Sentinel node navigation surgery in cervical cancer: a systematic review and metaanalysis

Current applications of indocyanine green (ICG) in abdominal, gynecologic and urologic surgery: a meta-review and quality analysis with use of the AMSTAR 2 instrument

BACKGROUND

Indocyanine green (ICG) is an injectable fluorochrome that has recently gained popularity as a means of assisting intraoperative visualization during laparoscopic and robotic surgery. Many systematic reviews and meta-analyses have been published. We conducted a meta-review to synthesize the findings of these studies.

METHODS

PubMed and Embase were searched to identify systematic reviews and meta-analyses coping with the uses of ICG in abdominal operations, including Metabolic Bariatric Surgery, Cholecystectomy, Colorectal, Esophageal, Gastric, Hepato-Pancreato-Biliary, Obstetrics and Gynecology (OG), Pediatric Surgery, Surgical Oncology, Urology, (abdominal) Vascular Surgery, Adrenal and Splenic Surgery, and Interdisciplinary tasks, until September 2023. We submitted the retrieved meta-analyses to qualitative analysis based on the AMSTAR 2 instrument.

RESULTS

We identified 116 studies, 41 systematic reviews (SRs) and 75 meta-analyses (MAs), spanning 2013-2023. The most thoroughly investigated (sub)specialties were Colorectal (6 SRs, 25 MAs), OG (9 SRs, 15 MAs), and HPB (4 SRs, 12 MAs). Interestingly, there was high heterogeneity regarding the administered ICG doses, routes, and timing. The use of ICG offered a clear benefit regarding anastomotic leak prevention, particularly after colorectal and esophageal surgery. There was no clear benefit regarding sentinel node detection after OG. According to the AMSTAR 2 tool, most meta-analyses ranked as "critically low" (34.7%) or "low" (58.7%) quality. There were only five meta-analyses (6.7%) that qualified as "moderate" quality, whereas there were no "high" quality reviews.

CONCLUSIONS

Regardless of the abundance of pertinent literature and reviews, surgeons should be cautious when interpreting their results on ICG use in abdominal surgery. Future reviews should focus on ensuring methodological vigor; establishing clear protocols of ICG dose, route of administration, and timing; and improving reporting quality. Other sources of data (e.g., registries) and novel methods of data analysis (e.g., machine learning) might also contribute to an enhanced role of ICG as a decision-making tool in surgery.

Development of a supportive care needs eHealth application for patients with cervical cancer undergoing surgery: a feasibility study

PURPOSE

To inform the development of an eHealth application for patients with cervical cancer for monitoring supportive care needs, perceived care supply and quality of life.

METHODS

A mixed-method design was used. The 19-month process involved five phases: (1) a literature review to screen the components of applications, (2) a cross-sectional needs assessment for patients with cervical cancer to define the needs and application program frame, (3) expert consultation to refine the draft, (4) software development, and (5) pilot testing and user comment collection. Patients in the intervention group received a 7-day application intervention combined with usual care. Supportive care needs, perceived care supply, quality of life and user's additional comments were collected.

RESULTS

The literature review results in phase 1 revealed the importance of full preparation, especially a supportive care needs assessment, before application development. Subsequent supportive care needs investigation in phase 2 revealed that the most urgent needs were informational needs and privacy protection. In phase 3, 43 expert recommendations for application improvement were refined. The new application contained the patient and the health care professional portal in phase 4. Then, on Day 7, there existed score changes of the outcome measures in both intervention and control group. Users had a positive experience with the application.

CONCLUSIONS

This study demonstrates the feasibility of applications targeting access to supportive care, which may be effective for improving the outcome measures but needed to be evaluated in future studies.

Predictors of Non-Sentinel Lymph Node Metastasis in Patients with Positive Sentinel Lymph Node in Early-Stage Cervical Cancer: A SENTICOL GROUP Study

BACKGROUND

The goal of this study was to identify the risk factors for metastasis in the remaining non-sentinel lymph nodes (SLN) in the case of positive SLN in early-stage cervical cancer.

METHODS

An ancillary analysis of two prospective multicentric databases on SLN biopsy for cervical cancer (SENTICOL I and II) was performed. Patients with early-stage cervical cancer (FIGO 2018 IA to IIA1), with bilateral SLN detection and at least one positive SLN after ultrastaging, were included.

