Neoadjuvant Nivolumab Plus Chemotherapy Followed By Response-Adaptive Therapy for HPV+ Oropharyngeal Cancer: OPTIMA II Phase 2 Open-Label Nonrandomized Clinical Trial.

Importance: Immune checkpoint inhibitors improve survival in recurrent and/or metastatic head and neck cancer, yet their role in curative human papillomavirus-positive oropharyngeal cancer (HPV+ OPC) remains undefined. Neoadjuvant nivolumab and chemotherapy followed by response-adaptive treatment in HPV+ OPC may increase efficacy while reducing toxicity. Objective: To determine the deep response rate and tolerability of the addition of neoadjuvant nivolumab to chemotherapy followed by response-adapted locoregional therapy (LRT) in patients with HPV+ OPC. Design, Setting, and Participants: This phase 2 nonrandomized clinical trial conducted at a single academic center enrolled 77 patients with locoregionally advanced HPV+ OPC from 2017 to 2020. Data analyses were performed from February 10, 2021, to January 9, 2023. Interventions: Addition of nivolumab to neoadjuvant nab-paclitaxel and carboplatin (studied in the first OPTIMA trial) followed by response-adapted LRT in patients with HPV+ OPC stages III to IV. Main Outcomes and Measures: Primary outcome was deep response rate to neoadjuvant nivolumab plus chemotherapy, defined as the proportion of tumors with 50% or greater shrinkage per the Response Evaluation Criteria in Solid Tumors 1.1. Secondary outcomes were progression-free survival (PFS) and overall survival (OS). Swallowing function, quality of life, and tissue- and blood-based biomarkers, including programmed death-ligand 1 (PD-L1) expression and circulating tumor HPV-DNA (ctHPV-DNA), were also evaluated. Results: The 73 eligible patients (median [range] age, 61 [37-82] years; 6 [8.2%] female; 67 [91.8%] male) started neoadjuvant nivolumab and chemotherapy. Deep responses were observed in 51 patients (70.8%; 95% CI, 0.59-0.81). Subsequent risk- and response-adaptive therapy was assigned as follows: group A, single-modality radiotherapy alone or transoral robotic surgery (28 patients); group B, intermediate-dose chemoradiotherapy of 45 to 50 Gray (34 patients); and group C, regular-dose chemoradiotherapy of 70 to 75 Gray (10 patients). Two-year PFS and OS were 90.0% (95% CI, 0.80-0.95) and 91.4% (95% CI, 0.82-0.96), respectively. By response-adapted group, 2-year PFS and OS for group A were 96.4% and 96.4%, and group B, 88.0% and 91.0%, respectively. Lower enteral feeding rates and changes in weight, as well as improved swallowing, were observed among patients who received response-adapted LRT. Pathologic complete response rate among patients who underwent transoral robotic surgery was 67.0%. PD-L1 expression was nonsignificantly higher for deeper responses and improved PFS, and ctHPV-DNA clearance was significantly associated with improved PFS. Conclusions and Relevance: This phase 2 nonrandomized clinical trial found that neoadjuvant nivolumab and chemotherapy followed by response-adapted LRT is feasible and has favorable tolerability, excellent OS, and improved functional outcomes in HPV+ OPC, including among patients with high-risk disease. Moreover, addition of nivolumab may benefit high PD-L1 expressors, and sensitive dynamic biomarkers (eg, ctHPV-DNA) are useful for patient selection. Trial Registration: ClinicalTrials.gov Identifier: NCT03107182.

Imaging features and surgical management of giant parathyroid adenoma with autoinfarction.

Autoinfarction of a parathyroid adenoma can have an atypical clinicoradiologic features that can mimic an inflammatory process or malignancy. In addition, the associated fibrosis makes surgical resection more challenging than for regular parathyroid adenomas. The implications of these findings are that while autoinfarction of parathyroid adenomas is a rare phenomenon, this entity should be considered when there are heterogeneous and cystic components on imaging in patients without hypercalcemia. Ultimately, histopathology is necessary for definitive diagnosis.

Early Postoperative Magnetic Resonance Imaging Findings Related to Electrocauterization for Cerebellar Reduction During Chiari Decompression Surgery.

