The clinical problem the Italian team set out to address is well known to anyone who works in pediatric oncology. When a child is diagnosed with a malignant renal mass, the surgical team must decide whether to remove the entire kidney, a procedure called radical nephrectomy, or to attempt nephron-sparing surgery, in which only the tumor and a thin margin of healthy tissue are excised. Nephron-sparing surgery is strongly preferred whenever it is safe, because children who keep functioning kidney tissue face a lower lifetime risk of chronic kidney disease, hypertension, and the long-term consequences of reduced renal reserve. But deciding whether the tumor can be safely shaved away from vital vessels and collecting structures requires an exquisitely detailed understanding of each patient’s unique anatomy — something that flat CT and MRI slices, read one at a time, do not always convey intuitively even to experienced surgeons.

The Turin group, led by pediatric urological surgeon Elisa Cerchia together with colleagues from the hospital’s pediatric surgery, oncology, and radiology units and the urology department of the University of Torino, tested a straightforward technical workflow. Standard abdominal MRI or CT examinations were performed for each patient as part of normal clinical care. The image data, stored in the universal DICOM format that medical scanners produce, were then imported into segmentation software. Segmentation is the computational process of outlining, slice by slice, the boundaries of each structure of interest — the tumor, the renal artery and its branches, the renal vein, the healthy kidney parenchyma, and the urinary collecting system. Once each structure is traced, the software renders it as a colored, fully rotatable three-dimensional object that can be zoomed, turned, made translucent, or viewed from any angle on a screen, effectively letting the surgeon fly through the child’s anatomy before making a single incision.

Eight patients, four boys and four girls, with complex renal masses were included in the study. For each child, the 3D virtual reconstruction was completed before surgery and reviewed by the surgeons and the pediatric radiologist involved in the case. To evaluate the technology rigorously rather than anecdotally, the team designed a modified closed-ended questionnaire administered in two phases, one before the operation and one afterward. Respondents compared the 3D models directly against the conventional imaging studies, rating how well each modality displayed the tumor and its relationships with arteries, veins, and the urinary tract, and assessing whether the reconstruction helped define the criteria for choosing nephron-sparing surgery over radical removal. The questionnaire also asked whether the models were practical to consult during the operation itself.

The statistical results were striking. For the tumor, the arteries, and the veins, the 3D virtual reconstructions were rated significantly better than conventional imaging, with p-values below 0.0001 for each of those structures — a level of significance that indicates the difference is extremely unlikely to be a statistical fluke even in a small case series. The urinary tract was the one exception; here the advantage of the 3D models did not reach statistical significance, with a p-value of 0.0888, suggesting that the collecting system may already be adequately visualized by standard scans or that segmentation of this thin-walled structure is technically harder to render convincingly. Even so, the overall pattern was unmistakable: the interactive models outperformed the flat images that surgeons have relied on for decades.

Perhaps the most clinically meaningful finding concerned surgical decision making. The study found that 3D virtual reconstruction was significantly more effective in defining the elective criteria for nephron-sparing surgery, with a p-value of 0.0003. In practical terms, this means the models helped surgeons judge whether a tumor could be removed while preserving healthy kidney tissue — the single most consequential decision in these operations. The questionnaire results also showed that the models were fundamentally easier to use during surgery than conventional images, with a p-value of 0.0006. A surgeon in the operating room can glance at a rotatable 3D model and instantly re-orient themselves in three-dimensional space, whereas scrolling through stacks of two-dimensional slices mid-operation is cumbersome and mentally taxing.

In the series, the eight children underwent a total of seven recorded operations: four radical nephrectomies and three nephron-sparing procedures. That three of the children could be treated with kidney-preserving surgery at all reflects the kind of complex, carefully selected cases for which preoperative three-dimensional planning is most valuable. In tumors judged too large or too centrally located for partial removal, the models still contributed by clarifying vascular anatomy before a radical nephrectomy, where precise knowledge of the renal artery and vein is essential for safe vessel control. The authors conclude that 3D virtual reconstruction is a genuinely useful tool in the preoperative evaluation of children with complex renal masses and that it facilitates nephron-sparing surgery in selected patients.

