Two-color fluorescence-guided surgery for head and neck cancer resections.

Significance: Head and neck squamous cell carcinoma (HNSCC) has the sixth highest incidence worldwide, with > 650,000 cases annually. Surgery is the primary treatment option for HNSCC, during which surgeons balance two main goals: (1) complete cancer resection and (2) preservation of normal tissues to ensure post-surgical quality of life. Unfortunately, these goals are not synergistic, where complete cancer resection is often limited by efforts to preserve normal tissues, particularly nerves, and reduce life-altering comorbidities. Aim: Currently, no clinically validated technology exists to enhance intraoperative cancer and nerve recognition. Fluorescence-guided surgery (FGS) has successfully integrated into clinical medicine, providing surgeons with real-time visualization of important tissues and complex anatomy, where FGS imaging systems operate almost exclusively in the near-infrared (NIR, 650 to 900 nm). Notably, this spectral range permits the detection of two NIR imaging channels for spectrally distinct detection. Approach: Herein, we evaluated the utility of spectrally distinct NIR nerve- and tumor-specific fluorophores for two-color FGS to guide HNSCC surgery. Using a human HNSCC xenograft murine model, we demonstrated that facial nerves and tumors could be readily differentiated using these nerve- and tumor-specific NIR fluorophores. Results: The selected nerve-specific fluorophore showed no significant difference in nerve specificity and off-target tissue fluorescence in the presence of xenograft head and neck tumors. Co-administration of two NIR fluorophores demonstrated successful tissue-specific labeling of nerves and tumors in spectrally distinct NIR imaging channels. Conclusions: We demonstrate a comprehensive FGS tool for cancer resection and nerve sparing during HNSCC procedures for future clinical translation.

Tumor Hypoxia on 18F-fluoromisonidazole Positron Emission Tomography and Distant Metastasis From Head and Neck Squamous Cell Carcinoma.

Importance: Given high rates of locoregional control after definitive management of head and neck squamous cell carcinoma (HNSCC), better methods are needed to project distant metastasis (DM) risk. Tumor hypoxia on 18F-fluoromisonidazole (FMISO) positron emission tomography (PET) is associated with locoregional failure, but data demonstrating an association with DM are limited. Objective: To determine whether tumor hypoxia on FMISO PET is associated with DM risk after chemoradiotherapy (CRT) for HNSCC. Design, Setting, and Participants: This cohort study assessed patients with HNSCC enrolled in 2 prospective clinical trials at a single academic referral center from 2004 to 2021 in which participants received FMISO PET before and during CRT. Data analysis occurred from May 2023 to May 2024. Exposures: FMISO PET scans before and 1 to 2 weeks after starting CRT were evaluated for tumor hypoxia by nuclear medicine physicians. Main Outcomes and Measures: The primary outcome was DM, defined as biopsy-proven HNSCC outside the primary site and regional lymph nodes. Time to DM was modeled with competing risk regression, with death as a competing risk. Overall survival (OS) was assessed secondarily and modeled with Cox regression. Results: Among 281 patients (median [range] age at CRT, 58.7 [25.5-85.6] years; 251 male [89.3%]) included in this study, 242 (86.1%) had oropharyngeal primary cancer, and 266 (94.7%) had human papillomavirus-positive disease. Of all patients, 217 (77.2%) had T stage 1 or 2, and 231 patients (82.2%) had N stage 2b or less. De-escalated 30 Gy CRT was delivered to 144 patients (51.2%), and the remainder received standard 70 Gy CRT. On FMISO PET examination, 73 patients (26.0%) had hypoxia-negative disease before CRT, 138 patients (49.1%) had hypoxia-positive disease before CRT and then hypoxia-negative disease during CRT, and 70 patients (24.9%) persistently had hypoxia-positive disease before and during CRT. At a median (IQR) 58 (46-91) months of follow-up, 12 DM events and 22 deaths were observed. Persistent intratreatment hypoxia was associated with increased DM risk (hazard ratio, 3.51; 95% CI, 1.05-11.79; P = .04) and worse OS (hazard ratio, 2.66; 95% CI, 1.14-6.19; P = .02). No patients with hypoxia-negative disease before CRT experienced DM. Conclusions and Relevance: In this cohort study using pooled analysis of prospective nonrandomized clinical trials incorporating FMISO PET in the definitive management of HNSCC, persistent intratreatment hypoxia was associated with increased risk of DM and worse OS. Conversely, all patients with hypoxia-negative disease before treatment remained free of DM. These findings suggest that pretreatment and intratreatment FMISO PET results may serve as biomarkers for DM risk and aid in identifying candidates for escalated therapeutic strategies.

