Search Results (955)

Background and Objectives: Breast cancer surgery is increasingly performed in older patients with multimorbidity, in whom cardiovascular disease and frailty may substantially modify perioperative risk, including vulnerability to heart failure decompensation and other major medical complications. However, most available studies report global perioperative complication rates and composite medical endpoints, with heart failure events only rarely captured as dedicated outcomes, and operative technique, cardiovascular comorbidity, and frailty are often treated as separate domains rather than components of an integrated risk framework. Materials and Methods: We conducted a systematized narrative review with a structured literature search in PubMed/MEDLINE, Scopus, and Web of Science from inception to 31 January 2026, including original studies of adult patients undergoing breast-conserving surgery, mastectomy, and/or reconstruction that reported early postoperative outcomes in relation to comorbidities, cardiovascular risk, or frailty. Eligibility assessment, data extraction, and qualitative synthesis followed key PRISMA 2020 principles, and findings were organized into three prespecified domains: surgical complexity, cardiovascular vulnerability (including patients with heart failure where reported), and frailty. Results: Nineteen studies (retrospective cohorts, registry-based analyses, and large database studies, primarily ACS NSQIP) met inclusion criteria, encompassing diverse breast surgery populations, including elderly, metastatic, and reconstructive cohorts. Across datasets, escalation from breast-conserving surgery to mastectomy and then to increasingly complex reconstruction was associated with a stepwise increase in perioperative complications, reoperations, bleeding, and, in selected series, catastrophic events. Preexisting cardiovascular disease and systemic vascular pathology significantly amplified postoperative morbidity even in procedures considered low or intermediate cardiac risk, with signals that patients with underlying heart failure carry particularly heightened vulnerability, although HF-specific events were infrequently reported as separate endpoints. Frailty, mainly assessed using modified frailty indices, consistently emerged as a strong, age-independent predictor of 30-day complications, mortality, and readmissions across surgical types, including both breast-conserving and reconstructive procedures. Conclusions: Early postoperative outcomes after breast cancer surgery are associated with the interaction between surgical complexity, cardiovascular comorbidity (with limited HF-specific reporting), and frailty rather than by operative technique alone. In this context, our synthesis primarily reflects overall cardiovascular vulnerability in comorbid and frail patients, with heart failure risk inferred indirectly from the available data. These findings support a patient-centered, risk-adapted surgical strategy in which the extent and timing of surgery and reconstruction are tailored to each patient’s cardiovascular profile and frailty status, with preferential use of breast-conserving or less complex procedures in vulnerable individuals. Integrating standardized frailty assessment and cardio-oncologic evaluation into preoperative workflows, and prospectively validating this tri-axial framework in dedicated cohorts, may improve perioperative risk stratification and reduce the burden of postoperative medical complications in an aging breast cancer population. Full article

The overexpression of cyclin-dependent kinase inhibitor p16 (INK4a) is widely recognized as a surrogate marker for high-risk human papillomavirus (HPV) in anogenital malignancies, but its significance in invasive breast carcinoma is complex and remains frequently debated. While historically investigated as a viral proxy, emerging evidence suggests that elevated p16 levels in breast tissue may instead reflect intrinsic cell-cycle dysregulation and retinoblastoma (Rb) pathway disruption, though direct molecular confirmation is lacking in this area of research. This study aims to evaluate the role of p16 as an indicator of tumor aggressiveness for high-risk phenotypes. We conducted a retrospective study of 100 female patients with invasive breast carcinoma. Employing a purposive sampling strategy rather than a consecutive series, we analyzed a targeted cohort consisting predominantly of triple-negative breast cancer (TNBC) and high-grade tumors to evaluate biomarker patterns specifically in advanced disease contexts. Immunohistochemical assessment was performed using a standardized cumulative nuclear and cytoplasmic scoring system, with expression thresholds defined by receiver operating characteristic (ROC) curve analysis optimized for histological grade. p16 overexpression was a predominant characteristic of these aggressive tumors and was identified in 64% of cases. Statistical evaluation revealed a robust and significant correlation between p16 overexpression and the triple-negative molecular subtype, as well as a marked inverse relationship with estrogen receptor (ER) status. Although p16 levels were frequently associated with specific aggressive phenotypes, no statistically significant difference in overall survival was observed between expression groups, a finding attributable to the uniformly high-risk nature of the selected cohort. This study suggests an association between p16 expression levels and aggressive tumor features, although the study design limits causal inferences. A non-significant trend towards p16 overexpression was observed in ductal carcinomas compared to lobular subtypes, while high p16 expression was noted exclusively in G3 tumors within this selected cohort, a finding influenced by the purposive sampling strategy and the ROC-based cutoff definition. Tumor necrosis was more prevalent in p16-overexpressing tumors. Furthermore, p16 levels showed a strong inverse relationship with estrogen receptor (ER) status, as they were significantly elevated in ER-negative and triple-negative tumors compared to luminal phenotypes. Full article