The technical pipeline behind these results deserves attention because it is reproducible in any hospital with standard imaging equipment. No additional scanning is required; the same DICOM datasets acquired for diagnosis feed the reconstruction. Segmentation software separates the anatomy into labeled structures, and rendering engines assemble them into interactive volumes. Some centers in the broader field go further and 3D-print physical models from the same data, which can be sterilized and brought into the operating theater, but the Turin study focused on the virtual models themselves, which require no printing hardware and can be shared instantly across the surgical team, from the operating room to the tumor board where treatment decisions are made.

What makes the study especially credible is its multidisciplinary design. The questionnaire was completed not only by the operating surgeons but also by the pediatric radiologist responsible for interpreting the original scans, meaning the comparison between 3D and conventional imaging was evaluated from multiple professional perspectives. The work also drew on collaboration with adult urological surgeons at the Città della Salute e della Scienza hospital in Turin, bringing experience from the larger field of kidney surgery into the pediatric arena. The project received no external funding, and the authors declare no competing interests, with technical support for the reconstruction workflow acknowledged from a collaborating company. The study was approved by the local ethics committee, and informed consent was obtained from each child’s parents or guardian in accordance with hospital rules.

Caveats remain, as they do with any small, single-center case series. Eight patients cannot establish how often 3D planning changes the final operative decision, whether it shortens operative times, reduces complications, or improves long-term kidney function — outcomes that will require larger, ideally multi-center comparative studies. The near-significant result for the urinary tract hints that some structures remain harder to model than others. Still, the consistency and strength of the reported significance levels, particularly for tumors and blood vessels, give the findings real weight. For a specialty in which the stakes are measured in decades of renal health for young patients, the message from Turin is compelling: letting surgeons rehearse a child’s cancer in three dimensions before entering the operating room is no longer a futuristic gimmick but a practical, statistically validated planning tool that may help more children keep the kidney tissue they will need for the rest of their lives.

Subject of Research: Use of 3D virtual reconstruction from MRI and CT scans for preoperative planning of oncologic renal surgery in children

Article Title: 3D virtual reconstruction: usefulness in preoperative planning for oncologic renal surgery in children

Article References: Cerchia, E., Ruggiero, E., Teruzzi, E., Serpentino, M., Cirigliano, L., Quarello, P., Petraz, M., Catti, M., Allasia, M., Gontero, P., Fagioli, F., & Nappo, S. G. (2026). 3D virtual reconstruction: usefulness in preoperative planning for oncologic renal surgery in children. 3D Printing in Medicine. https://doi.org/10.1186/s41205-026-00340-y

Image Credits: AI Generated

DOI: 10.1186/s41205-026-00340-y

Keywords: 3D virtual reconstruction, pediatric surgery, renal tumors, nephron-sparing surgery, surgical planning, 3D Printing in Medicine, DICOM segmentation, pediatric oncology, kidney cancer, preoperative imaging, MRI, CT

The study, led by Ines Maria Fernandez-Calderon and colleagues at the university’s Department of Biomedical Engineering and the hospital’s Center for 3D Modeling and Printing, was explicitly framed as a demonstration rather than a trial. The authors set out to show the variety of ways their department has deployed 3D technologies to manage difficult lower limb cases, and to capture the perceptions of the operating surgeons through questionnaires. Their conclusion is measured but firm: three-dimensional technologies are particularly advantageous in complex cases that require precise, individualized solutions, especially when conventional methods are insufficient because the anatomy is challenging or the deformity severe.