Diagnostic Accuracy of [18F]FDG PET/MRI in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Metaanalysis.

This study evaluates the diagnostic utility of PET/MRI for primary, locoregional, and nodal head and neck squamous cell carcinoma (HNSCC) through systematic review and metaanalysis. Methods: A systematic search was conducted using PubMed and Scopus to identify studies on the diagnostic accuracy of PET/MRI for HNSCC. The search included specific terms and excluded nonhybrid PET/MRI studies, and those with a sample size of fewer than 10 patients were excluded. Results: In total, 15 studies encompassing 638 patients were found addressing the diagnostic test accuracy for PET/MRI within the chosen subject domain. Squamous cell carcinoma of the nasopharynx was the most observed HNSCC subtype (n = 198). The metaanalysis included 12 studies, with pooled sensitivity and specificity values of 93% and 95% per patient for primary disease evaluation, 93% and 96% for locoregional evaluation, and 89% and 98% per lesion for nodal disease detection, respectively. An examination of a subset of studies comparing PET/MRI against PET/CT or MRI alone for evaluating nodal and locoregional HNSCC found that PET/MRI may offer slightly higher accuracy than other modalities. However, this difference was not statistically significant. Conclusion: PET/MRI has excellent potential for identifying primary, locoregional, and nodal HNSCC.

Impact of kV-cone beam computed tomography dose on DNA repair mechanisms: A pilot study.

PURPOSE: In head and neck squamous cell carcinoma (HNSCC), early complications of the radiotherapy (RT) are observed from the beginning of the treatment to a few months after its end. During external radiotherapy treatment, several patient-dependent parameters can cause a modification of the dose distribution compared to the planned distribution due to variation in patient positioning, anatomy, or intra-fractional movements for example. To verify these parameters during treatment sessions, one of the most commonly used solutions is the cone-beam computed tomography (CBCT). Nowadays, the use of CBCT may constitutes a significant part of the total dose at the end of treatment (up to 10 cGy per session) and more often the volume irradiated by imaging is larger than the one irradiated by the treatment, leading to unintentional irradiation of nearby organs. In this study, we asked whether the imaging low dose added to a following fraction dose (2Gy) may affect the biological response in terms of DNA repair. MATERIAL AND METHODS: Using an IVInomad dosimeter and scintillating fiber probes specially designed for this exploratory study, we exposed fibroblasts cells from head and neck cancer (HNC) patients to a CBCT dose followed by a radiotherapy fraction dose. DNA double strand breaks and DNA repair were assessed by immunofluorescence using the biomarkers gamma H2AX (γH2AX) and pATM. RESULTS: The median dose of CBCT was measured between 17 to 21 mGy per session. The kinetics of both biomarkers were found to be strongly dependent on the individual factor in radiosensitive patients. For HNC patients, a prior CBCT dose applied few minutes before the 2Gy dose may have a sublinear effect on the DNA repair mechanisms and potentially on observed health tissue toxicity. CONCLUSION: The preliminary results obtained highlight the importance of individual and tissue factors for recognizing and repairing DSB during a treatment by radiotherapy using CBCT.

Tumour Marker Expression in Head and Neck Malignancies to Identify Potential Targets for Intraoperative Molecular Near-Infrared Imaging.