Background: Lymph node metastasis (LNM) is a determinant of prognosis and in guiding chemotherapy decisions in breast cancer. Herein, we aimed to discover the protease content of the circulating large extracellular vesicles (L-EVs) as potential markers for LNM. Methods: L-EVs were isolated from the plasma of chemotherapy-naïve breast cancer patients with negative LNM (nLNM, n = 40) and positive LNM (pLNM, n = 32) patients using differential centrifugation. The isolated L-EVs were characterized by Transmission Electron Microscopy, dynamic light scattering and EV marker profiling, and their protease content was profiled using unbiased proteome profiler human protease array. Results: Protease profiling uncovered that L-EVs contained significantly elevated levels of MMP-8 (p < 0.001) and MMP-9 (p < 0.05) in pLNM versus nLNM patients. Further validation by Western blotting confirmed that latent MMP-8 was significantly increased (p < 0.01) in L-EVs from pLNM patients. Interestingly, zymography revealed that L-EVs isolated from pLNM patients contained higher levels of latent MMP-9 compared with those from nLNM patients, whereas gelatinolytically active MMP-2 was only detected in L-EVs from pLNM patients and not in those from nLNM. Online datasets revealed that higher MMP-8 and MMP-9 mRNA levels were associated with poorer overall, relapse-free, and distant metastasis-free survival. Receiver operating characteristic (ROC) plotter analyses indicated that MMP-2 and MMP-8 may serve as predictive biomarkers for response to specific chemotherapeutic regimens. Conclusions: These findings highlight the potential clinical utility of L-EV-derived MMP-2, MMP-8, and MMP-9 expressions and/or activities, as non-invasive blood-based markers associated with nodal progression and therapeutic response. Full article

High-resolution LiDAR and individual-tree modeling are generating increasing volumes of tree-level spatial data, including coordinates, tree height, and diameter at breast height (DBH). However, the lack of scalable and spatially explicit identifiers still limits the organization and integration of tree records in digital twin forest systems. This paper presents a GeoSOT-based framework for assigning position-linked identifiers to standardized tree observation records. The proposed code is used as a spatial anchor for record organization, candidate retrieval, and lifecycle-oriented management, rather than as a direct label of biological tree identity. The framework is implemented through a Yukon-based workflow for spatial storage and GeoSOT-code attachment, with a Bigtable-style schema described for time-stamped record organization. In a Mengjiagang forest farm case study, 604 treetop observations were extracted from airborne-LiDAR-derived canopy height models. Perturbation tests, boundary stress testing, controlled candidate matching, and a prototype retrieval benchmark show that fine-level GeoSOT codes are sensitive to positional uncertainty, whereas coarser levels combined with target-cell and adjacent-cell retrieval provide more stable candidate filtering with compact candidate sets under controlled experimental conditions. These results suggest that GeoSOT-based coding can support tree-observation record organization and candidate matching in digital twin forest systems. Independent cross-source identity validation and deployed database-level benchmarking should be addressed using real multi-source datasets and operational database environments. Full article

Objectives: Lymphedema (LE) is a debilitating complication in breast cancer patients, typically identified through clinical symptoms and volume-based diagnostics. As early diagnosis is crucial for favorable outcomes of microsurgical procedures, a more sensitive tool for LE assessment is required. The primary aim of this study was to evaluate whether a prolongation in postoperative indocyanine (ICG) lymphography drainage time, relative to preoperative baseline values, serves as a predictor of future LE development. Methods: A total of 41 women undergoing axillary lymph node dissection received ICG lymphography preoperatively and four weeks postoperatively. Drainage time (the duration for ICG to reach the axilla) was recorded. Clinical LE was defined as a >10% limb volume difference 12 months post-surgery, while subjective LE (sLE) was assessed via the Lymphedema Life Impact Score. Results: LE developed in 19.5% of patients. Patients who developed LE exhibited significantly higher mean drainage prolongation compared to those who did not (335 s vs. 40 s; p = 0.004). ROC analysis identified an optimal threshold of 119 s for predicting LE, yielding 100% sensitivity and 84.85% specificity (AUC = 0.96). sLE was reported by 48.8% of patients. Their drainage prolongation was significantly greater than in the sLE group (188 s vs. 13 s; p = 0.03). Conclusions: Preliminary findings suggest postoperative prolongation of ICG drainage time may serve as a potential predictor of future LE. In our cohort, a 119 s delay at four weeks post-operation was associated with LE at 12 months. While these results are promising, further research in larger, more diverse populations is required to validate these thresholds for clinical utility. Full article