The technical pipeline behind such planning is worth understanding in detail. It typically begins with computed tomography, whose stacked cross-sectional images are converted into digital three-dimensional models of the patient’s bones. Those models can then be manipulated in software: surgeons and biomedical engineers can rotate the anatomy, measure angles that matter for limb alignment, simulate osteotomy cuts, and test how an implant or graft will fit before anyone touches a scalpel. Selected components are then physically fabricated, often by fused deposition modeling, a 3D printing method that builds objects layer by layer from thermoplastic material such as polylactic acid. The result can be a patient-specific instrument, a physical anatomical model for rehearsal, or a custom-shaped graft or spacer matched to a single patient’s skeleton.

That precision matters because limb reconstruction lives and dies by angles. The authors’ abbreviation list hints at the measurements involved: the mechanical lateral distal femoral angle, the posterior distal femoral angle, and the medial lateral tibial angle are all parameters that determine whether a leg will bear weight in a straight, mechanically sound line after surgery. When a surgeon performs a femoral or tibial osteotomy, the planned correction of these angles must be translated into real bone cuts, and small deviations can compound into lasting misalignment. Patient-specific instrumentation, printed to sit on the patient’s unique bone surface, is designed to carry those planned angles from the digital plan to the operating field.

The four cases presented in the series span the range of what 3D technologies can contribute. Two were pediatric deformity corrections: a 17-year-old female who underwent multiple femoral osteotomies with the aid of custom 3D-printed guides, and a 7-year-old female who underwent a tibial osteotomy guided the same way. In both, the printed guides served as physical embodiments of the surgical plan, positioning cuts so that the intended angular corrections could be achieved in growing bones where every millimeter of alignment influences future development.

The third case moved beyond guides into the shaping of biological material. A 48-year-old female required a calcaneal allograft, meaning donor bone intended to reconstruct the calcaneus, the heel bone that absorbs enormous loads with every step. Rather than trimming the allograft freehand, the team used 3D modeling to shape it, matching the graft’s contours to the defect it needed to fill. The heel is an anatomically unforgiving target: its complex, irregular geometry makes it notoriously difficult to reconstruct from standard implants or generic templates, which is precisely the situation the authors identify as the best fit for 3D assistance.

The fourth case illustrates a different role for the technology entirely. A 21-year-old male was treated with a 3D-modeled tibial spacer as part of the Masquelet technique, a staged reconstruction strategy used for significant segmental bone loss. In the Masquelet approach, a first procedure places a cement spacer in the bone defect, which induces the formation of a vascularized membrane around it; in a second stage, the spacer is removed and the membrane-lined cavity is filled with bone graft. Modeling the spacer in three dimensions before fabrication allows it to be tailored to the patient’s tibial defect, a step the Bogotá team integrated into their preoperative workflow.

Surgeons’ perceptions were formally evaluated through questionnaires, and the series reports that the tools enhanced the team’s understanding of patient-specific anatomy and improved surgical outcomes in these cases. The authors are careful, however, not to oversell the approach. They note that not every case necessitates three-dimensional technologies, and that its application is most appropriate when conventional methods fall short, particularly in anatomically challenging situations or severe deformities. Routine fractures and straightforward procedures, in other words, may not justify the added modeling time, cost, and coordination that a 3D workflow requires.

What emerges most clearly from the study is that the technology is only half of the story. The authors emphasize that the success of these interventions depends on a multidisciplinary approach, combining the expertise of engineers and medical professionals. Their own authorship reflects that model: biomedical engineers from Universidad de los Andes worked alongside the hospital’s orthopedics service, radiology and diagnostic imaging department, and the Center for 3D Modeling and Printing, with one co-author, Javier Navarro-Rueda, also affiliated with the University of Minnesota’s Visible Heart Laboratories. The modeling and printing center itself is funded by the Colombian Ministry of Science, MinCiencias, under contract 744-2021, an indication that national science agencies are investing in hospital-based 3D capabilities as clinical infrastructure rather than laboratory curiosities.