BACKGROUND: Oral and laryngeal squamous cell carcinoma (OSCC and LSCC) and papillary thyroid carcinoma (PTC) are common head and neck cancers (HNCs) typically treated surgically. Challenges in tumour delineation often lead to inadequate resection margins in OSCC and LSCC, and missed multifocality in PTC. Fluorescence imaging (FLI) using near-infrared tumour-targeting tracers may improve intraoperative identification of malignancy, facilitating precise excision. This study evaluates six potential FLI targets in OSCC, LSCC and PTC. MATERIALS AND METHODS: Immunohistochemical staining was performed on OSCC (n = 20), LSCC (n = 10) and PTC (n = 10), assessing CEA, c-Met, EpCAM, EGFR, integrin αvß6 and VEGF-α. Expression was scored (0-12) using the total immunostaining score (TIS) system, and categorized into absent (TIS 0), low (TIS 1-5), moderate (TIS 6-8) or high (TIS 9-12). RESULTS: Integrin αvß6 showed significant overexpression in OSCC (TIS: 12; p < 0.001) and LSCC (TIS: 8; p = 0.002), with 80% of OSCC and 90% of LSCC exhibiting moderate-high expression. Similarly, EGFR expression was moderate-high in most OSCC (87.5%; TIS: 8) and universally high in LSCC (100%; TIS: 12). In PTC, EGFR and VEGF-α expressions were low-moderate, but significantly higher than in healthy tissue (TIS: 6; p < 0.006). CONCLUSION: This study highlights integrin αvß6 and EGFR as viable FLI targets in OSCC and LSCC, especially integrin αvß6 for tumour margin delineation. In PTC, despite lower expressions, the significant overexpression of VEGF-α, c-MET, and EGFR suggests their potential as FLI targets. Our findings support the development of tumour-targeted FLI tracers to improve surgical precision in HNC.

A novel nomogram for predicting overall survival in patients with tongue squamous cell carcinoma using clinical features and MRI radiomics data: a pilot study.

OBJECTIVE: Tongue squamous cell carcinoma (TSCC) accounts for 43.4% of oral cancers in China and has a poor prognosis. This study aimed to explore whether radiomics features extracted from preoperative magnetic resonance imaging (MRI) could predict overall survival (OS) in patients with TSCC. METHODS: The clinical imaging data of 232 patients with pathologically confirmed TSCC at Xiangyang No. 1 People's Hospital were retrospectively analyzed from February 2010 to October 2022. Based on 2-10 years of follow-up, patients were categorized into two groups: control (healthy survival, n = 148) and research (adverse events: recurrence or metastasis-related death, n = 84). A training and a test set were established using a 7:3 ratio and a time node. Radiomics features were extracted from axial T2-weighted imaging, contrast-enhanced T1-weighted imaging, and diffusion-weighted imaging (DWI) sequences. The corresponding radiomics scores were generated using the least absolute shrinkage and selection operator algorithm. Kaplan-Meier and multivariate Cox regression analyses were used to screen for independent factors affecting adverse events in patients with TSCC using clinical and pathological results. A novel nomogram was established to predict the probability of adverse events and OS in patients with TSCC. RESULTS: The incidence of adverse events within 2-10 years after surgery was 36.21%. Kaplan-Meier analysis revealed that hot pot consumption, betel nut chewing, platelet-lymphocyte ratio, drug use, neutrophil-lymphocyte ratio, Radscore, and other factors impacted TSCC survival. Multivariate Cox regression analysis revealed that the clinical stage (P < 0.001), hot pot consumption (P < 0.001), Radscore 1 (P = 0.01), and Radscore 2 (P < 0.001) were independent factors affecting TSCC-OS. The same result was validated by the XGBoost algorithm. The nomogram based on the aforementioned factors exhibited good discrimination (C-index 0.86/0.81) and calibration (P > 0.05) in the training and test sets, accurately predicting the risk of adverse events and survival. CONCLUSION: The nomogram constructed using clinical data and MRI radiomics parameters may accurately predict TSCC-OS noninvasively, thereby assisting clinicians in promptly modifying treatment strategies to improve patient prognosis.

Prognostic Value of the 18F-FDG PET/CT and Haematological Parameters in Head and Neck Cancer.

INTRODUCTION: Fluorine 18-fluoro-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) is commonly used for the staging of head and neck cancer. This study aimed to evaluate the correlation between 18F-FDG PET/CT, haematological parameters and prognosis in patients with advanced head and neck cancer. METHODS: This was a single-institutional retrospective study of 83 patients with advanced head and neck squamous cell carcinoma (HNSCC) who underwent 18F-FDG PET/CT imaging before initial treatment between 2014 and 2018. 18F-FDG PET/CT after treatment was performed in 57 patients. The prognostic parameters of the pre- and post-treatment maximum standardised uptake value (SUVmax), metabolic tumour volume (MTV), total lesion glycolysis (TLG) of primary tumours and haematological parameters were analysed to evaluate the association between overall survival (OS) and progression-free survival (PFS). RESULTS: Pre-MTV, pre-TLG and post-SUVmax were significantly associated with poor OS and PFS (p < 0.05). Haematological parameters, including pretreatment neutrophil/lymphocyte ratio and C-reactive protein/albumin ratio, were associated with 18F-FDG PET/CT parameters. In multivariate analysis, post-SUVmax was an independent prognostic factor for OS and PFS. CONCLUSION: A correlation between PET/CT metabolic and haematological parameters was observed. The volume and intensity of 18F-FDG uptake region, in addition to haematological parameters, are feasible markers for predicting the progression of HNSCC in daily practice. Further, post-SUVmax could be an independent parameter for predicting poor survival.