BACKGROUND: Cerebellar tonsillar reduction or resection can be performed as part of the surgical management of Chiari type 1 malformation when it is accompanied by symptomatic brainstem compression or syringomyelia. The purpose of this study is to characterize the early postoperative magnetic resonance imaging (MRI) findings in patients with Chiari type 1 malformations who undergo cerebellar tonsillar reduction via electrocautery. METHODS: The extent of cytotoxic edema and microhemorrhages demonstrated on MRI scans obtained within 9 days following surgery was assessed and correlated with neurological symptoms. RESULTS: Cytotoxic edema was found on all postoperative MRI examinations included in this series, with superimposed hemorrhage in 12 of 16 patients (75%) and was primarily located along the margins of the cauterized inferior cerebellum. Cytotoxic edema was present beyond the margins of the cauterized cerebellar tonsils in 5 of 16 patients (31%) and was associated with new focal neurological deficits in 4 of 5 patients (80%). CONCLUSION: Cytotoxic edema and hemorrhages along the cerebellar tonsil cautery margins can be expected findings in early postoperative MRI in patients who undergo Chiari decompression accompanied by tonsillar reduction. However, the presence of cytotoxic edema beyond these regions can be associated with new focal neurological symptoms.

Advances in the Radiological Evaluation of and Theranostics for Glioblastoma.

Imaging is essential for evaluating patients with glioblastoma. Traditionally a multimodality undertaking, CT, including CT cerebral blood profusion, PET/CT with traditional fluorine-18 fluorodeoxyglucose (18F-FDG), and MRI have been the mainstays for diagnosis and post-therapeutic assessment. However, recent advances in these modalities, in league with the emerging fields of radiomics and theranostics, may prove helpful in improving diagnostic accuracy and treating the disease.

Recent Advances in Deep Learning and Medical Imaging for Head and Neck Cancer Treatment: MRI, CT, and PET Scans.

Deep learning techniques have been developed for analyzing head and neck cancer imaging. This review covers deep learning applications in cancer imaging, emphasizing tumor detection, segmentation, classification, and response prediction. In particular, advanced deep learning techniques, such as convolutional autoencoders, generative adversarial networks (GANs), and transformer models, as well as the limitations of traditional imaging and the complementary roles of deep learning and traditional techniques in cancer management are discussed. Integration of radiomics, radiogenomics, and deep learning enables predictive models that aid in clinical decision-making. Challenges include standardization, algorithm interpretability, and clinical validation. Key gaps and controversies involve model generalizability across different imaging modalities and tumor types and the role of human expertise in the AI era. This review seeks to encourage advancements in deep learning applications for head and neck cancer management, ultimately enhancing patient care and outcomes.

MRI radiomics and potential applications to glioblastoma.

MRI plays an important role in the evaluation of glioblastoma, both at initial diagnosis and follow up after treatment. Quantitative analysis via radiomics can augment the interpretation of MRI in terms of providing insights regarding the differential diagnosis, genotype, treatment response, and prognosis. The various MRI radiomic features of glioblastoma are reviewed in this article.

A preliminary diagnostic accuracy study of quantitative MRI biomarkers for differentiating parotid tumor types.

Background: Differentiating among the different types of parotid tumors on imaging is useful for guiding clinical disposition, which ultimately may lead to surgical management. The goal of this study was to determine whether quantitative T2 signal characteristics and morphologic features on magnetic resonance imaging (MRI) can serve as predictive biomarkers for distinguishing between tumor types. Methods: A retrospective review of T2-weighted MRIs in patients with pathology-proven parotid tumors was performed. Quantitative T2 maps and surface regularity measurements of the tumors were obtained via semi-automated regions of interest (ROI). Linear Discriminant Analysis was used to populate the receiver operating characteristics (ROCs) curves for these variables. A P value of <0.05 was considered to be significant. Results: A total of 35 tumors (21 benign and 14 malignant neoplasms) were included in this analysis. For differentiating the benign versus malignant classes of parotid tumors, T2 signal and surface regularity combined yielded an area under the curve of 0.62 (P value: 0.2) through the ROC analysis. However, for the pleomorphic adenomas versus other types of parotid tumors, using both T2 signal and surface regularity yielded an area under the curve of 0.81 (P value: 0.007) through the ROC analysis. Conclusions: T2 signal and surface regularity combined can significantly differentiate pleomorphic adenomas from other types of parotid tumors and can potentially be used as a predictive imaging biomarker.

Evaluation of an Automated Reminder System for Reducing Missed MRI Appointments.