The work was conducted in accordance with the Declaration of Helsinki, with institutional review board and ethics committee approval from Fundación Cardioinfantil, and informed consent obtained from all patients and, for the pediatric cases, from their parents or legal guardians. For a field watching patient-specific instrumentation and 3D printing move steadily from novelty toward standard of care, the Bogotá series offers a practical template: begin with CT data, build a digital twin of the patient’s anatomy, plan the correction collaboratively with engineers, print the guides, models, grafts, or spacers that carry the plan into the operating room, and reserve the whole apparatus for the cases where it genuinely changes what is possible. The authors’ recommendation to other departments is straightforward: consider integrating three-dimensional technologies as an adjunct in the treatment of complex lower extremity reconstruction, because the same digital pipeline that lets a surgeon rehearse a femoral osteotomy on a 17-year-old’s printed femur can reshape a heel graft, design a Masquelet spacer, and turn two-dimensional scans into three-dimensional surgical confidence.

Subject of Research: Use of 3D printing and modeling technologies for preoperative planning in complex lower extremity reconstructive surgery

Article Title: Integration of 3D technologies in preoperative planning for complex lower extremity reconstructions: a descriptive case series study

Article References: Fernandez-Calderon, I. M., Pérez-Cualtán, C. E., Torres-Gómez, D., Brilla, M. A. R., Castro-Páez, C., Pérez, J. M., Rodríguez-Torres, O., Briceño, J. C., & Navarro-Rueda, J. (2026). Integration of 3D technologies in preoperative planning for complex lower extremity reconstructions: a descriptive case series study. 3D Printing in Medicine. https://doi.org/10.1186/s41205-026-00349-3

Image Credits: AI Generated

DOI: 10.1186/s41205-026-00349-3

Keywords: 3D printing, lower limb reconstruction, orthopedic surgery, patient-specific instrumentation, osteotomy, Masquelet technique, surgical planning, computed tomography, biomedical engineering, reconstructive surgery, calcaneal allograft, preoperative planning

The research, led by Janine Rothert and colleagues spanning the University Hospital Schleswig-Holstein in Kiel, Otto-von-Guericke-University Magdeburg, and the University Medical Center Mainz, addresses a concept known as parenchyma-sparing hepatectomy. Unlike major resections that remove entire liver segments or lobes, parenchyma-sparing surgery minimizes the volume of liver tissue removed while maintaining oncological safety. This approach expands eligibility for curative surgery, reduces operative stress and morbidity, and preserves liver function for potential future resections. The stakes are quantifiable: clinicians must preserve a future liver remnant of at least 20 to 30 percent in healthy livers, and at least 40 percent in patients with impaired hepatic reserve. Accurate preoperative planning therefore has to integrate tumor location, arterial and portal venous perfusion, hepatic venous drainage, and biliary anatomy all at once.

To test how different levels of anatomical and functional information shape surgical predictions, the team built three distinct modeling paradigms, each operating on segmentation-derived representations of the liver, tumor, and vessels. The first is a purely geometric, distance-based approach designed for non-anatomical, surface-near tumor resections such as atypical wedge procedures. It uses an Euclidean distance transform to find the shortest path from tumor to liver surface, generates a global resection direction from averaged normalized direction vectors, and then dilates the tumor mask by an 8-millimeter margin, a figure matching the dataset’s average planned minimal resection margin of 7.63 millimeters, before extending the zone toward the liver surface. The result is a cylindrical, maximally tissue-sparing resection proposal that requires no knowledge of blood vessels at all.

The second paradigm is explicitly perfusion-aware. Starting from the same 8-millimeter dilation, the algorithm converts skeletonized portal and hepatic vein segmentations into directed graphs, placing nodes at bifurcations and inferring flow direction from the largest-radius node. Any vessel intersecting the initial resection zone is marked as transected, and all downstream branches are classified as non-perfused. Each liver voxel is then assigned to its nearest perfused or non-perfused vessel following a classical method from Selle and colleagues, defining the viable remnant and the final predicted resection zone. In effect, the model approximates Couinaud segments and simulates the physiological consequence of cutting a specific vessel, something purely geometric tools cannot do.