The Neck-Persistency-Net: a three-dimensional, convolution, deep neural network aids in distinguishing vital from non-vital persistent cervical lymph nodes in advanced head and neck squamous cell carcinoma after primary concurrent radiochemotherapy.

PURPOSE: To evaluate the diagnostic performance (DP) of the high-resolution contrast computed tomography (HR-contrast-CT) based Neck-Persistency-Net in distinguishing vital from non-vital persistent cervical lymph nodes (pcLNs) in patients with advanced head and neck squamous cell carcinoma (HNSCC) following primary concurrent chemoradiotherapy (CRT) with [18F]-fluorodeoxyglucose positron emission tomography and high-resolution contrast-enhanced computed tomography ([18F]FDG-PET-CT). Furthermore, the Neck-Persistency-Net's potential to justify omitting post-CRT neck dissection (ND) without risking treatment delays or preventing unnecessary surgery was explored. METHODS: All HNSCC patients undergoing primary CRT followed by post-CRT-ND for pcLNs recorded in the institutional HNSCC registry were analyzed. The Neck-Persistency-Net DP was explored for three scenarios: balanced performance (BalPerf), optimized sensitivity (OptSens), and optimized specificity (OptSpec). Histopathology of post-CRT-ND served as a reference. RESULTS: Among 68 included patients, 11 were female and 32 had vital pcLNs. The Neck-Persistency-Net demonstrated good DP with an area under the curve of 0.82. For BalPerf, both sensitivity and specificity were 78%; for OptSens (90%), specificity was 62%; for OptSpec (95%), sensitivity was 54%. Limiting post-CRT-ND to negative results would have delayed treatment in 27%, 40%, and 7% for BalPerf, OptSens and OptSpec, respectively, versus 23% for [18F]FDG-PET-CT. Conversely, restricting post-CRT-ND to positive results would have prevented unnecessary post-CRT-ND in 78%, 60%, and 95% for BalPerf, OptSens and OptSpec, respectively, versus 55% for [18F]FDG-PET-CT. CONCLUSION: The DP of the Neck-Persistency-Net was comparable to [18F]-FDG-PET-CT. Depending on the chosen decision boundary, the potential to justify the omission of post-CRT-ND without risking treatment delays in false negative findings or reliably prevent unnecessary surgery in false positive findings outperforms the [18F]-FDG-PET-CT.

Radiomics-based prediction of recurrence for head and neck cancer patients using data imbalanced correction.

OBJECTIVES: To propose a radiomics-based prediction model for head and neck squamous cell carcinoma (HSNCC) recurrence after radiation therapy using a novel data imbalance correction method known as Gaussian noise upsampling (GNUS). MATERIALS AND METHODS: The dataset includes 97 HNSCC patients treated with definitive radiotherapy alone or concurrent chemoradiotherapy at two institutions. We performed radiomics analysis using nine segmentations created on pretreatment positron emission tomography and computed tomography images. Feature selection was performed by the least absolute shrinkage and selection operator analysis via five-fold cross-validation. The proposed GNUS was compared with seven conventional data-imbalance correction methods. Classification models of HNSCC recurrence were constructed on oversampled features using the machine learning algorithms of linear regression. Their predictive performance was evaluated based on accuracy, sensitivity, specificity, and the area under the curve (AUC) of the receiver operating performance characteristic curve via five-fold cross-validation using the same combinations as for feature selection. RESULT: The prediction model without data imbalance correction shows sensitivity, specificity, accuracy, and AUC values of 83 %, 96 %, 92 %, and 0.96, respectively. The conventional model with the best performance is the random over-sampler model, which shows sensitivity, specificity, accuracy, and AUC values of 93 %, 91 %, 92 %, 0.97, respectively, whereas the GNUS model shows values of 93 %, 94 %, 94 %, 0.98, respectively. CONCLUSION: Oversampling methods can reduce sensitivity and specificity bias. The proposed GNUS can improve accuracy as well as reduce sensitivity and specificity bias.

