One-year Visual and Refractive Outcomes of Deep Anterior Lamellar Keratoplasty (DALK) in Patients with Advanced Keratoconus

Donut-shaped Corneal Allogeneic Intrastromal Segment as an Alternative to Deep Anterior Lamellar Keratoplasty in Advanced Keratoconus

PURPOSE

The aim of this study was to describe a new technique of selective corneal stromal transplantation for keratoconus treatment, donut-shaped CAIRS (corneal allogeneic intrastromal ring segment).

METHODS

A donut-shaped corneal graft is obtained using a double-bladed trephine. Descemet membrane, endothelium, and epithelium are all removed from the graft. Only stromal tissue is transplanted. A wide 360-degree intrastromal tunnel is created using the femtosecond laser, with a 30-degree angulation. The diameter is from 5.4 mm to 8 mm optical zone. After dehydration, the corneal graft is inserted into the tunnel. We report the clinical and tomographic outcomes after the procedure in 3 patients.

RESULTS

The mean follow-up time after donut-shaped CAIRS was 6.01 ± 1.02 months. In case 1, best spectacle-corrected visual acuity improved from 20/150 to 20/40. In case 2, it improved from 20/400 to 20/40, and in case 3 from 20/200 to 20/40. The mean preoperative K was 57.3 ± 4.5 D and reduced to 44.2 ± 2.5 D after donut-shaped CAIRS. The mean spherical equivalent decreased from -9.8 ± 3.2 preoperatively to -3.2 ± 2.2 postoperatively. No intraoperative or postoperative complications were observed. Anterior segment OCT showed a mid-stroma implant, fusiform in shape, equidistant from the epithelium and endothelium.

CONCLUSIONS

Donut-shaped CAIRS is a variation of the traditional CAIRS technique and showed to be an alternative option for keratoconus treatment, especially in moderate to advanced cases with a central clear cornea without scars. The technique is minimally invasive, and the visual axis remains untouched.

Keratoconus: exploring fundamentals and future perspectives - a comprehensive systematic review

Background

New developments in artificial intelligence, particularly with promising results in early detection and management of keratoconus, have favorably altered the natural history of the disease over the last few decades. Features of artificial intelligence in different machine such as anterior segment optical coherence tomography, and femtosecond laser technique have improved safety, precision, effectiveness, and predictability of treatment modalities of keratoconus (from contact lenses to keratoplasty techniques). These options ingrained in artificial intelligence are already underway and allow ophthalmologist to approach disease in the most non-invasive way.

Objectives

This study comprehensively describes all of the treatment modalities of keratoconus considering machine learning strategies.

Design

A multidimensional comprehensive systematic narrative review.

Data sources and methods

A comprehensive search was done in the five main electronic databases (PubMed, Scopus, Web of Science, Embase, and Cochrane), without language and time or type of study restrictions. Afterward, eligible articles were selected by screening the titles and abstracts based on main mesh keywords. For potentially eligible articles, the full text was also reviewed.

Results

Artificial intelligence demonstrates promise in keratoconus diagnosis and clinical management, spanning early detection (especially in subclinical cases), preoperative screening, postoperative ectasia prediction after keratorefractive surgery, and guiding surgical decisions. The majority of studies employed a solitary machine learning algorithm, whereas minor studies assessed multiple algorithms that evaluated the association of various keratoconus staging and management strategies. Last but not least, AI has proven effective in guiding the implantation of intracorneal ring segments in keratoconus corneas and predicting surgical outcomes.

Conclusion

The efficient and widespread clinical translation of machine learning models in keratoconus management is a crucial goal of potential future approaches to better visual performance in keratoconus patients.

Trial registration

The article has been registered through PROSPERO, an international database of prospectively registered systematic reviews, with the ID: CRD42022319338.

Bubbling With Confidence: A Study of Numerous Deep Anterior Lamellar Keratoplasty Cases Using Anwar's Big Bubble Technique

PURPOSE

This study aims to assess the postoperative results, variability, and complications of a hundred deep anterior lamellar keratoplasty cases. Study design and duration: This is an observational study. The study was conducted at Pak International Medical College (PIMC) for a duration of four years (January 2019-January 2023).

METHODOLOGY

Our study collected information on a hundred cases of deep anterior lamellar keratoplasty (DALK) utilizing Anwar's big bubble technique, consisting of patients with keratoconus, superficial corneal scars, and macular dystrophy. Consenting patients had their pre and postoperative visual acuities and keratometry readings recorded. Overall success and complications were recorded and compared with the present literature.

RESULTS

Big bubble formation was achieved in 87% (n = 87) eyes and not achieved in 13% (n=13). There was a significant reduction in keratometry values after the procedures as well as improved vision in all patients, with 84% reporting significant improvement. Descemet membrane exposure was achieved in 91% (n=91). Complications included the failure of Anwar's big bubble formation in 13% (n=13) patients and the failure to expose Descemet's in nine patients (9%).

CONCLUSION

DALK using the big bubble technique is a safe and effective procedure in patients with corneal diseases who have a healthy Descemet membrane and endothelium.