multiple institutions, exceeding the diagnostic ability of radiologists with specialized head and neck experience. Our findings suggest that deep learning has utility in the identification of ENE in patients with HNSCC and has the potential to be integrated into clinical decision making.
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Affiliation(s)
- Benjamin H Kann
- Department of Radiation Oncology, Dana-Farber Cancer Institute/Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Daniel F Hicks
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Sam Payabvash
- Department of Radiology, Yale School of Medicine, New Haven, CT
| | - Amit Mahajan
- Department of Radiology, Yale School of Medicine, New Haven, CT
| | - Justin Du
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT
| | - Vishal Gupta
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Henry S Park
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT
| | - James B Yu
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT
| | - Wendell G Yarbrough
- Department of Otolaryngology/Head and Neck Surgery, University of North Carolina School of Medicine, Chapel Hill, NC
| | | | - Zain A Husain
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Sanjay Aneja
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT
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Douglas C, Crosbie R, Young D, Montgomery J, O'Neill G, McArthur C. Accuracy of contrast-enhanced CT and predictive factors for extracapsular spread in unknown primary head and neck squamous cell cancer. Clin Radiol 2019; 75:77.e23-77.e28. [PMID: 31679816 DOI: 10.1016/j.crad.2019.09.138] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 09/24/2019] [Indexed: 10/25/2022]
Abstract
AIM To determine the accuracy of contrast-enhanced computed tomography (CECT) for nodal extracapsular spread (ECS) and identify predictive radiological signs and clinicopathological features for ECS in unknown-primary head and neck squamous cell cancer (UPHNSCC). MATERIALS AND METHODS The CECT imaging of patients who underwent primary neck dissection for UPHNSCC during 2011-2015 was analysed. The largest pathological-looking node at each radiologically involved level was evaluated in consensus by two head and neck radiologists. Parameters included longest diameter, margin sharpness, haziness in adjacent fat, necrosis, and loss of fat plane with adjacent structures. Independent assessment was also made regarding the presence/absence of ECS. Findings and clinicopathological parameters were correlated with histopathology. RESULTS Thirty-one patients with 39 neck levels had metastatic nodal involvement determined on CECT. Confirmed ECS was found at 26 levels in 23 patients. Sensitivity of radiological assessment for ECS by nodal level was 81-85% (95% confidence interval [CI]=65-93%) and specificity 46-54% (95% CI=19-81%); kappa 0.87. On univariate analysis based on the largest involved node per patient, longest diameter being ≥30 mm (p=0.007), haziness in adjacent fat (p=0.023), increasing age (p=0.006), and more advanced pathological nodal status (p=0.027) were statistically significantly associated with ECS. Haziness and increasing age were independent predictors on multivariate analysis (odds ratio [OR]=26.4 and 1.24). CONCLUSION Expert assessment of ECS on CECT had good sensitivity with excellent interobserver agreement. A longest nodal diameter of ≥30 mm, haziness in the surrounding fat on CECT, advanced pathological nodal status, and advancing patient age were significantly associated with ECS in UPHNSCC patients, findings not previously reported.
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Affiliation(s)
- C Douglas
- Department of Otolaryngology - Head and Neck Surgery, Queen Elizabeth University Hospital, 1345 Govan Rd, Glasgow G51 4TF, UK
| | - R Crosbie
- Department of Otolaryngology - Head and Neck Surgery, Queen Elizabeth University Hospital, 1345 Govan Rd, Glasgow G51 4TF, UK
| | - D Young
- Department of Mathematics and Statistics, Strathclyde University, 16 Richmond Street, Glasgow G1 1XQ, UK
| | - J Montgomery
- Department of Otolaryngology - Head and Neck Surgery, Queen Elizabeth University Hospital, 1345 Govan Rd, Glasgow G51 4TF, UK
| | - G O'Neill
- Department of Radiology - Glasgow Royal Infirmary, 84 Castle Street, Glasgow G4 0SF, UK
| | - C McArthur
- Department of Radiology - Glasgow Royal Infirmary, 84 Castle Street, Glasgow G4 0SF, UK.
