Chronic rhinosinusitis (CRS) is a common and persistent sinus inflammation that affects 5%-12% of the general population. It substantially reduces quality of life, yet its severity is often challenging to assess objectively. The Lund-Mackay score (LMS) rates sinus opacification but is typically assessed manually and subjectively. We introduce Paranasal Segmentation for Imaging-based Disease Evaluation (PARASIDE), an automatic tool for segmenting air and soft tissue volumes of the structures of the sinus maxillaris, frontalis, sphenoidalis, and ethmoidalis in T1-weighted magnetic resonance imaging. Utilizing that segmentation, we quantify feature relations such as volume, thickness, and intensity relations which were previously observed only manually and subjectively. Using these features, we regress the Total Lund-Mackay Score (TLMS) of each subject. We compare our approach against established baselines: the Quantitative Opacification Score (QOS) and the Quantitative Lund-Mackay Score (QLMS). PARASIDE achieves a mean-squared error (MSE) of 2.444 and mean absolute error (MAE) of 1.181 for TLMS prediction, outperforming the QOS/QLMS baseline (MSE = 3.784, MAE = 1.445). The segmentation achieves a mean Dice similarity coefficient of 0.882 ± 0.138 and an average symmetric surface distance (ASSD) of 0.311 ± 0.354 mm across all structures. PARASIDE enables the first automated whole-paranasal sinus segmentation for T1-weighted MRI, extracting quantitative features that predict CRS severity more accurately than existing volumetric scoring methods. By integrating high-quality segmentation with fully automated TLMS estimation, our system offers a reproducible and objective assessment tool in clinical workflows, with the potential to reduce inter-rater variability, accelerate reporting, and support large-scale retrospective studies.

Background/Objectives: To evaluate whether automated three-dimensional volumetric body composition metrics from the Body and Organ Analysis (BOA) algorithm provide prognostic information beyond body mass index (BMI) for overall survival (OS) in surgically treated head and neck squamous cell carcinoma (HNSCC), and to compare cervical (C1–C7) measurements with thoracic and abdominal regional comparators. Methods: This single-center retrospective cohort study included 391 surgically treated HNSCC patients (2010–2019). Pretreatment CT scans were processed using the open-source BOA algorithm to obtain volumetric muscle, bone, and adipose measurements across cervical (C1–C7), thoracic, and abdominal regions. Composite indices—Sarcopenia Index (SI = Muscle/Bone) and Myosteatotic Fat Index (MFI = IMAT/TAT)—were derived; Cerv SI denotes the volumetric C1–C7 ratio. The predefined primary Cox model adjusted for age, sex, tumor site, UICC stage, treatment, HN-CCI, and secondary malignancy. Results: Of 391 patients (91% male, median follow-up 5.0 years, 141 deaths), BMI was not independently associated with OS (HR 0.88, p = 0.15). Cerv SI was associated with OS in the minimally adjusted model (HR 0.71, 95% CI 0.58–0.88, p = 0.002) and remained independent in the primary clinically adjusted model (HR 0.72, 95% CI 0.58–0.90, p = 0.004; C-index 0.67). When BMI and Cerv SI were entered together, Cerv SI remained independently associated (HR 0.72, p = 0.006) while BMI was null (HR 1.01, p = 0.95). Conclusions: BOA-derived cervical volumetric body composition is associated with overall survival beyond BMI and is obtainable from routine head and neck CT. Prospective validation and comparison with established two-dimensional C3/L3 methods are warranted before clinical use.

Background: Maxillary sinus puncture (MSP), once a cornerstone for diagnosing and treating acute rhinosinusitis (ARS), has declined with the rise in less invasive techniques. This study explores MSP trends, its association with age, and long-term effects on quality of life using data from the Study of Health in Pomerania (SHIP). Methods: Data from SHIP-START-2 (n = 2332), SHIP-START-3 (n = 1717), and SHIP-TREND-0 (n = 4420) cohorts were analyzed to assess MSP prevalence, demographic correlations, and quality- of-life impacts using SNOT-20-D, EQ-5D-3L, and SF-12. Results: MSP prevalence was higher in older SHIP-START cohorts (11.2% in START-2) compared to SHIP-TREND-0 (9.5%), reflecting its historical decline. The procedure was more frequently reported by participants aged > 60 years (e.g., 14.0% in START-2) than by younger groups (<40 years: 3.5% in START-2). MSP was associated with increased SNOT-20-D scores across cohorts (e.g., +0.28 in START-2, p < 0.001) and minor reductions in EQ-5D-3L and SF-12 mental health scores, indicating greater symptom burden but limited general health impact. The age- and time-related decline in MSP highlights its diminishing role in modern practice. Conclusions: While MSP offers diagnostic insights and serves as an indicator for ARS, its modest impact on long-term quality-of-life underscores the need for alternative, minimally invasive techniques for sinonasal conditions.

Manual sinus magnetic resonance imaging (MRI) annotations are valuable but difficult to scale. We evaluated PARASIDE, an nnU-Net-based framework for automated sinus compartment segmentation on T1-weighted MRI, against independent manual and radiological assessments from the Study of Health in Pomerania. We linked 12,867 sinus sides from 3,217 participants. Analyses defined before outcome modelling evaluated soft-tissue fraction for healthy versus abnormal sides, inferior soft-tissue centroid position for basal versus apical maxillary opacification, and total frontal volume for aplasia/hypoplasia. Soft-tissue fraction discriminated abnormal sides in frontal (area under the receiver operating characteristic curve [AUC] 0.850, 95% confidence interval [CI] 0.834–0.866) and maxillary sinuses (AUC 0.828, 95% CI 0.818–0.839). The topographic marker discriminated basal from apical opacification (AUC 0.746 left; 0.782 right). Total frontal volume discriminated historical aplasia/hypoplasia ratings (AUC 0.988); a previously established near-absence threshold was highly specific but insensitive. Historical maxillary volumetric masks showed strong overlap and volume association for total and aerated compartments, whereas frontal comparisons reflected a predefined caudal boundary. The historical polyposis rating category remained weakly separable, and surgery-related features corresponded more closely to visible postoperative morphology than to self-reported surgery. PARASIDE reproduced anatomically measurable MRI phenotypes, whereas morphology-specific constructs required dedicated reference standards.