Background: The high frequency of missed appointments continues to be a burden on healthcare providers, leading to decreased productivity, quality of service, and quality of outcome. The purpose of this study is to evaluate the effectiveness of Televox's automated appointment reminder service in reducing the missed appointment rate for MRI (magnetic resonance imaging). The appointment reminders were sent 72 h in advance. The total and no-show numbers were tallied to calculate missed appointment rates. Comparison of the missed appointment rate with and without Televox implementation and different payment types was performed. Temporal comparisons were also made across the corresponding time periods in order to control for seasonal fluctuations. Results: An insignificant decline in missed appointment rates was found in locations implementing Televox (P = .495) overall, although a significant decrease in missed appointments was found among Medicaid patients (P = .0381). Conclusion: Implementation of Televox appointment reminder systems did not significantly affect appointment attendance overall, but could be more useful specifically for encouraging Medicaid patients to attend MRI appointments.

Characterizing Lymph Node Burden With Elective Unilateral Neck Irradiation in Human Papillomavirus-Positive Tonsil Squamous Cell Carcinoma: Defining the Upper Limits.

Objectives Elective unilateral neck irradiation in well-lateralized tonsil carcinoma for N2b disease is controversial. Metrics regarding nodal burden beyond the N-stage to define the upper limit of this de-escalation approach remain limited. We investigated the role of nodal number, level, and volume on outcomes in patients with well-lateralized tonsil carcinoma treated with this approach. Methods A total of 37 patients received radiotherapy (RT) with unilateral neck coverage for well-lateralized tonsil cancer. Of patients, 95% had p16+ disease, and 81% were staged with positron emission tomography/computed tomography. The majority of patients received definitive chemoradiation on prospective de-escalation trials. Ten patients had ipsilateral neck dissections and were treated adjuvantly. The median RT dose to the ipsilateral neck (generally II-IV) was 45 Gy. The effects of nodal number, max dimension, volume, and level on recurrence-free survival (RFS) and overall survival (OS) were to be analyzed via Cox proportional hazards (Cox-PH). Results After a median follow-up of 3.9 years, two-year RFS and two-year OS were 100% and 97%, respectively. Given the 0% contralateral recurrence rate, Cox-PH analysis was not performed. Of patients, 70% were American Joint Committee on Cancer (AJCC) 7th edition N2b, with a median number of nodes, number of nodal levels, max dimension, and volume of two, one, 3.4 cm, and 15.6 cc, respectively. There were several patients with low-lying nodes; aggregate nodal volume measured was up to 85.4 cc. Conclusion Unilateral neck irradiation in well-lateralized tonsil carcinoma resulted in no contralateral recurrence. Nodal volume, level, and number do not seem to have a significant impact on outcomes.

Imaging Features of Intratumoral Injection of NBTXR3 for Head and Neck Squamous Cell Carcinoma Lymph Node Metastases.

NBTXR3 nanoparticle injection is a relatively novel radioenhancer for treatment of various cancers. CT scans following NBTXR3 injection of metastatic lymph nodes from head and neck squamous cell carcinoma were reviewed in a small series of patients. The radioenhancing appears as hyperattenuating, with a mean attenuation of the injected material of 1516 HU. The material was found to leak beyond the margins of the tumor in some cases.

Semantic Segmentation of Extraocular Muscles on Computed Tomography Images Using Convolutional Neural Networks.

Computed tomography (CT) imaging of the orbit with measurement of extraocular muscle size can be useful for diagnosing and monitoring conditions that affect extraocular muscles. However, the manual measurement of extraocular muscle size can be time-consuming and tedious. The purpose of this study is to evaluate the effectiveness of deep learning algorithms in segmenting extraocular muscles and measuring muscle sizes from CT images. Consecutive CT scans of orbits from 210 patients between 1 January 2010 and 31 December 2019 were used. Extraocular muscles were manually annotated in the studies, which were then used to train the deep learning algorithms. The proposed U-net algorithm can segment extraocular muscles on coronal slices of 32 test samples with an average dice score of 0.92. The thickness and area measurements from predicted segmentations had a mean absolute error (MAE) of 0.35 mm and 3.87 mm2, respectively, with a corresponding mean absolute percentage error (MAPE) of 7 and 9%, respectively. On qualitative analysis of 32 test samples, 30 predicted segmentations from the U-net algorithm were accepted while 2 were rejected. Based on the results from quantitative and qualitative evaluation, this study demonstrates that CNN-based deep learning algorithms are effective at segmenting extraocular muscles and measuring muscles sizes.

Computed Tomography Imaging Artifacts in the Head and Neck Region: Pitfalls and Solutions.

Computed tomography (CT) artifacts are aberrations that usually degrade the image quality of CT images, but occasionally provide insights regarding actual imaging findings. The presence of artifacts can be attributed to various sources, including patient, scanner, and postprocessing factors. Artifacts can lead to diagnostic errors by obscuring findings or by being misinterpreted as actual lesions. This article reviews various types of CT artifacts that can be encountered in the head and neck region and explain how these artifacts may be mitigated. While we cannot fully eliminate the occurrence of CT artifacts, building an awareness of their cause provides reading physicians the tools to detect and read through their presence. Further, this knowledge may be applied to contribute to protocol adjustments to improve a site's overall imaging practice.