Integrating lipid metabolite analysis with MRI-based transformer and radiomics for early and late stage prediction of oral squamous cell carcinoma.

BACKGROUND: Oral Squamous Cell Carcinoma (OSCC) presents significant diagnostic challenges in its early and late stages. This study aims to utilize preoperative MRI and biochemical indicators of OSCC patients to predict the stage of tumors. METHODS: This study involved 198 patients from two medical centers. A detailed analysis of contrast-enhanced T1-weighted (ceT1W) and T2-weighted (T2W) MRI were conducted, integrating these with biochemical indicators for a comprehensive evaluation. Initially, 42 clinical biochemical indicators were selected for consideration. Through univariate analysis and multivariate analysis, only those indicators with p-values less than 0.05 were retained for model development. To extract imaging features, machine learning algorithms in conjunction with Vision Transformer (ViT) techniques were utilized. These features were integrated with biochemical indicators for predictive modeling. The performance of model was evaluated using the Receiver Operating Characteristic (ROC) curve. RESULTS: After rigorously screening biochemical indicators, four key markers were selected for the model: cholesterol, triglyceride, very low-density lipoprotein cholesterol and chloride. The model, developed using radiomics and deep learning for feature extraction from ceT1W and T2W images, showed a lower Area Under the Curve (AUC) of 0.85 in the validation cohort when using these imaging modalities alone. However, integrating these biochemical indicators improved the model's performance, increasing the validation cohort AUC to 0.87. CONCLUSION: In this study, the performance of the model significantly improved following multimodal fusion, outperforming the single-modality approach. CLINICAL RELEVANCE STATEMENT: This integration of radiomics, ViT models, and lipid metabolite analysis, presents a promising non-invasive technique for predicting the staging of OSCC.

The Importance of the Time Interval Between Preoperative 18F-FDG PET/CT Imaging and Neck Dissection for the Detection of Nodal Metastases in Patients with Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Detection of nodal metastasis is critical for the treatment and prognosis of head and neck cancer (HNC). Positron emission tomography/computed tomography (PET/CT) is increasingly being used to detect cervical lymph node involvement. AIM: The purposes of this study were to (1) investigate the diagnostic accuracy of PET/CT for the detection of neck metastasis in patients with HNC and (2) determine the effect of the time interval between surgery and PET/CT. METHODS: Fifty patients with head and neck squamous cell carcinoma who underwent PET/CT before surgery were included in this study. Preoperative PET/CT images that determined lymph node metastasis were compared with the histopathological analysis of neck dissection samples. Neck dissections were divided into three groups according to the time interval between surgery and PET/CT (0-2 weeks, >2-4 weeks, and >4 weeks). The concordance between PET/CT and histopathology was measured using the neck sides at different time intervals. The specificity, sensitivity, accuracy, negative predictive value (NPV), and positive predictive value (PPV) of PET/CT in detecting metastatic lymph nodes in the neck were calculated. RESULTS: A total of 79 neck dissections were included in the study as 29 (58%) of the patients underwent bilateral neck dissection. The overall accuracy of PET/CT in detecting nodal metastasis was highest for the 0-2 weeks interval (95.6%). During this time interval, the sensitivity, specificity, NPV, and PPV of PET/CT were 100%, 90.9%, 100%, and 92.3%, respectively. CONCLUSIONS: Although PET/CT is an important and reliable diagnostic method for detecting nodal metastases in patients with HNC, its reliability decreases as the time between surgeries increases. The optimal interval was 2 weeks; however, up to 4 weeks was acceptable.