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Faraji F, Aygun N, Coquia SF, Gourin CG, Tan M, Rooper LM, Eisele DW, Fakhry C. Computed tomography performance in predicting extranodal extension in HPV‐positive oropharynx cancer. Laryngoscope 2019; 130:1479-1486. [DOI: 10.1002/lary.28237] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 07/20/2019] [Accepted: 07/26/2019] [Indexed: 12/13/2022]
Affiliation(s)
- Farhoud Faraji
- Division of Otolaryngology–Head and Neck Surgery, Department of SurgeryUniversity of California San Diego Health San Diego California U.S.A
| | - Nafi Aygun
- The Russell H. Morgan Department of Radiology and Radiological SciencesJohns Hopkins Hospital Baltimore Maryland U.S.A
| | - Stephanie F. Coquia
- The Russell H. Morgan Department of Radiology and Radiological SciencesJohns Hopkins Hospital Baltimore Maryland U.S.A
| | - Christine G. Gourin
- Department of Otolaryngology–Head and Neck SurgeryJohns Hopkins University School of Medicine Baltimore Maryland U.S.A
| | - Marietta Tan
- Department of Otolaryngology–Head and Neck SurgeryJohns Hopkins University School of Medicine Baltimore Maryland U.S.A
| | - Lisa M. Rooper
- Department of PathologyJohns Hopkins University School of Medicine Baltimore Maryland U.S.A
| | - David W. Eisele
- Department of Otolaryngology–Head and Neck SurgeryJohns Hopkins University School of Medicine Baltimore Maryland U.S.A
| | - Carole Fakhry
- Department of Otolaryngology–Head and Neck SurgeryJohns Hopkins University School of Medicine Baltimore Maryland U.S.A
- Bloomberg‐Kimmel Institute for Cancer Immunotherapy at Johns Hopkins Baltimore Maryland U.S.A
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public Health Baltimore Maryland U.S.A
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Molecular prognosticators in clinically and pathologically distinct cohorts of head and neck squamous cell carcinoma-A meta-analysis approach. PLoS One 2019; 14:e0218989. [PMID: 31310629 PMCID: PMC6634788 DOI: 10.1371/journal.pone.0218989] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Accepted: 06/14/2019] [Indexed: 02/06/2023] Open
Abstract
Head and neck squamous cell carcinomas (HNSCC) includes multiple subsites that exhibit differential treatment outcome, which is in turn reflective of tumor stage/histopathology and molecular profile. This study hypothesized that the molecular profile is an accurate prognostic adjunct in patients triaged based on clinico-pathological characteristics. Towards this effect, publically available micro-array datasets (n = 8), were downloaded, classified based on HPV association (n = 83) and site (tongue n = 88; laryngopharynx n = 53; oropharynx n = 51) and re-analyzed (Genespring; v13.1). The significant genes were validated in respective cohorts in The Cancer Genome Atlas (TCGA) for correlation with clinico-pathological parameters/survival. The gene entities (n = 3258) identified from HPV based analysis, when validated in TCGA identified the subset specifically altered in HPV+ HNSCC (n = 63), with three genes showing survival impact (RPP25, NUDCD2, NOVA1). Site-specific meta-analysis identified respective differentials (tongue: 3508, laryngopharynx: 4893, oropharynx: 2386); validation in TCGA revealed markers with high incidence (altered in >10% of patients) in tongue (n = 331), laryngopharynx (n = 701) and oropharynx (n = 404). Assessment of these genes in clinical sub-cohorts of TCGA indicated that early stage tongue (MTFR1, C8ORF33, OTUD6B) and laryngeal cancers (TWISTNB, KLHL13 and UBE2Q1) were defined by distinct prognosticators. Similarly, correlation with perineural/angiolymophatic invasion, identified discrete marker panels with survival impact (tongue: NUDCD1, PRKC1; laryngopharynx: SLC4A1AP, PIK3CA, AP2M1). Alterations in ANO1, NUDCD1, PIK3CA defined survival in tongue cancer patients with nodal metastasis (node+ECS-), while EPS8 is a significant differential in node+ECS- laryngopharyngeal cancers. In oropharynx, wherein HPV is a major etiological factor, distinct prognosticators were identified in HPV+ (ECHDC2, HERC5, GGT6) and HPV- (GRB10, EMILIN1, FNDC1). Meta-analysis in combination with TCGA validation carried out in this study emphasized on the molecular heterogeneity inherent within HNSCC; the feasibility of leveraging this information for improving prognostic efficacy is also established. Subject to large scale clinical validation, the marker panel identified in this study can prove to be valuable prognostic adjuncts.