Background/Objectives: Artificial intelligence (AI) shows promise in supporting mammography interpretation and triaging referrals, potentially enhancing breast screening. However, successful AI integration depends on patient acceptance and trust. This study explores patient and public perceptions of AI in breast imaging and clinical decision-making to identify knowledge gaps and guide communication strategies. Methods: Paper surveys were distributed to women attending the Breast Care Unit at Queen’s Hospital, Burton, and the London Breast Institute between August and December 2025. Demographic data, levels of trust and comfort with AI, and concerns about AI were collected. Responses were analysed using descriptive statistics, Pearson’s Chi-square tests with Cramér’s V and thematic analysis. Results: One hundred and twenty participants completed the survey. Fifty percent would accept AI alongside clinicians for interpretation of mammograms or ultrasound scans, significantly associated with no previous breast cancer diagnosis (p = 0.02; Cramér’s V = 0.22, 2 degrees of freedom (df)) and technological comfort (p < 0.001; Cramér’s V = 0.42, 1 df). Lower acceptance was found among those with prior diagnosis and low comfort with technology. Acceptance of AI-assisted triage (44.5%) was also significantly associated with technological comfort (p = 0.008; Cramér’s V = 0.30, 1 df). Eighty percent reported no knowledge of AI use in breast clinics, and only 37% would trust AI findings. Qualitative analysis identified three themes: (1) clinician oversight as indispensable, (2) the knowledge gap as a barrier to acceptance, and (3) concerns about operational risks and accountability. Conclusions: Although patients were generally receptive to AI, acceptance was conditional on clinician supervision. Limited awareness and concerns about diagnostic accuracy remain barriers to implementation. Educational initiatives should precede widespread adoption to support informed and confident patient acceptance of AI-assisted imaging and decision-making. Full article

Understanding forest dynamics requires reliable inventories that assess tree- and stand-level characteristics. Traditionally, this has relied on field measurements such as diameter at breast height (DBH), height, and crown attributes, but these methods are labor-intensive and spatially limited. Remote sensing, particularly Light Detection and Ranging (LiDAR), has expanded forest inventory capacity by generating three-dimensional structural information. Mobile laser scanning (MLS), a recent adaptation, offers flexible, high-resolution data collection, though its performance across complex forests is still being evaluated. This study assessed the effectiveness of MLS in detecting individual trees and estimating DBH in mixed-species forests of the Northeastern United States. We also evaluated the influence of tree- and plot-level characteristics on detection accuracy and DBH estimation. Results showed an 85.2% tree detection rate, a 23.5% commission rate, and a DBH root mean square error (RMSE) of 1.98 cm (9.65%). Among the variables tested, tree DBH was the only significant predictor of detection probability; tree density and relative density had minimal effect. These findings demonstrate that MLS can achieve precise DBH estimation when trees are correctly identified, but false detections remain a limitation. Further methodological improvements are needed to enhance accuracy in structurally complex forests and advance MLS for operational forest monitoring. Full article