Diagnostic Performance of 18F-FDG PET/CT According to Delay After Treatment to Detect Subclinical Recurrence of Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) remains a malignancy with high rates of locoregional recurrence and poor prognosis for recurrent cases. Early detection of subclinical lesions is challenging but critical for effective patient management. Imaging surveillance after treatment, particularly 18F-FDG PET/CT, has shown promise in the diagnosis of HNSCC recurrence. The aim was to evaluate the diagnostic performance of 18F-FDG PET/CT according to delay after treatment in detecting subclinical recurrence (SCR) in HNSCC patients. Methods: In this retrospective study, all 18F-FDG PET/CT scans were performed at a single center. All adults with histologically proven HNSCC who were treated with curative intent between January 1, 2006, and December 31, 2021, were included. They had a normal clinical examination before each scan. Patients who underwent an intensive follow-up strategy after treatment had 18F-FDG PET/CT with an intravenous contrast agent at 3-6 mo and annually thereafter for 5 y. The primary endpoint was diagnostic performance (positive and negative predictive values, sensitivity, specificity, and accuracy). Results: In total, 2,566 18F-FDG PET/CT scans were performed among 852 patients, with an average of 3 scans per patient. The overall diagnostic performance measures were as follows: positive predictive value (88%), negative predictive value (98%), sensitivity (98%), specificity (89%), and accuracy (93%). There were no significant differences in diagnostic performance over time. The scans detected 126 cases of SCR (14.8%) and 118 cases of metachronous cancer (13.8%). The incidence of SCR decreased over time, with the highest detection rate in the first 2 y after treatment. Positive predictive value improved over time, reaching 90% for the digital Vision 600 system (third period) compared with 76% for the analog Gemini GXLi system (first period, P < 0.001). Multivariate analysis identified advanced stage, high body mass index, and initial PET/CT upstaging as predictive factors for detection of SCR. Conclusion: Our study demonstrates that 18F-FDG PET/CT has high diagnostic performance in detecting SCR during follow-up after treatment of HNSCC, especially in the first 2 y. Advanced tumor stage, initial PET/CT upstaging, and high body mass index were associated with a higher likelihood of SCR detection. The routine use of 18F-FDG PET/CT during follow-up seems justified for patients with HNSCC.

FGD-PET/CT three months after (chemo)radiotherapy for head and neck squamous cell carcinoma spares considerable number of patients from a salvage neck dissection.

PURPOSE: In the last decades FDG-PET/CT is increasingly used in combination with the standard diagnostic modalities (MRI + US-FNA) to identify residual neck disease (RND) after (chemo)radiotherapy for head-and-neck squamous cell carcinoma (HNSCC). The purpose of the current study is to identify the impact of increasing use of FDG-PET/CT on the accuracy of patient selection for salvage neck dissection (SND). MATERIALS AND METHODS: Between 2008 and 2022, 908 consecutive patients with node-positive HNSCC were treated with (chemo)radiotherapy in our institution. PRIMARY ENDPOINT: positive predictive value (PPV) of FDG-PET/CT for pathologic-confirmed RND (pRND) after SND, compared to the standard of care; MRI + US-FNA. Secondary endpoints: oncologic outcomes. RESULTS: Of the entire group, 130 patients (14 %) received SND. Of them only 53 patients (41 %) had pRND at the SND-specimens. The PPV of FDG-PET/CT for the detection of pRND was considerably better, compared to MRI + US-FNA; 89 % and 65 %, respectively. If FDG-PET/CT showed metabolic CR, these patients did not undergo SND. The NPV was 97.5 %, as only 2.5 % of these patients developed delayed regional failure. FDG-PET/CT considerably improved the accuracy of patient selection for SND, as significantly more patients treated in the second period, compared to first period of the study (n = 454 each) still had vital tumor at SND-specimen (53 % and 31 %, p = 0.008). Regional recurrence free-survival, DFS, OS and HNSCC-death were significantly worse in patients with pRND (p < 0.05) CONCLUSIONS: Incorporating FDG-PET/CT into the diagnostic pathway for the response evaluation after (chemo)radiotherapy significantly improved the accuracy of patient selection for SND and spared considerable number of patients (>20 %) from unnecessary SND. For patients with metabolic CR, SND can safely be omitted while for patients with no metabolic CR, SND is strongly advocated.