The third paradigm abandons hand-crafted rules entirely. The researchers formulated resection zone prediction as a volumetric segmentation task and trained a deep learning model on the nnU-Net framework, the self-configuring architecture that has repeatedly set benchmarks in medical image segmentation. Input consisted of three channels, a liver mask, a tumor mask, and a combined portal and hepatic vein mask, with the resection zone as the target. Training used 3D full-resolution patches of 160 by 192 by 224 voxels, a residual large encoder with six down- and upsampling stages, and a combined Dice and cross-entropy loss, run over 1000 epochs with fivefold cross-validation balanced for tumor and resection types.

The evaluation drew on a clinical database from Mainz comprising 312 patients who underwent 338 open liver tumor resections performed by seven different surgeons. After strict inclusion and exclusion criteria based on data integrity, entity integrity, and procedure type, 104 patients with 104 retrospectively defined resection zones remained for analysis. All segmentation masks, generated semiautomatically with surgical planning software, were rasterized onto a common voxel grid with 0.4-millimeter isotropic resolution, keeping boundary discretization errors below one millimeter. Predictions were scored with overlap metrics, the Dice similarity coefficient and intersection over union, and distance metrics, including the 95th-percentile Hausdorff distance, maximum Hausdorff distance, and average surface distance.

The results reveal a striking trade-off. The distance-based model produced predictions with the smallest surface deviation, a 95th-percentile Hausdorff distance of 33.89 millimeters, but suffered from systematic undersegmentation, achieving a Dice score of only 58.18 percent. The perfusion-based method struck the best overall balance, with a Dice score of 67.41 percent and a Hausdorff distance of 37.92 millimeters, though it tended to overestimate the resection region because of its strict binary assumption that tissue downstream of a cut vessel is entirely lost, whereas real hepatic perfusion is highly interconnected. The deep learning model delivered the highest overlap accuracy at 76.31 percent, but with the largest distance errors, a 95th-percentile Hausdorff distance of 65.21 millimeters, reflecting localized boundary inaccuracies and occasional spatially distant false positives that disproportionately inflated the distance metrics.

Statistical analyses added crucial nuance. Pearson correlation tests showed that all three models performed significantly better, in terms of Dice overlap, for deeper tumors, likely because larger tumors extend further into the liver and reduce the relative impact of minor boundary deviations. Higher ratios of tumor volume to resection zone volume also correlated with improved performance across models. Subgroup comparisons using the Mann-Whitney U test found that atypical, non-anatomical wedge resections were consistently harder to predict than standardized segmental resections, underscoring how individualized parenchyma-sparing surgery is, and how challenging it is to replicate algorithmically. Notably, the deep learning model’s advantage was strongest for larger and more standardized resection volumes, while the rule-based approaches retained their edge in constrained, tissue-sparing scenarios.

The authors are careful to position these tools as decision support rather than replacement for surgical judgment. Each paradigm, they argue, functions as a modular building block suited to a different clinical situation: the distance-based model is well suited to maximal parenchyma-sparing resections, particularly for patients with limited functional reserve; the perfusion-based model is advantageous when tumors sit near major vessels where downstream perfusion loss must be anticipated; and the deep learning model offers the strongest raw predictive power where larger resections are planned. Because the rule-based methods expose their logic through adjustable parameters such as the resection margin, they also offer a transparency and clinical controllability that neural networks currently lack.

Looking forward, the team proposes hybrid strategies that fuse the paradigms, integrating perfusion-aware and distance-based reasoning into deep learning either during training or as a post-processing step, adding surface-distance-aware loss functions, clinical metadata such as tumor entity and body composition, and simple connected-component cleanup to remove false positives. Extending the framework to standard segment-based hepatectomies is also on the agenda. With the code publicly released on GitHub, the study offers surgeons something genuinely new: not a single algorithmic answer, but a menu of differently nuanced resection proposals for the same patient, each grounded in a different model of liver anatomy and physiology. In a field where every spared millimeter of functional liver tissue can determine whether a patient tolerates the operation, and whether future curative options remain open, that flexibility could prove transformative.

