MANAGEMENT OF ANEURYSMAL BONE CYST WITH BONE GRAFT AND TRICALCIUM PHOSPHATE WITH 6 YEARS OF FOLLOW UP: A CASE REPORT

Aneurysmal Bone Cyst (ABC) is a Benign tumor, Also known as Giant Cell Repetative Granuloma, They are locally destructive hemorrhagic benign cystic legion. According to the definition of the WHO Aneurismal Bone Cyst is expanding osteolytic lesion consisting of blood-filled spaces of variable size and that are separated by connective tissue septae containing trabecula of bone or osteoid tissue and osteoclast giant cells. We report a case of a giant aneurysmal bone cyst in the Middle one-third of Right humerus of a 16 -year-old boy, which was treated with Allograft, Autograft and ender's nail fixation. At 6 Years of follow up Patient regain a pain-free complete Range of motion with radiographically subside of legion.

Feasibility of Multi-Parametric Magnetic Resonance Imaging Combined with Machine Learning in the Assessment of Necrosis of Osteosarcoma after Neoadjuvant Chemotherapy: A Preliminary Study

Background Response evaluation of neoadjuvant chemotherapy (NACT) in patients with osteosarcoma is significant for the termination of ineffective treatment, the development of postoperative chemotherapy regimens, and the prediction of prognosis. However, histological response and tumour necrosis rate can currently be evaluated only in resected specimens after NACT. A preoperatively accurate, noninvasive, and reproducible method of response assessment to NACT is required. In this study, the value of multi-parametric magnetic resonance imaging (MRI) combined with machine learning for assessment of tumour necrosis after NACT for osteosarcoma was investigated.Methods Twelve patients with primary osteosarcoma of limbs underwent NACT and received MRI examination before surgery. Postoperative tumour specimens were made corresponding to the transverse image of MRI. One hundred and two tissue samples were obtained and pathologically divided into tumour survival areas (non-cartilaginous and cartilaginous tumour viable areas) and tumour-nonviable areas (non-cartilaginous tumour necrosis areas, post-necrotic tumour collagen areas, and tumour necrotic cystic/haemorrhagic and secondary aneurismal bone cyst areas). The MRI parameters, including standardised apparent diffusion coefficient (ADC) values, signal intensity values of T2-weighted imaging (T2WI) and subtract-enhanced T1-weighted imaging (ST1WI) were used to train machine learning models based on the random forest algorithm. Three classification tasks of distinguishing tumour survival, non-cartilaginous tumour survival, and cartilaginous tumour survival from tumour nonviable were evaluated by five-fold cross-validation.Results For distinguishing non-cartilaginous tumour survival from tumour nonviable, the classifier constructed with ADC achieved an AUC of 0.93, while the classifier with multi-parametric MRI improved to 0.97 (P=0.0933). For distinguishing tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.83, while the classifier with multi-parametric MRI improved to 0.90 (P<0.05). For distinguishing cartilaginous tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.61, while the classifier with multi-parametric MRI parameters improved to 0.81(P<0.05).ConclusionsThe combination of multi-parametric MRI and machine learning significantly improved the discriminating ability of viable cartilaginous tumour components. Our study suggests that this method may provide an objective and accurate basis for NACT response evaluation in osteosarcoma.

Feasibility of Multi-Parametric Magnetic Resonance Imaging Combined with Machine Learning in the Assessment of Necrosis of Osteosarcoma after Neoadjuvant Chemotherapy: A Preliminary Study

Background Response evaluation of neoadjuvant chemotherapy (NACT) in patients with osteosarcoma is significant for the termination of ineffective treatment, the development of postoperative chemotherapy regimens, and the prediction of prognosis. However, histological response and tumour necrosis rate can currently be evaluated only in resected specimens after NACT. A preoperatively accurate, noninvasive, and reproducible method of response assessment to NACT is required. In this study, the value of multi-parametric magnetic resonance imaging (MRI) combined with machine learning for assessment of tumour necrosis after NACT for osteosarcoma was investigated. Methods Twelve patients with primary osteosarcoma of limbs underwent NACT and received MRI examination before surgery. Postoperative tumour specimens were made corresponding to the transverse image of MRI. One hundred and two tissue samples were obtained and pathologically divided into tumour survival areas (non-cartilaginous and cartilaginous tumour viable areas) and tumour-nonviable areas (non-cartilaginous tumour necrosis areas, post-necrotic tumour collagen areas, and tumour necrotic cystic/haemorrhagic and secondary aneurismal bone cyst areas). The MRI parameters, including standardised apparent diffusion coefficient (ADC) values, signal intensity values of T2-weighted imaging (T2WI) and subtract-enhanced T1-weighted imaging (ST1WI) were used to train machine learning models based on the random forest algorithm. Three classification tasks of distinguishing tumour survival, non-cartilaginous tumour survival, and cartilaginous tumour survival from tumour nonviable were evaluated by five-fold cross-validation. Results For distinguishing non-cartilaginous tumour survival from tumour nonviable, the classifier constructed with ADC achieved an AUC of 0.93, while the classifier with multi-parametric MRI improved to 0.97 ( P =0.0933). For distinguishing tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.83, while the classifier with multi-parametric MRI improved to 0.90 ( P <0.05). For distinguishing cartilaginous tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.61, while the classifier with multi-parametric MRI parameters improved to 0.81( P <0.05). Conclusions The combination of multi-parametric MRI and machine learning significantly improved the discriminating ability of viable cartilaginous tumour components, which can provide an objective and accurate basis for NACT response evaluation in osteosarcoma.