The Prognostic Significance of Tumor SUVmax Value in Pre- and Post-Chemoradiotherapy 18F-FDG PET/CT Imaging in Patients with Localized and Advanced Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Some parameters of 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) can predict tumor chemosensitivity and survival in patients with head and neck squamous cell carcinoma (HNSCC). AIM: The aim of the study was to investigate the prognostic value of pre- and post-treatment maximum standardized uptake values (SUVmax) in 18F-FDG PET/CT imaging for predicting mortality in patients with HNSCC, as well as its prognostic value in terms of disease progression, overall survival (OS), and progression-free survival (PFS). METHODS: This retrospective study included 37 patients with a histopathological diagnosis of HNSCCs between 2015 and 2018. In patients with HNSCC, the first 18F-FDG PET/CT imaging was performed for pre-treatment staging, and the second imaging was performed to evaluate post-treatment response. In these imaging studies, SUVmax values of the primary tumor before and after treatment were determined. After the second imaging, patients were re-evaluated and followed up. ROC analysis was used to determine the predictive value of 18F-FDG PET/CT SUVmax parameters in terms of death and progression, and Cox regression analysis was used to investigate the prognostic value in terms of OS and PFS. RESULTS: Cut-off value 15 for SUVmax1 (pre-treatment) had a significant predictive value for mortality (P = 0.02). Cut-off value 3.1 for SUVmax2 (post-treatment) had a significant predictive value for progression (P = 0.024). In univariate analysis, both SUVmax1 and SUVmax2 values were significant prognostic factors for OS (P = 0.047, P = 0.004). However, for PFS, only the SUVmax2 value was a significant prognostic factor (P = 0.001). CONCLUSION: SUVmax1 value of the primary tumor at diagnosis in HNSCC patients has a predictive value for mortality and a prognostic value for OS. However, the SUVmax2 value in the primary tumor after treatment is a predictive factor for progression and a prognostic factor for both OS and PFS.

Explainable prediction model for the human papillomavirus status in patients with oropharyngeal squamous cell carcinoma using CNN on CT images.

Several studies have emphasised how positive and negative human papillomavirus (HPV+ and HPV-, respectively) oropharyngeal squamous cell carcinoma (OPSCC) has distinct molecular profiles, tumor characteristics, and disease outcomes. Different radiomics-based prediction models have been proposed, by also using innovative techniques such as Convolutional Neural Networks (CNNs). Although some of these models reached encouraging predictive performances, there evidence explaining the role of radiomic features in achieving a specific outcome is scarce. In this paper, we propose some preliminary results related to an explainable CNN-based model to predict HPV status in OPSCC patients. We extracted the Gross Tumor Volume (GTV) of pre-treatment CT images related to 499 patients (356 HPV+ and 143 HPV-) included into the OPC-Radiomics public dataset to train an end-to-end Inception-V3 CNN architecture. We also collected a multicentric dataset consisting of 92 patients (43 HPV+ , 49 HPV-), which was employed as an independent test set. Finally, we applied Gradient-weighted Class Activation Mapping (Grad-CAM) technique to highlight the most informative areas with respect to the predicted outcome. The proposed model reached an AUC value of 73.50% on the independent test. As a result of the Grad-CAM algorithm, the most informative areas related to the correctly classified HPV+ patients were located into the intratumoral area. Conversely, the most important areas referred to the tumor edges. Finally, since the proposed model provided additional information with respect to the accuracy of the classification given by the visualization of the areas of greatest interest for predictive purposes for each case examined, it could contribute to increase confidence in using computer-based predictive models in the actual clinical practice.

First-in-Human Hyperpolarized MRI for Tumor Metabolism in HNSCC.

This case report describes the use of hyperpolarized magnetic resonance imaging (MRI) in a patient with head and neck squamous cell carcinoma (HNSCC) to demonstrate its translational viability.

Durable radiologic and molecular complete response following nivolumab in an HNSCC patient with UV signature and HIV.

Cancer patients living with HIV (CPLWH) may experience increased mortality risk. Furthermore, they have been historically excluded from clinical trials due to safety concerns. Our patient with squamous cell carcinoma of the lower lip received radiotherapy and platinum-based chemotherapy but declined by multiple centers due to his accidental HIV status. Genomic profiling revealed CDKN2A/B, PBRM1, TP53, and TERT alterations corresponding to UV signature, and high tumor mutational burden with positive PD-L1 staining. Accordingly, we report a durable radiologic and molecular complete response upon nivolumab plus IVC and antiretroviral therapy (ART). We demonstrated the safety and efficacy of ICIs, and feasibility of managing adverse events caused by antitumor, antiviral, and integrative therapies.

Cyto R-CNN and CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images.