Subject of Research: Computational modeling of resection zone prediction for parenchyma-sparing liver surgery planning

Article Title: Resection zone prediction for parenchyma-sparing hepatectomy planning: a comparative study of three modeling paradigms

Article References: Rothert, J., Rakshit, J., Salz, J. L., Huettl, F., Ehses, V., Huber, T., Lang, H., Saalfeld, S., & Hille, G. (2026). Resection zone prediction for parenchyma-sparing hepatectomy planning: a comparative study of three modeling paradigms. International Journal of Computer Assisted Radiology and Surgery. https://doi.org/10.1007/s11548-026-03798-7

Image Credits: AI Generated

DOI: 10.1007/s11548-026-03798-7

Keywords: liver cancer, hepatectomy, surgical planning, deep learning, nnU-Net, perfusion modeling, resection zone prediction, parenchyma-sparing surgery, medical image segmentation, Hausdorff distance, Dice similarity coefficient, computational surgery

Congenital bronchial atresia, or CBA, is a rare developmental anomaly in which a lobar, segmental or subsegmental bronchus is focally interrupted while the distal bronchial tree remains intact. Because the airway is blocked proximally, mucus accumulates downstream, forming a mucus-filled cavity known as a bronchocele or mucocele. At the same time, air finds its way into the affected tissue through collateral ventilation channels, causing the trapped lung segment to become hyperinflated. The pairing of a bronchocele with distal hyperinflation is considered the radiological fingerprint of the condition, and in most cases computed tomography can nail the diagnosis by showing the abrupt bronchial interruption, the mucus-filled structure and the adjacent hyperlucent, emphysematous lung.

But the clinical picture becomes murkier when the anomaly sits in the lower lobes. Pulmonary sequestration, a key differential diagnosis for lower-lobe congenital lung lesions, is defined by the complete absence of normal bronchial communication and the presence of an aberrant systemic arterial supply, typically arising from the aorta. Lower-lobe CBA can also present with recurrent infection and cystic or cavitary changes, meaning the two conditions can look strikingly similar when inflammation blurs the anatomical details. That is precisely what happened in this case, and the report underscores why a systematic evaluation of both bronchial continuity and vascular supply is essential before any diagnosis of a congenital lower-lobe lesion is finalized.

The patient’s story began with annual episodes of respiratory infection, each temporarily quieted by oral antibiotics. Chest radiography revealed an abnormal shadow in the right lung field, and CT imaging demonstrated a cavitary lesion with internal fluid retention in the right lower lobe, surrounded by ground-glass opacity suggestive of active inflammation. After a course of antibiotic therapy settled the inflammation, she was referred for surgical management, still carrying the presumptive diagnosis of pulmonary sequestration.

Repeat computed tomography at the treating institution changed the picture dramatically. The scans revealed segmental emphysematous change localized mainly to Segment 7 of the right lower lobe, alongside the cavitary lesion with internal fluid retention and faint residual ground-glass opacity. Critically, the imaging identified an interruption of the right B7 bronchus — the segmental airway serving Segment 7. Just as importantly, no aberrant systemic arterial supply from the aorta was observed anywhere in the region. Instead, the pulmonary artery showed a normal branching pattern, with a normally distributed segmental artery, designated A7, supplying the lesion. Together, these findings pointed decisively away from pulmonary sequestration and toward congenital bronchial atresia, with the cavitary lesion reinterpreted as a bronchocele.