MR Imaging Artifacts in the Head and Neck Region: Pitfalls and Solutions.

MR Imaging artifacts are features appearing in MR images that are not present in the original anatomy. MR imaging artifacts can be patient-related, hardware-related, or signal-processing-related and affect diagnostic quality or mimic pathology. It is necessary to take MR imaging artifacts into consideration when interpreting images. A basic knowledge of MR imaging physics and the potential origin of MR imaging artifacts can help to find solutions to eliminate or reduce the influence of artifacts on image quality by adjusting acquisition parameters appropriately for a better diagnosis.

Pearls and Pitfalls of 18FDG-PET Head and Neck Imaging.

18FDG-PET plays an important role in cancer imaging. However, there are certain challenges with interpreting head and neck 18FDG-PET. In this article, examples of technical issues that can undermine the interpretation of the scans, normal physiologic activity that can mimic lesions or obscure lesions, and causes of false positives and false negatives on posttreatment cancer imaging are discussed. In addition, suggestions for addressing potential pitfalls on head and neck 18FDG-PET are highlighted.

Postsurgical and Postradiation Findings in the Head and Neck Imaging.

Surgical procedures and radiation therapy can have recognizable features on diagnostic imaging that should be recognized by the radiologist. Although it is a good practice to reference the surgical and clinical notes regarding any procedures that may have been performed in the head and neck, this information is not always available. Selected examples of posttreatment findings and potential mimics are described and depicted in the following sections.

Implants and Foreign Bodies on Head and Neck Imaging.

A wide variety of foreign bodies can be encountered on head and neck imaging. These foreign bodies might include comestible foreign bodies, retained foreign bodies from trauma, and surgically implanted devices. The imaging features of these items are reviewed in this article.

Normal Anatomic Structures, Variants, and Mimics of the Temporal Bone.

Various anatomic structures and variants in the temporal bone are potential radiological mimics and surgical hazards. The imaging features of normal variants and lesions with similar imaging appearance are presented in this article. Throughout the article, salient features that can help elucidate the distinguishing features between mimics and imaging pitfalls are presented.

Development and Validation of a Decision Analytical Model for Posttreatment Surveillance for Patients With Oropharyngeal Carcinoma.

Importance: Clinical practice regarding posttreatment radiologic surveillance for patients with oropharyngeal carcinoma (OPC) is neither adapted to individual patient risk nor fully evidence based. Objectives: To construct a microsimulation model for posttreatment OPC progression and use it to optimize surveillance strategies while accounting for both tumor stage and human papillomavirus (HPV) status. Design, Setting, and Participants: In this decision analytical modeling study, a Markov model of 3-year posttreatment patient trajectories was created. The training data source was the American College of Surgeon's National Cancer Database from 2010 to 2015. The external validation data set was the 2016 International Collaboration on Oropharyngeal Cancer Network for Staging (ICON-S) study. Training data comprised 2159 patients with OPC treated with primary radiotherapy who had known HPV status and disease staging information. Patients with American Joint Committee on Cancer, 7th edition stage III to IVB disease and those with clinical metastases during the time of primary treatment were included. Data were analyzed from August 1 to October 31, 2020. Main Outcomes and Measures: Main outcomes included disease stage and HPV status, specific disease transition probabilities, and latency of surveillance regimens, defined as time between recurrence incidence and disease discovery. Results: Training data consisted of 2159 total patients (1708 men [79.1%]; median age, 59.6 years [range, 40-90 years]; 401 with stage III disease, 1415 with stage IVA disease, and 343 with stage IVB disease). Cohorts predominantly had HPV-negative disease (1606 [74.4%]). With model-optimized regimens, recurrent disease was discovered a mean of 0.6 months (95% CI, 0.5-0.8 months) earlier than with a standard surveillance regimen based on current clinical guidelines. Recurrent disease was discovered using the optimized regimens without significant reduction in sensitivity. Compared with strategies based on reimbursement guidelines, the model-optimized regimens found disease a mean of 1.8 months (95% CI, 1.3-2.3 months) earlier. Conclusions and Relevance: Optimized, risk-stratified surveillance regimens consistently outperformed nonoptimized strategies. These gains were obtained without requiring any additional imaging studies. This approach to risk-stratified surveillance optimization is generalizable to a broad range of tumor types and risk factors.