Application of three-dimensional computed tomography imaging and reconstructive techniques in lung surgery: A mini-review

Evaluating the use of three-dimensional reconstruction visualization technology for precise laparoscopic resection in gastroesophageal junction cancer

BACKGROUND

Laparoscopic gastrectomy for esophagogastric junction (EGJ) carcinoma enables the removal of the carcinoma at the junction between the stomach and esophagus while preserving the gastric function, thereby providing patients with better treatment outcomes and quality of life. Nonetheless, this surgical technique also presents some challenges and limitations. Therefore, three-dimensional reconstruction visualization technology (3D RVT) has been introduced into the procedure, providing doctors with more comprehensive and intuitive anatomical information that helps with surgical planning, navigation, and outcome evaluation.

AIM

To discuss the application and advantages of 3D RVT in precise laparoscopic resection of EGJ carcinomas.

METHODS

Data were obtained from the electronic or paper-based medical records at The First Affiliated Hospital of Hebei North University from January 2020 to June 2022. A total of 120 patients diagnosed with EGJ carcinoma were included in the study. Of these, 68 underwent laparoscopic resection after computed tomography (CT)-enhanced scanning and were categorized into the 2D group, whereas 52 underwent laparoscopic resection after CT-enhanced scanning and 3D RVT and were categorized into the 3D group. This study had two outcome measures: the deviation between tumor-related factors (such as maximum tumor diameter and infiltration length) in 3D RVT and clinical reality, and surgical outcome indicators (such as operative time, intraoperative blood loss, number of lymph node dissections, R0 resection rate, postoperative hospital stay, postoperative gas discharge time, drainage tube removal time, and related complications) between the 2D and 3D groups.

RESULTS

Among patients included in the 3D group, 27 had a maximum tumor diameter of less than 3 cm, whereas 25 had a diameter of 3 cm or more. In actual surgical observations, 24 had a diameter of less than 3 cm, whereas 28 had a diameter of 3 cm or more. The findings were consistent between the two methods (χ2 = 0.346, P = 0.556), with a kappa consistency coefficient of 0.808. With respect to infiltration length, in the 3D group, 23 patients had a length of less than 5 cm, whereas 29 had a length of 5 cm or more. In actual surgical observations, 20 cases had a length of less than 5 cm, whereas 32 had a length of 5 cm or more. The findings were consistent between the two methods (χ2 = 0.357, P = 0.550), with a kappa consistency coefficient of 0.486. Pearson correlation analysis showed that the maximum tumor diameter and infiltration length measured using 3D RVT were positively correlated with clinical observations during surgery (r = 0.814 and 0.490, both P < 0.05). The 3D group had a shorter operative time (157.02 ± 8.38 vs 183.16 ± 23.87), less intraoperative blood loss (83.65 ± 14.22 vs 110.94 ± 22.05), and higher number of lymph node dissections (28.98 ± 2.82 vs 23.56 ± 2.77) and R0 resection rate (80.77% vs 61.64%) than the 2D group. Furthermore, the 3D group had shorter hospital stay [8 (8, 9) vs 13 (14, 16)], time to gas passage [3 (3, 4) vs 4 (5, 5)], and drainage tube removal time [4 (4, 5) vs 6 (6, 7)] than the 2D group. The complication rate was lower in the 3D group (11.54%) than in the 2D group (26.47%) (χ2 = 4.106, P < 0.05).

CONCLUSION

Using 3D RVT, doctors can gain a more comprehensive and intuitive understanding of the anatomy and related lesions of EGJ carcinomas, thus enabling more accurate surgical planning.