Background: Liquid biopsy-based biomarkers provide valuable insights into tumor biology, dynamics, burden, relapse prediction and therapeutic responsiveness. The stress-inducible heat shock protein 70 (Hsp70), which is frequently overexpressed in highly aggressive solid tumors and is presented on the cell membrane of tumors but not normal cells, is found in the circulation either as a free protein originating from dying cells or in the context of extracellular vesicles (EVs) that are actively released by viable tumor cells. This study demonstrates the potential value of circulating Hsp70 (eHsp70) levels across multiple solid tumor entities as an entity- and stage-dependent diagnostic biomarker reflecting tumor burden and disease stage. Methods: Circulating eHsp70 levels, as determined using the Hsp70-exo ELISA which detects free and EV-associated Hsp70, in plasma samples collected from patients with different tumor entities (n = 389) prior to the initiation of any oncological therapy and healthy controls (n = 108) between 2021 and 2025, were analyzed retrospectively. Tumor stages were categorized as early, locally advanced, or metastatic. The Kruskal–Wallis test was used for group comparisons and the Receiver Operating Characteristic (ROC) curve was used to evaluate the diagnostic performance of eHsp70 levels. DeLong’s test was used to calculate differences between AUC values. Results: In tumor patients (n = 389), circulating eHsp70 levels were significantly higher than those in healthy controls (n = 108) (Kruskal–Wallis, p < 0.001). eHsp70 levels progressively increased from early-stage to locally advanced and metastatic disease in a stage-dependent manner. Although ROC analysis demonstrated the limited discriminatory performance of eHsp70 levels in early-stage disease (AUC 0.569), increased discrimination was apparent in locally advanced disease (AUC 0.751), metastatic tumors (AUC 0.784) and combined advanced tumor diseases (AUC 0.765; significant by DeLong’s Test comparing early-stage to locally advanced and metastatic tumors), irrespective of the tumor entity with the highest AUC values in metastatic breast cancer (AUC 0.872), sarcoma (AUC 0.861) and non-small cell lung cancer (NSCLC) (AUC 0.835). Apart from minor entity-specific differences, the correlation of eHsp70 levels with the tumor stage remained consistent across all measured tumor entities. Conclusions: Circulating eHsp70 levels are markedly elevated in patients with highly malignant solid tumors and show a consistent, stage-dependent increase across multiple tumor types. These findings suggest that circulating eHsp70, as an indicator of tumor-associated cellular stress and overall tumor burden, represents a valuable biomarker for assessing disease stage, monitoring disease progression, and evaluating therapeutic responses. Full article

Reliable estimation of tree-level diameter at breast height (DBH) and stem volume from remote sensing data remains challenging across structurally heterogeneous plantation forests due to cross-site domain shift. This study proposes a structurally site-aware modelling framework designed to mitigate site-induced errors by prioritising training samples structurally proximate to the target site in predictor space. Using unmanned aerial vehicle-based laser scanning (ULS)-derived metrics from 20 geographically independent radiata pine plantation sites in New Zealand, we compared standard pooled workflows with site-aware implementations across multiple feature selection and regression combinations under leave-one-site-out (LOSO) validation. For DBH, the optimal site-aware Elastic Net configuration achieved a mean rRMSE of 16.0% and coefficient of determination (R²) of 0.607, reducing relative error by up to 23.7% compared with the corresponding standard workflow. Gains were more pronounced for stem volume, where the site-aware model achieved a mean rRMSE of 34.5% and R² of 0.648, substantially reducing cross-site errors observed under standard parametric formulations by 85.2% and outperforming a previously published high-dimensional Random Forest benchmark built on the same dataset (mean rRMSE of 35.6% and R² of 0.631). Feature selection patterns revealed that standard workflows converged on a narrow set of universally dominant structural predictors, whereas the site-aware approach redistributed predictor importance across sites, reflecting adaptive alignment to local structural variations. These findings demonstrate that correcting structural domain misalignment can enhance model transferability while maintaining parsimony, offering a scalable solution for operational multi-site forest inventory modelling. Full article

This experiment evaluated the effects of pellet diameter on growth performance and intestinal health of piglets during the creep feeding stage. A total of 144 7-day-old suckling piglets (body weight of 2.2 ± 0.3 kg) were randomly assigned to four groups and fed the same formula as meal feed and pellets of 2 mm, 4 mm, and 8 mm in diameter, respectively. Each treatment consisted of six replicates of six piglets. The trial was divided into two phases by weaning time: 7–21 days (breast milk + creep feed) and 21–35 days (creep feed only). After the feeding trial, piglets from the meal feed group and the 8 mm pellet group were selected for slaughter and sampling. The results showed that before weaning, average daily feed intake (ADFI) increased significantly with increasing pellet diameter (p < 0.001). Post-weaning, piglets fed 8 mm pellets presented significantly higher final body weight (FBW) and average daily gain (ADG) than those in the meal group (p < 0.05). Apparent nutrient digestibility (ATTD) in pellet groups was significantly higher than that in the meal feed group and rose with increasing pellet diameter (p < 0.001). The organ indices of the stomach and large intestine in the 8 mm group of piglets were significantly lower than those of the meal group. The jejunal villus height (VH) in the 8 mm group showed a trend toward an increase (p = 0.066), and the ileal crypt depth (CD) was significantly lower (p = 0.004), with significantly higher digestive enzyme activities in the jejunum and ileum (p < 0.05). In the 8 mm group, the relative abundances of Bacteroidetes in the jejunum and Actinobacteriota in the cecum and colon increased, while those of Pseudomonadota decreased; jejunal microbial relative richness increased significantly, while the ileal microbial operational taxonomic unit (OTU) richness decreased obviously. In conclusion, pellets improved the growth performance of creep feeding piglets. Compared with meal, 8 mm pellets can significantly enhance intestinal health level and nutrient digestion and absorption capacity by optimizing intestinal morphology, boosting digestive enzyme activities, and improving flora structure. Full article