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Moratin J, Metzger K, Engel M, Hoffmann J, Freudlsperger C, Freier K, Horn D. The occurrence of cervical metastases in squamous cell carcinoma of the tongue: Is there a rationale for bilateral neck dissection in early-stage tumors? J Craniomaxillofac Surg 2019; 47:1134-1138. [DOI: 10.1016/j.jcms.2019.03.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 02/05/2019] [Accepted: 03/04/2019] [Indexed: 10/27/2022] Open
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Ariji Y, Sugita Y, Nagao T, Nakayama A, Fukuda M, Kise Y, Nozawa M, Nishiyama M, Katumata A, Ariji E. CT evaluation of extranodal extension of cervical lymph node metastases in patients with oral squamous cell carcinoma using deep learning classification. Oral Radiol 2019; 36:148-155. [DOI: 10.1007/s11282-019-00391-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 06/05/2019] [Indexed: 12/13/2022]
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Wu WL, Wang CL, Li D, Luo J, Ye JY, Xu SS. Multiphase contrast-enhanced computed tomography imaging features of salivary duct carcinoma: differentiation from other salivary gland malignancies. Oral Surg Oral Med Oral Pathol Oral Radiol 2019; 128:543-551. [PMID: 31277959 DOI: 10.1016/j.oooo.2019.05.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 05/15/2019] [Accepted: 05/24/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVE The aim of this study was to investigate the imaging features of salivary duct carcinoma (SDC) with multiphase contrast-enhanced computed tomography (CECT) and to compare them with those of mucoepidermoid carcinoma (MEC), adenoid cystic carcinoma (ACC), and acinic cell carcinoma. STUDY DESIGN A total of 63 patients with histologically diagnosed salivary gland malignancies underwent preoperative multiphase CECT. Clinical information, location, size, mass pattern, enhancement pattern, borders, invasion of adjacent tissues, and lymph node metastasis were evaluated. Computed tomography (CT) number attenuation patterns were calculated. RESULTS SDCs were significantly more common in males and in the parotid gland (P ≤ .018). They were more likely to invade into adjacent tissues and metastasize to lymph nodes (P ≤ .032). Six SDCs (66.7%) had comedonecrosis, as detected on histopathologic examination, and 3 lesions presented cribriform necrosis on CECT. CT numbers during delayed-phase scanning were significantly higher in SDC than in ACC (P = .031). Significant differences were discovered between MEC and ACC for CT numbers during arterial-phase scanning (P = .047) and in the ratio of CT numbers (P = .018). CONCLUSIONS SDC exhibits some specific CT features, and multiphase CECT imaging is useful in the differential diagnosis of salivary gland malignancies.
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Affiliation(s)
- Wen-Li Wu
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Cheng-Long Wang
- Department of Pathology, Chongqing Traditional Chinese Medicine Hospital, Chongqing, China
| | - Dan Li
- Department of Pathology, College of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Jin Luo
- Key Laboratory of Optoelectronic Technology and Systems of the Ministry of Education, Chongqing University, Chongqing, China
| | - Jun-Yong Ye
- Key Laboratory of Optoelectronic Technology and Systems of the Ministry of Education, Chongqing University, Chongqing, China
| | - Sheng-Sheng Xu
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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Tian S, Ferris MJ, Switchenko JM, Magliocca KR, Cassidy RJ, Jhaveri J, Aiken AH, Baugnon KL, Hudgins PA, Kendi ATK, Patel MR, Saba NF, Curran WJ, Beitler JJ. Prognostic value of radiographically defined extranodal extension in human papillomavirus-associated locally advanced oropharyngeal carcinoma. Head Neck 2019; 41:3056-3063. [PMID: 31046181 DOI: 10.1002/hed.25791] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Revised: 03/11/2019] [Accepted: 04/17/2019] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Pathologic extranodal extension (ENE) has traditionally guided the management of head and neck cancers. The prognostic value of radiographic ENE (rENE) in human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (HPV + OPX) is uncertain. METHODS Patients with HPV + OPX with adequate pretreatment radiographic nodal evaluation from a single institution were analyzed. rENE status was determined by neuroradiologists' at time of diagnosis. Distant metastasis-free survival (DMFS), overall survival (OS), and locoregional recurrence-free survival (LRFS) were estimated using Kaplan-Meier methods. Cox proportional hazards models were fit to assess the impact of rENE on survival endpoints. RESULTS Hundred sixty-eight patients with OPX + squamous cell carcinomas diagnosed between April 2008 and December 2014 were included for analysis with median follow-up of 3.3 years. Eighty-eight percent of patients received concurrent chemoradiotherapy. rENE was not prognostic; its presence in patients with HPV + OPX did not significantly impact OS, LRFS, or DMFS. CONCLUSIONS In patients with HPV + OPX, rENE was not significantly associated with OS, LRFS, or DMFS.