Giant Aggressive Aneurismal Bone Cyst of the Proximal Humerus Unresponsive to Denosumab

Aneurysmal Bone Cyst (ABC) is a destructive lesion. The main treatment is curettage, local adjuvant and grafting. However, it is difficult to apply the optimal surgical procedure in aggressive lesions. In these cases, the use of denosumab prior to surgery has been shown to reduce bone destruction and facilitate surgical treatment. A 22-year-old woman was referred for limited shoulder movement and pain complaints. Physical examination and radiological findings were interpreted in favor of ABC. The biopsy was also found to be consistent with the ABC. Since the lesion was aggressive, denosumab was applied prior to surgery. The mass quickly became calcified and patient’s pain complaint decreased. After stopping denosumab treatment, lesion progressed rapidly and destructive character became dominant at every part of lesion. The patient underwent proximal humeral resection and prosthesis. A painless limb with limited shoulder movement was achieved. Although denosumab application prior to surgery was initially good in this case, after termination of treatment, lesion progressed rapidly and the gains associated with denosumab use was lost.

Bimaxillary Aneurismal Bone Cyst in Patient with End Stage Renal Disease and Hyperparathyroidism: A Rare Case Report and Review of the Literature

Aneurismal bone cyst (ABC) is a rare bony lesion occurring predominantly in long bones. Its jaws’ involvement is uncommon and the simultaneous involvement of both jaws is very rare. This report is about a 27-year-old female experiencing renal failure with ABC involving her maxilla and mandible. The progressive lesion was treated surgically and there was no recurrence after 18 months of follow-up.

Spontaneous Regression after Extensive Recurrence of a Pediatric Cervical Spine Aneurysmal Bone Cyst

Aneurysmal bone cyst is a pseudotumoral lesion. Complete resection prior to selective arterial embolization seems to be the treatment of choice for the more extensive and destructive lesions. In these cases maintaining stability of the cervical spine is critical. This can be very challenging in children and adolescents in whom the axial skeleton is still growing. In this case a young girl presented with a voluminous cervical aneurysmal bone cyst encaging both vertebral arteries and spinal cord. The lesion was treated with aggressive surgical resection, followed by cervical vertebral fusion with instrumentation. After nine months the patient referred no pain and no neurological deficit. MRI scans showed an extensive local recurrence. The family of the young girl refused any other therapy and any other followup. The patients returned to our attention after five years with no pain and neurological deficit. Cervical spine radiographs and MRI scans showed a complete regression of the extensive local recurrence. In the literature, the possibility of spontaneous regression of residual part or local recurrence is reported. The case of this young girl provided the chance to attend a spontaneous regression in an extensive recurrence of aneurismal bone cyst.

Plexiform Ameloblastoma of the Mandible

Ameloblastoma is a common and aggressive odontogenic epithelial tumor. It has an aggressive behavior and recurrent course, and is rarely metastatic. Ameloblastoma represents 1% of all tumors and cysts that involve the maxillomandibular area and about 10% of the odontogenic tumors. It is primarily seen in adults in the third to fifth decade of life, with equal sex predilection. Radiographically, it appears as an expansile radiolucent, with thinned and perforated cortices, and is known to cause root resorption. As it shares common radiographic features with other lesions such as the giant cell tumor, aneurismal bone cyst, and renal cell carcinoma metastasis, a definitive diagnosis can only be made with histopathology. We present an extensive case of plexiform ameloblastoma of the mandible in a 42-year-old female patient.