Objective: To evaluate the Tumor-Immune-Proliferation-Inflammation (TIPI) score as a composite biomarker for predicting pathological complete response (pCR) in human epidermal growth factor receptor 2 (HER2)-positive breast cancer treated with neoadjuvant therapy. Methods: This retrospective single-center study included 75 patients with HER2-positive invasive breast cancer treated with neoadjuvant chemotherapy plus dual anti-HER2 blockade (trastuzumab and pertuzumab). The association between the TIPI score and pCR was assessed using receiver operating characteristic (ROC) analysis and logistic regression. Results: pCR was achieved in 34 patients (45.3%). The optimal TIPI cut-off was 11.41. Patients with high TIPI scores had a higher pCR rate than those with low TIPI scores (56.3% vs. 25.9%, p = 0.016). However, the discriminative performance of the score was modest (AUC 0.598, 95% CI: 0.467–0.730; p = 0.145). In the adjusted analysis, hormone receptor negativity remained the most consistent factor associated with pCR. Conclusions: The TIPI score was developed as a preliminary composite model integrating selected tumor- and host-related biological variables and showed an exploratory association with pCR in this single-center HER2-positive cohort. Given the modest discriminative performance and lack of external validation, these findings should be interpreted cautiously. Further validation in larger independent cohorts is required before the score can be considered for clinical stratification or implementation. Full article

Background/Objectives: Image quality of mammograms in breast cancer screening is strongly operator-dependent, particularly in the mediolateral oblique (MLO) projection where adequate visualisation of the pectoralis major muscle serves as a surrogate marker of posterior tissue inclusion. Current positioning assessment is predominantly qualitative and subject to inter-observer variability. This study aimed to quantitatively evaluate pectoral muscle visualisation and compression force variability among radiographers participating in a national screening programme. Methods: A retrospective observational study was conducted at Clinical Hospital Center Rijeka in January and February 2020. A total of 464 digital MLO mammograms were analysed. Images from nine radiographers were randomly retrieved from the institutional Picture Archiving and Communication System (PACS). Pectoral muscle length and width were measured using a standard clinical workstation with an integrated distance measurement tool. Additional variables included radiographer gender, breast side (LMLO vs. RMLO), imaging order, and applied compression force. Statistical analyses included Welch’s ANOVA, one-way ANOVA, t-tests, and appropriate post hoc comparisons. Results: Across all MLO projections, the combined mean pectoral muscle width was 41.0 ± 11.4 mm and the mean length was 134.3 ± 21.7 mm. Significant inter-operator differences were observed in pectoral muscle width (p < 0.001) and length (p = 0.023). Mean muscle width ranged from 35.0 mm to 54.2 mm, and mean length from 126.5 mm to 139.4 mm across radiographers. No significant differences were found with respect to radiographer gender, breast side, or imaging order (all p > 0.05). Compression force differed significantly among radiographers (p < 0.001), ranging from 117.0 ± 18.3 N to 184.8 ± 33.9 N. Conclusions: This study demonstrates significant inter-operator variability in both pectoral muscle visualisation and applied compression force during MLO mammography. These findings indicate that important technical aspects of mammographic examination remain strongly operator-dependent and highlight the need for more consistent positioning practices within screening programmes. Quantitative measurement of pectoral muscle dimensions may serve as a practical and objective approach for monitoring positioning quality and supporting quality assurance in routine clinical practice. Full article