Lung Cancer Surgery in Octogenarians: Implications and Advantages of Artificial Intelligence in the Preoperative Assessment

The general world population is aging and patients are often diagnosed with early-stage lung cancer at an advanced age. Several studies have shown that age is not itself a contraindication for lung cancer surgery, and therefore, more and more octogenarians with early-stage lung cancer are undergoing surgery with curative intent. However, octogenarians present some peculiarities that make surgical treatment more challenging, so an accurate preoperative selection is mandatory. In recent years, new artificial intelligence techniques have spread worldwide in the diagnosis, treatment, and therapy of lung cancer, with increasing clinical applications. However, there is still no evidence coming out from trials specifically designed to assess the potential of artificial intelligence in the preoperative evaluation of octogenarian patients. The aim of this narrative review is to investigate, through the analysis of the available international literature, the advantages and implications that these tools may have in the preoperative assessment of this particular category of frail patients. In fact, these tools could represent an important support in the decision-making process, especially in octogenarian patients in whom the diagnostic and therapeutic options are often questionable. However, these technologies are still developing, and a strict human-led process is mandatory.

New developments in the imaging of lung cancer

Radiological and nuclear medicine methods play a fundamental role in the diagnosis and staging of patients with lung cancer. Imaging is essential in the detection, characterisation, staging and follow-up of lung cancer. Due to the increasing evidence, low-dose chest computed tomography (CT) screening for the early detection of lung cancer is being introduced to the clinical routine in several countries. Radiomics and radiogenomics are emerging fields reliant on artificial intelligence to improve diagnosis and personalised risk stratification. Ultrasound- and CT-guided interventions are minimally invasive methods for the diagnosis and treatment of pulmonary malignancies. In this review, we put more emphasis on the new developments in the imaging of lung cancer.

Study on high-precision three-dimensional reconstruction of pulmonary lesions and surrounding blood vessels based on CT images

The adoption of computerized tomography (CT) technology has significantly elevated the role of pulmonary CT imaging in diagnosing and treating pulmonary diseases. However, challenges persist due to the complex relationship between lesions within pulmonary tissue and the surrounding blood vessels. These challenges involve achieving precise three-dimensional reconstruction while maintaining accurate relative positioning of these elements. To effectively address this issue, this study employs a semi-automatic precise labeling process for the target region. This procedure ensures a high level of consistency in the relative positions of lesions and the surrounding blood vessels. Additionally, a morphological gradient interpolation algorithm, combined with Gaussian filtering, is applied to facilitate high-precision three-dimensional reconstruction of both lesions and blood vessels. Furthermore, this technique enables post-reconstruction slicing at any layer, facilitating intuitive exploration of the correlation between blood vessels and lesion layers. Moreover, the study utilizes physiological knowledge to simulate real-world blood vessel intersections, determining the range of blood vessel branch angles and achieving seamless continuity at internal blood vessel branch points. The experimental results achieved a satisfactory reconstruction with an average Hausdorff distance of 1.5 mm and an average Dice coefficient of 92%, obtained by comparing the reconstructed shape with the original shape,the approach also achieves a high level of accuracy in three-dimensional reconstruction and visualization. In conclusion, this study is a valuable source of technical support for the diagnosis and treatment of pulmonary diseases and holds promising potential for widespread adoption in clinical practice.

Anatomy of the lung revisited by 3D-CT imaging

The anatomy of the lung was originally described based on data acquired from cadaveric studies and surgical findings. Over time, computed tomography (CT) and three-dimensional (3D) imaging techniques have been developed, allowing for reconstruction and understanding of lung anatomy in a more intuitive way. The wide adoption of 3D-CT imaging technology has led to a variety of anatomical studies performed not only by anatomists but also by surgeons and radiologists. Such studies have led to new or modified classification systems, shed light on lung anatomy from a useful surgical viewpoint, and enabled us to analyze lung anatomy with a focus on particular anatomical features. 3D images also allow for enhanced pre- and intra-operative simulation, improved surgical safety, enhanced educational utility, and the capacity to perform large-scale anatomical studies in shorter time frames. We will review here the key features of 3D-CT imaging of the lung, along with representative anatomical studies regarding (I) general lung anatomy, (II) anatomy of the right and left lobes, and (III) features of interlobar vessels. The current surge of 3D imaging analysis shows that the field is growing, with the technology continuing to improve. Future studies using these new and innovative methodologies will continue to refine our understanding of lung anatomy while enhancing our ability to perform safe and effective surgical resections.