RESULTS

405 patients were included in SENTICOL I and Il. Fifty-two patients had bilateral SLN detection and were found to have SLN metastasis. After pelvic lymphadenectomy, metastatic involvement of non-SLN was diagnosed in 7 patients (13.5%). Patients with metastatic non-SLN were older (51.9 vs. 40.8 years, p = 0.01), had more often lympho-vascular space invasion (LVSI) (85.7% vs. 35.6%, p = 0.03), and had more often parametrial involvement (42.9% vs. 6.7%, p = 0.003). Multivariate analysis retained age (OR = 1.16, 95% IC = [1.01-1.32], p = 0.03) and LVSI (OR = 25.97, 95% IC = [1.16-582.1], p = 0.04) as independently associated with non-SLN involvement.

CONCLUSIONS

Age and LVSI seemed to be predictive of non-SLN metastasis in patients with SLN metastasis in early-stage cervical cancer. Larger cohorts are needed to confirm the results and clinical usefulness of such findings.

Identification of lymph node metastasis in pre-operation cervical cancer patients by weakly supervised deep learning from histopathological whole-slide biopsy images

BACKGROUND

Lymph node metastasis (LNM) significantly impacts the prognosis of individuals diagnosed with cervical cancer, as it is closely linked to disease recurrence and mortality, thereby impacting therapeutic schedule choices for patients. However, accurately predicting LNM prior to treatment remains challenging. Consequently, this study seeks to utilize digital pathological features extracted from histopathological slides of primary cervical cancer patients to preoperatively predict the presence of LNM.

METHODS

A deep learning (DL) model was trained using the Vision transformer (ViT) and recurrent neural network (RNN) frameworks to predict LNM. This prediction was based on the analysis of 554 histopathological whole-slide images (WSIs) obtained from Qilu Hospital of Shandong University. To validate the model's performance, an external test was conducted using 336 WSIs from four other hospitals. Additionally, the efficiency of the DL model was evaluated using 190 cervical biopsies WSIs in a prospective set.

RESULTS

In the internal test set, our DL model achieved an area under the curve (AUC) of 0.919, with sensitivity and specificity values of 0.923 and 0.905, respectively, and an accuracy (ACC) of 0.909. The performance of the DL model remained strong in the external test set. In the prospective cohort, the AUC was 0.91, and the ACC was 0.895. Additionally, the DL model exhibited higher accuracy compared to imaging examination in the evaluation of LNM. By utilizing the transformer visualization method, we generated a heatmap that illustrates the local pathological features in primary lesions relevant to LNM.

CONCLUSION

DL-based image analysis has demonstrated efficiency in predicting LNM in early operable cervical cancer through the utilization of biopsies WSI. This approach has the potential to enhance therapeutic decision-making for patients diagnosed with cervical cancer.

The distribution pattern of pelvic lymph nodal metastases in cervical cancer

PURPOSE

Depiction of pelvic lymph node metastasis (LNM) sites among patients with cervical cancer facilitates accurate determination of the extent of dissection and radiotherapy regimens.

METHODS

A retrospective study of 1182 cervical cancer patients who underwent radical hysterectomy and pelvic lymph node dissection between 2008 and 2018 was performed. The number of removed pelvic lymph nodes and metastasis status in different anatomical regions was analyzed. The prognostic difference of patients with lymph node involvement stratified by various factors was analyzed by Kaplan-Meier method.

RESULTS

The median number of pelvic lymph nodes detected was 22, mainly from obturator (29.54%) and inguinal (21.14%) sites. Metastatic pelvic lymph nodes were found in 192 patients, with obturator accounting for the highest percentage (42.86%). The patients with lymph node involvement in single site had better prognosis that those in multiple sites. The overall- (P = 0.021) (OS) and progression-free (P < 0.001) survival (PFS) curves of patients with inguinal lymph node metastases were worse compared to those with obturator site. There was no difference in the OS and PFS among patients with 2 and more than 2 lymph nodes involvement.

CONCLUSION

An explicit map of LNM in patients with cervical cancer was presented in this study. Obturator lymph nodes tended to be involved. The prognosis of patients with inguinal lymph node involvement was poor in contrast to that with obturator LNM. In patients with inguinal lymph node metastases, clinical staging needs to be reconsidered and extended radiotherapy to the inguinal region needs to be strengthened.