Background: Pre-pectoral direct-to-implant breast reconstruction is increasingly adopted after mastectomy because it avoids pectoralis major dissection, reduces postoperative pain, and eliminates animation deformity. However, reconstruction in patients with large or markedly ptotic breasts remains challenging because of skin envelope management, nipple–areola complex (NAC) viability, and implant stability. This study evaluated batwing skin-reducing mastectomy with immediate pre-pectoral polyurethane-coated implant reconstruction. Methods: We conducted a retrospective single-center study of consecutive patients who underwent batwing skin-reducing mastectomy with immediate pre-pectoral polyurethane-coated implant reconstruction between November 2022 and January 2025. Demographic, oncologic, operative, postoperative, and BREAST-Q data were collected. Primary outcomes included complications, oncologic events, and 12-month patient-reported outcomes. Results: Thirteen patients underwent reconstruction, accounting for 18 breasts, with a mean follow-up of 12.85 months. Mean age was 54.5 ± 9.7 years, mean body mass index was 27.0 ± 3.4 kg/m², and mean Regnault ptosis grade was 3.46 ± 0.52. No seromas or oncologic recurrences were observed. One hematoma and one late infection requiring implant removal occurred. Superficial NAC/central flap epidermolysis developed in four patients and resolved conservatively; no full-thickness NAC necrosis occurred. BREAST-Q scores improved significantly in all domains at 12 months, including satisfaction with breasts, psychosocial well-being, physical well-being, and sexual well-being (all p < 0.05). Conclusions: Batwing skin-reducing mastectomy with immediate pre-pectoral polyurethane implant reconstruction appears safe and reproducible in selected patients with advanced ptosis, with acceptable complication rates and significant improvement in patient-reported outcomes. Full article

Accurate identification of disease-associated microRNAs (miRNAs) is crucial for elucidating pathogenic mechanisms and advancing therapeutic discovery. Although computational methods, particularly those based on biological networks, have become essential tools for predicting miRNA-disease associations, existing approaches often struggle to comprehensively learn from heterogeneous data and optimize feature representations. To overcome these limitations, we propose the Multi-view Hybrid Attention Graph Convolutional Network (MV-HAGCN). This framework constructs a comprehensive heterogeneous network by integrating multi-source biological information, simultaneously capturing miRNA similarity and disease similarity. We design a hierarchical attention mechanism to enable refined feature learning: first, the Efficient Channel Attention (ECA) module prioritizes information-rich input features, ensuring the model focuses on high-value biological characteristics. Subsequently, the Multi-Head Self-Attention Graph Convolutional Network operates on these refined features. Through iterative message passing and multi-head self-attention, it captures not only direct first-order relationships between nodes but also explicitly models and infers complex, indirect higher-order relationships within the network. This hierarchical design progressively refines feature representations, from channel-level recalibration to global structural dependency modeling, enabling the model to capture both local and high-order relational patterns. Furthermore, a dynamic weight learning strategy adaptively integrates multi-perspective similarity matrices, achieving superior feature complementarity and synergy. Finally, the high-order node representations learned through multi-layer graph convolutions are fed into a multi-layer perceptron for integration and nonlinear transformation, enabling precise prediction of potential miRNA-disease associations. Comprehensive evaluation through five-fold cross-validation on HMDD v2.0 and v3.2 benchmark datasets demonstrates that MV-HAGCN consistently outperforms existing state-of-the-art methods in predictive performance. Case studies targeting key diseases such as breast cancer, lung tumors, and pancreatic disorders revealed that the top 50 miRNAs associated with each of these three conditions were all validated in databases, confirming the practical value of this model in screening candidate miRNAs with high biological relevance. Full article

Background and Objectives: Fragmented anatomical, imaging, and surgical accounts of the gracilis muscle hinder reproducible reporting and operative planning. We aimed to integrate prior systems into an Integrated Gracilis Framework (IGF)—an integrative synthesis, not a new classification—that harmonizes terminology, defines imaging correlates/pitfalls, and links morphology to surgical decisions. Methods: Integrative narrative review (January 1900–October 2025) of PubMed/MEDLINE, Scopus, and Web of Science covering vascularization (pedicles, perforators), innervation (motor points/segments), imaging (ultrasound, MRI, MR neurography, CTA/MRA), and clinical applications (facial reanimation, elbow flexion, perineal and breast reconstruction). Two reviewers screened/extracted with consensus adjudication. Searches were restricted to English or records with reliable English-language summaries. Results: IGF consolidates morphological variants, motor-point/segmental innervation, and pedicle/perforator patterns with imaging correlates and common pitfalls. It provides a crosswalk mapping historical systems to IGF and a proposed preoperative workflow (anatomy → imaging → harvest → neurotization) for structured planning and reporting (proposed framework; not prospectively validated). We summarize considerations for free/functional gracilis in facial reanimation and elbow-flexion, and for pedicled/free myocutaneous or perforator flaps in perineal and breast reconstruction. Conclusions: IGF offers a standardized language and decision scaffold to improve study comparability and transparency in operative reporting; as a nonvalidated synthesis, it requires systematic validation through cadaver–imaging correlation and prospective surgical cohorts. Full article