BACKGROUND AND OBJECTIVE: Cell segmentation in bright-field histological slides is a crucial topic in medical image analysis. Having access to accurate segmentation allows researchers to examine the relationship between cellular morphology and clinical observations. Unfortunately, most segmentation methods known today are limited to nuclei and cannot segment the cytoplasm. METHODS: We present a new network architecture Cyto R-CNN that is able to accurately segment whole cells (with both the nucleus and the cytoplasm) in bright-field images. We also present a new dataset CytoNuke, consisting of multiple thousand manual annotations of head and neck squamous cell carcinoma cells. Utilizing this dataset, we compared the performance of Cyto R-CNN to other popular cell segmentation algorithms, including QuPath's built-in algorithm, StarDist, Cellpose and a multi-scale Attention Deeplabv3+. To evaluate segmentation performance, we calculated AP50, AP75 and measured 17 morphological and staining-related features for all detected cells. We compared these measurements to the gold standard of manual segmentation using the Kolmogorov-Smirnov test. RESULTS: Cyto R-CNN achieved an AP50 of 58.65% and an AP75 of 11.56% in whole-cell segmentation, outperforming all other methods (QuPath 19.46/0.91%; StarDist 45.33/2.32%; Cellpose 31.85/5.61%, Deeplabv3+ 3.97/1.01%). Cell features derived from Cyto R-CNN showed the best agreement to the gold standard (D¯=0.15) outperforming QuPath (D¯=0.22), StarDist (D¯=0.25), Cellpose (D¯=0.23) and Deeplabv3+ (D¯=0.33). CONCLUSION: Our newly proposed Cyto R-CNN architecture outperforms current algorithms in whole-cell segmentation while providing more reliable cell measurements than any other model. This could improve digital pathology workflows, potentially leading to improved diagnosis. Moreover, our published dataset can be used to develop further models in the future.

MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to help surgeons make precise treatment decisions. AIM: To construct and evaluate a preoperative diagnostic method to predict OCLNM in early-stage oral and oropharyngeal squamous cell carcinoma (OC and OP SCC) based on deep learning features (DLFs) and radiomics features. METHODS: A total of 319 patients diagnosed with early-stage OC or OP SCC were retrospectively enrolled and divided into training, test and external validation sets. Traditional radiomics features and DLFs were extracted from their MRI images. The least absolute shrinkage and selection operator (LASSO) analysis was employed to identify the most valuable features. Prediction models for OCLNM were developed using radiomics features and DLFs. The effectiveness of the models and their clinical applicability were evaluated using the area under the curve (AUC), decision curve analysis (DCA), and survival analysis. RESULTS: Seventeen prediction models were constructed. The Resnet50 deep learning (DL) model based on the combination of radiomics and DL features achieves the optimal performance, with AUC values of 0.928 (95% CI: 0.881-0.975), 0.878 (95% CI: 0.766-0.990), 0.796 (95% CI: 0.666-0.927), and 0.834 (95% CI: 0.721-0.947) in the training, test, external validation set1, and external validation set2, respectively. Moreover, the Resnet50 model has great prediction value of prognosis in patients with early-stage OC and OP SCC. CONCLUSION: The proposed MRI-based Resnet50 DL model demonstrated high capability in diagnosis of OCLNM and prognosis prediction in the early-stage OC and OP SCC. The Resnet50 model could help refine the clinical diagnosis and treatment of the early-stage OC and OP SCC.

Dataset of weekly intra-treatment diffusion weighted imaging in head and neck cancer patients treated with MR-Linac.

Radiation therapy (RT) is a crucial treatment for head and neck squamous cell carcinoma (HNSCC); however, it can have adverse effects on patients' long-term function and quality of life. Biomarkers that can predict tumor response to RT are being explored to personalize treatment and improve outcomes. While tissue and blood biomarkers have limitations, imaging biomarkers derived from magnetic resonance imaging (MRI) offer detailed information. The integration of MRI and a linear accelerator in the MR-Linac system allows for MR-guided radiation therapy (MRgRT), offering precise visualization and treatment delivery. This data descriptor offers a valuable repository for weekly intra-treatment diffusion-weighted imaging (DWI) data obtained from head and neck cancer patients. By analyzing the sequential DWI changes and their correlation with treatment response, as well as oncological and survival outcomes, the study provides valuable insights into the clinical implications of DWI in HNSCC.