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Affiliation(s)
- Sibo Tian
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | - Matthew J Ferris
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | | | - Kelly R Magliocca
- Department of Pathology & Laboratory Medicine, Emory University School of Medicine, Atlanta, Georgia
| | - Richard J Cassidy
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | - Jaymin Jhaveri
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | - Ashley H Aiken
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Kristen L Baugnon
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Patricia A Hudgins
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Ayse T K Kendi
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Mihir R Patel
- Department of Otolaryngology - Head and Neck Surgery, Emory University School of Medicine, Atlanta, Georgia
| | - Nabil F Saba
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | - Walter J Curran
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | - Jonathan J Beitler
- Department of Otolaryngology - Head and Neck Surgery, Emory University School of Medicine, Atlanta, Georgia.,Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
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Noor A, Mintz J, Patel S, Bajic N, Boase S, Sethi N, Foreman A, Krishnan S, Hodge J. Predictive value of computed tomography in identifying extracapsular spread of cervical lymph node metastases in p16 positive oropharyngeal squamous cell carcinoma. J Med Imaging Radiat Oncol 2019; 63:500-509. [DOI: 10.1111/1754-9485.12888] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 03/24/2019] [Indexed: 11/27/2022]
Affiliation(s)
- Anthony Noor
- Department of Otolaryngology, Head and Neck Surgery Royal Adelaide Hospital University of Adelaide Adelaide South Australia Australia
| | - Jack Mintz
- Department of Otolaryngology, Head and Neck Surgery Royal Adelaide Hospital University of Adelaide Adelaide South Australia Australia
| | - Sandy Patel
- Department of Radiology Royal Adelaide Hospital Adelaide South Australia Australia
| | - Nicholas Bajic
- Department of Radiology Royal Adelaide Hospital Adelaide South Australia Australia
| | - Sam Boase
- Department of Otolaryngology, Head and Neck Surgery Royal Adelaide Hospital University of Adelaide Adelaide South Australia Australia
| | - Neeraj Sethi
- Department of Otolaryngology, Head and Neck Surgery Royal Adelaide Hospital University of Adelaide Adelaide South Australia Australia
| | - Andrew Foreman
- Department of Otolaryngology, Head and Neck Surgery Royal Adelaide Hospital University of Adelaide Adelaide South Australia Australia
| | - Suren Krishnan
- Department of Otolaryngology, Head and Neck Surgery Royal Adelaide Hospital University of Adelaide Adelaide South Australia Australia
| | - John‐Charles Hodge
- Department of Otolaryngology, Head and Neck Surgery Royal Adelaide Hospital University of Adelaide Adelaide South Australia Australia
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Kann BH, Aneja S, Loganadane GV, Kelly JR, Smith SM, Decker RH, Yu JB, Park HS, Yarbrough WG, Malhotra A, Burtness BA, Husain ZA. Pretreatment Identification of Head and Neck Cancer Nodal Metastasis and Extranodal Extension Using Deep Learning Neural Networks. Sci Rep 2018; 8:14036. [PMID: 30232350 PMCID: PMC6145900 DOI: 10.1038/s41598-018-32441-y] [Citation(s) in RCA: 109] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 09/07/2018] [Indexed: 12/14/2022] Open
Abstract
Identification of nodal metastasis and tumor extranodal extension (ENE) is crucial for head and neck cancer management, but currently only can be diagnosed via postoperative pathology. Pretreatment, radiographic identification of ENE, in particular, has proven extremely difficult for clinicians, but would be greatly influential in guiding patient management. Here, we show that a deep learning convolutional neural network can be trained to identify nodal metastasis and ENE with excellent performance that surpasses what human clinicians have historically achieved. We trained a 3-dimensional convolutional neural network using a dataset of 2,875 CT-segmented lymph node samples with correlating pathology labels, cross-validated and fine-tuned on 124 samples, and conducted testing on a blinded test set of 131 samples. On the blinded test set, the model predicted ENE and nodal metastasis each with area under the receiver operating characteristic curve (AUC) of 0.91 (95%CI: 0.85-0.97). The model has the potential for use as a clinical decision-making tool to help guide head and neck cancer patient management.
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Affiliation(s)
- Benjamin H Kann
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, USA.
| | - Sanjay Aneja
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, USA
| | | | - Jacqueline R Kelly
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, USA
| | - Stephen M Smith
- Department of Pathology, Yale School of Medicine, New Haven, USA
| | - Roy H Decker
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, USA
| | - James B Yu
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, USA
| | - Henry S Park
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, USA
| | - Wendell G Yarbrough
- Department of Head and Neck Surgery, Yale School of Medicine, New Haven, USA
| | - Ajay Malhotra
- Department of Radiology, Yale School of Medicine, New Haven, USA
| | | | - Zain A Husain
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, USA
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Can MR textural analysis improve the prediction of extracapsular nodal spread in patients with oral cavity cancer? Eur Radiol 2018; 28:5010-5018. [DOI: 10.1007/s00330-018-5524-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Revised: 04/23/2018] [Accepted: 05/03/2018] [Indexed: 01/18/2023]
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