Background/Objectives: To evaluate whether automated three-dimensional (3D) volumetric body composition metrics derived from the Body and Organ Analysis (BOA) algorithm provide prognostic information beyond body mass index (BMI) for overall survival (OS) in patients with surgically treated head and neck squamous cell carcinoma (HNSCC), and to compare cervical (C1–C7) measurements with thoracic and abdominal benchmarks. Methods: This single-center retrospective cohort study included 391 surgically treated HNSCC patients at Universitätsmedizin Greifswald (2010–2019). Patients with definitive (chemo)radiation (no surgery) or non-standard adjuvant chemotherapy alone (n=13) were excluded; thus, all included patients had primary surgical management. Tumor staging was retrieved from institutional records for all 391 patients. For patients with documented ongoing follow-up but without a specific last-contact date, survival status was verified by chart review where possible, and patients confirmed alive at the institutional database snapshot date were administratively censored on 28 January 2025. Pretreatment CT scans were processed using the open-source BOA algorithm (v0.1.3) to obtain volumetric tissue measurements of muscle, bone, and adipose compartments across abdominal, thoracic, and cervical (C1–C7) regions. Composite indices — Sarcopenia Index (SI = Muscle/Bone) and Myosteatotic Fat Index (MFI = IMAT/TAT) — were derived. Univariate and multivariate Cox proportional hazards models were used. The primary clinically adjusted model included cervical SI, age, sex, tumor site, UICC stage, treatment modality, the Head and Neck Charlson Comorbidity Index (HN-CCI), and secondary malignancy; a minimally adjusted model (HN-CCI and secondary malignancy) was retained as a supportive analysis. Leukocytes and postoperative CRP were examined in a sensitivity model. Reporting followed the STROBE checklist. Results: Of 391 evaluable cases (91% male, median follow-up 5.0 years, 141 deaths), BMI showed only a weak univariate association with overall survival (HR 0.84, p=0.052) and was not independently associated with OS after adjustment (multivariate HR 0.88, p=0.15). In contrast, in the minimally adjusted supportive model the cervical Sarcopenia Index (Cerv SI, Muscle/Bone) was associated with overall survival (HR 0.71, 95% CI 0.58–0.88, p=0.002); in the primary clinically adjusted model including age, sex, tumor site, UICC stage, treatment modality, HN-CCI, and secondary malignancy, cervical SI remained independently associated with OS (HR 0.75, 95% CI 0.61–0.92, p=0.007; n=254). Thoracic Myosteatotic Fat Index (Thor MFI) was associated with worse overall survival in the minimally adjusted supportive model (HR 1.35, p=0.002) and remained associated after extended oncologic adjustment (HR 1.26, p=0.013). Harrell's concordance index for overall survival prediction was 0.60 for cervical SI and 0.55 for BMI; the difference was modest. Inter-regional SI correlations were strong between abdomen and thorax (r=0.69) but only moderate for cervical–thoracic (r=0.42). An in-sample comparison showed that a BOA-derived single-level C3 Sarcopenia Index was non-prognostic (C-index 0.52) and weakly correlated with the volumetric C1–C7 SI (r=0.04), suggesting that the volumetric and single-vertebra-level metrics derived from the BOA pipeline capture different information. In paired bootstrap comparisons, cervical SI showed a modest but significant C-index improvement over BMI (ΔC = +0.087, p = 0.038) but did not significantly outperform the BOA-derived C3 SI, ASA classification, or thoracic SI. Conclusions: BOA-derived volumetric body composition indices, particularly the cervical Sarcopenia Index, are associated with overall survival in surgically treated HNSCC patients and remain prognostic after adjustment for established oncologic confounders, whereas BMI is not. Cervical C1–C7 BOA analysis enables body composition assessment from routine head and neck CT and may provide an objective imaging-derived marker for future risk-stratification studies. Prospective validation and formal comparison with established C3/L3 methods are warranted before routine clinical use.

Manual sinus magnetic resonance imaging (MRI) annotations are valuable but difficult to scale. We evaluated PARASIDE, an nnU-Net-based framework for automated sinus compartment segmentation on T1-weighted MRI, against historical manual annotations and radiological assessments generated independently of PARASIDE within the same longitudinal Study of Health in Pomerania (SHIP) imaging population. We linked 12,867 sinus sides from 3217 participants. Primary construct–marker pairings were specified before endpoint-specific modelling. Soft-tissue fraction discriminated abnormal sides in frontal (AUC 0.850, 95% CI 0.832–0.868) and maxillary sinuses (AUC 0.828, 95% CI 0.816–0.841). The topographic marker showed moderate discrimination of basal from apical opacification (AUC 0.746 left; 0.782 right), while total frontal volume discriminated aplasia/hypoplasia ratings (AUC 0.988); the near-absence threshold remained highly specific but insensitive. Primary findings were robust to exclusion of 279 participants overlapping with the original PARASIDE development population. Historical maxillary volumetric masks showed strong agreement, whereas frontal agreement improved after accounting for the predefined inferior extent of the non-equivalent historical segmentation approach. Polyposis remained weakly separable. PARASIDE showed correspondence with distinct, anatomically measurable MRI phenotypes across complementary historical reference layers, while morphology-specific constructs required dedicated reference standards.