Three-dimensional CT reconstruction sealed the diagnosis. The technique clearly demonstrated the interruption of the B7 bronchus and the normal distribution of the A7 segmental artery, while the pulmonary venous anatomy was confirmed to be unremarkable. This imaging approach, the report notes, is particularly valuable when sublobar resection is being considered, because precise anatomical understanding of the bronchovascular architecture is required for safe and appropriate surgery. In this patient, however, the geometry of the disease made lung-sparing surgery impractical: although the lesion was centered in Segment 7, the hyperinflation extended close to the basal bronchial bifurcation, and inflammatory changes on earlier scans had involved the adjacent segments. Complete resection by segmentectomy was therefore judged too difficult, and the surgical team opted for a thoracoscopic right lower lobectomy.

The operation itself went smoothly. Pulmonary function testing before surgery had been within normal limits, and laboratory findings showed only mild inflammatory change. Intraoperative bronchoscopy confirmed the imaging findings, demonstrating no identifiable orifice of the B7 bronchus at the level of the right intermediate bronchus, while the orifices of B6 and the remaining basal bronchi, B8 through B10, were clearly visible. The procedure took 123 minutes with minimal blood loss, the postoperative course was uneventful, and the patient was discharged on the eighth day after surgery.

Histopathological examination of the resected tissue provided the final confirmation. The cavitary lesion was composed of bronchial structures filled with retained mucus and showed no communication with the central airway — exactly the architecture expected of a bronchocele associated with congenital bronchial atresia. Based on the combined radiological, bronchoscopic and histopathological findings, the team established the final diagnosis of CBA, closing a diagnostic journey that had begun with a completely different suspected condition.

The case carries several important lessons for clinicians and radiologists. Although the combination of a bronchocele and distal hyperinflation is characteristic of CBA, a lower-lobe location, recurrent infection and a cavitary appearance can cause the anomaly to radiologically resemble pulmonary sequestration. The distinction matters enormously: pulmonary sequestration accounts for approximately 0.15 percent to 6.4 percent of congenital pulmonary malformations and is defined by its aberrant systemic blood supply, whereas CBA preserves normal pulmonary arterial supply despite its proximal bronchial interruption. In CBA, the bronchus is interrupted proximally while the distal airway is preserved and filled with mucus; in sequestration, there is no normal bronchial communication at all, and the tissue is fed by a systemic artery, typically from the aorta.

Rarity compounds the diagnostic difficulty. CBA is less frequently encountered in clinical practice than sequestration and is most commonly detected incidentally, with a strong predilection for the upper lobes — particularly the left upper lobe. Lower-lobe involvement is uncommon in adult radiologic series, and segmental bronchial atresia confined to a single basal segment such as S7 is extremely rare. In such cases, recurrent infection and cystic or cavitary changes can closely resemble intralobar pulmonary sequestration, making accurate differentiation genuinely challenging even for experienced teams. The authors emphasize that systematic evaluation of both bronchial continuity and vascular supply is the key to getting it right, and that three-dimensional CT reconstruction may prove useful not only for diagnosis but also for guiding surgical decision-making, from choosing between segmentectomy and lobectomy to mapping the precise anatomy the surgeon will encounter.

Subject of Research: Congenital bronchial atresia of the right lower lobe mimicking pulmonary sequestration

Article Title: Congenital Bronchial Atresia Mimicking Pulmonary Sequestration in the Lower Lobe: A Case Report

Article References: Mitsumata, S., Midorikawa, K., Wakamatsu, K., Kaneda, S., Futamata, T., Iwanaka, T., Ueda, Y., Miyahara, S., Masuda, Y., Nakashima, H., & Sato, T. (2026). Congenital Bronchial Atresia Mimicking Pulmonary Sequestration in the Lower Lobe: A Case Report. Respirology Case Reports, 14(9), Article e70712. https://doi.org/10.1002/rcr2.70712

Image Credits: AI Generated

DOI: 10.1002/rcr2.70712

Keywords: congenital bronchial atresia, pulmonary sequestration, bronchocele, three-dimensional CT reconstruction, thoracoscopic lobectomy, segment 7 right lower lobe, recurrent lung infection, bronchial interruption, segmental emphysema, congenital pulmonary malformation, surgical planning, case report